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# -*- coding: utf-8 -*-
import zmq
import cPickle
from zsync_logger import MYLOGGER as logging
from collections import deque
import zhelpers
import time
|
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2,
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12,
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23,
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12,
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80,
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] | 2.962264 | 53 |
from django.views.generic import TemplateView, DetailView, CreateView
from .models import User
|
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] | 3.846154 | 26 |
from dataclasses import dataclass
@dataclass
@dataclass
@dataclass
@dataclass
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from django import forms
|
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# Copyright (c) 2018 ISP RAS (http://www.ispras.ru)
# Ivannikov Institute for System Programming of the Russian Academy of Sciences
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
from clade import Clade
|
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from django.contrib import admin
from rent.models import Rent,Car
# Register your models here.
admin.site.register(Rent,RentAdmin)
admin.site.register(Car,CarAdmin)
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"""
Handles /webhooks endpoint
Doc: https://developers.mailersend.com/api/v1/webhooks.html
"""
import requests
from mailersend.base import base
data = {}
class NewWebhook(base.NewAPIClient):
"""
Instantiates the /webhooks endpoint object
"""
def __init__(self):
"""
NewWebhook constructor
"""
pass
def get_webhooks(self, domain_id):
"""
Returns a JSON response from the MailerSend API
@params:
domain_id (str): A domain ID
"""
request = requests.get(
f"{self.api_base}/webhooks",
headers=self.headers_default,
json={"domain_id": domain_id},
)
return request.text
def get_webhook_by_id(self, webhook_id):
"""
Returns a JSON response from the MailerSend API
@params:
webhook_id (str): A webhook ID
"""
request = requests.get(
f"{self.api_base}/webhooks/{webhook_id}", headers=self.headers_default
)
return request.text
def set_webhook_url(self, webhook_url):
"""
Sets the webhook 'url' field
@params:
webhook_url (str): A webhook URL
"""
data["url"] = webhook_url
def set_webhook_name(self, webhook_name):
"""
Sets the webhook 'name' field
@params:
webhook_name (str): A webhook name
"""
data["name"] = webhook_name
def set_webhook_events(self, events):
"""
Sets the webhook 'events' field
@params:
events (list): A list containing valid events
"""
data["events"] = events
def set_webhook_enabled(self, enabled=True):
"""
Sets the webhook 'enabled' status field
@params:
enabled (bool): Controls webhook status
"""
data["enabled"] = enabled
def set_webhook_domain(self, domain_id):
"""
Sets the webhook 'domain_id' status field
@params:
domain_id (str): A valid domain ID
"""
data["domain_id"] = domain_id
def update_webhook(self, webhook_id, key, value):
"""
Updates a webhook setting
@params:
webhook_id (str): A valid webhook ID
key (str): A setting key
value (str): Corresponding keys value
"""
request = requests.put(
f"{self.api_base}/webhooks/{webhook_id}",
headers=self.headers_default,
json={f"{key}": value},
)
return request.text
def delete_webhook(self, webhook_id):
"""
Returns a JSON response from the MailerSend API
@params:
webhook_id (str): A valid webhook ID
"""
request = requests.delete(
f"{self.api_base}/webhooks/{webhook_id}", headers=self.headers_default
)
return request.text
def create_webhook(self):
"""
Returns a JSON response from the MailerSend API
"""
request = requests.post(
f"{self.api_base}/webhooks", headers=self.headers_default, json=data
)
return request.text
|
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220,
220,
220,
220,
1441,
2581,
13,
5239,
198
] | 2.132402 | 1,503 |
# -*- coding: utf-8 -*-
#
# Copyright (C) 2020-2021 CERN.
# Copyright (C) 2020-2021 Northwestern University.
#
# Flask-Resources is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
"""Utility for rendering URI template links."""
from ..base import Link
class RecordLink(Link):
"""Short cut for writing record links."""
@staticmethod
def vars(record, vars):
"""Variables for the URI template."""
vars.update({"id": record.pid.pid_value})
def pagination_links(tpl):
"""Create pagination links (prev/selv/next) from the same template."""
return {
"prev": Link(
tpl,
when=lambda pagination, ctx: pagination.has_prev,
vars=lambda pagination, vars: vars["args"].update(
{"page": pagination.prev_page.page}
),
),
"self": Link(tpl),
"next": Link(
tpl,
when=lambda pagination, ctx: pagination.has_next,
vars=lambda pagination, vars: vars["args"].update(
{"page": pagination.next_page.page}
),
),
}
|
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220,
220,
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10612,
198,
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220,
1782,
198
] | 2.299029 | 515 |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'Motors_widget.ui'
#
# Created by: PyQt5 UI code generator 5.13.0
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
|
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2,
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198,
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7560,
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8205,
72,
11,
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54,
312,
11407,
628
] | 2.83908 | 87 |
#!/usr/bin/python
# -*- encoding: utf-8 -*-
from io import BytesIO
import time
import base64
import json
import requests
key = "-fd9YqPnrLnmugQGAhQoimCkQd0t8N8L"
secret = "0GLyRIHDnrjKSlDuflLPO8a6U32hyDUy"
beautify.url = 'https://api-cn.faceplusplus.com/facepp/v2/beautify'
rank.url = 'https://api-cn.faceplusplus.com/facepp/v3/detect'
|
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] | 2.157233 | 159 |
#!/usr/bin/env python3
# coding: utf-8
# @Author: ArthurBernard
# @Email: [email protected]
# @Date: 2020-09-18 21:15:59
# @Last modified by: ArthurBernard
# @Last modified time: 2020-09-18 22:21:22
""" Rolling functions. """
# Built-in packages
# Third party packages
import numpy as np
# Local packages
from fynance.features.roll_functions_cy import *
from fynance._wrappers import WrapperArray
__all__ = ["roll_min", "roll_max"]
# =========================================================================== #
# Min Max #
# =========================================================================== #
@WrapperArray('dtype', 'axis', 'window')
def roll_min(X, w=None, axis=0, dtype=None):
r""" Compute simple rolling minimum of size `w` for each `X`' series.
.. math::
roll\_min^w_t(X) = min(X_{t - w}, ..., X_t)
Parameters
----------
X : np.ndarray[dtype, ndim=1 or 2]
Elements to compute the rolling minimum.
w : int, optional
Size of the lagged window of the rolling minimum, must be positive. If
``w is None`` or ``w=0``, then ``w=X.shape[axis]``. Default is None.
axis : {0, 1}, optional
Axis along wich the computation is done. Default is 0.
dtype : np.dtype, optional
The type of the output array. If `dtype` is not given, infer the data
type from `X` input.
Returns
-------
np.ndarray[dtype, ndim=1 or 2]
Simple rolling minimum of each series.
Examples
--------
>>> X = np.array([60, 100, 80, 120, 160, 80])
>>> roll_min(X, w=3, dtype=np.float64, axis=0)
array([60., 60., 60., 80., 80., 80.])
>>> X = np.array([[60, 60], [100, 100], [80, 80],
... [120, 120], [160, 160], [80, 80]])
>>> roll_min(X, w=3, dtype=np.float64, axis=0)
array([[60., 60.],
[60., 60.],
[60., 60.],
[80., 80.],
[80., 80.],
[80., 80.]])
>>> roll_min(X, w=3, dtype=np.float64, axis=1)
array([[ 60., 60.],
[100., 100.],
[ 80., 80.],
[120., 120.],
[160., 160.],
[ 80., 80.]])
See Also
--------
roll_max
"""
return _roll_min(X, w)
@WrapperArray('dtype', 'axis', 'window')
def roll_max(X, w=None, axis=0, dtype=None):
r""" Compute simple rolling maximum of size `w` for each `X`' series.
.. math::
roll\_max^w_t(X) = max(X_{t - w}, ..., X_t)
Parameters
----------
X : np.ndarray[dtype, ndim=1 or 2]
Elements to compute the rolling maximum.
w : int, optional
Size of the lagged window of the rolling maximum, must be positive. If
``w is None`` or ``w=0``, then ``w=X.shape[axis]``. Default is None.
axis : {0, 1}, optional
Axis along wich the computation is done. Default is 0.
dtype : np.dtype, optional
The type of the output array. If `dtype` is not given, infer the data
type from `X` input.
Returns
-------
np.ndarray[dtype, ndim=1 or 2]
Simple rolling maximum of each series.
Examples
--------
>>> X = np.array([60, 100, 80, 120, 160, 80])
>>> roll_max(X, w=3, dtype=np.float64, axis=0)
array([ 60., 100., 100., 120., 160., 160.])
>>> X = np.array([[60, 60], [100, 100], [80, 80],
... [120, 120], [160, 160], [80, 80]])
>>> roll_max(X, w=3, dtype=np.float64, axis=0)
array([[ 60., 60.],
[100., 100.],
[100., 100.],
[120., 120.],
[160., 160.],
[160., 160.]])
>>> roll_max(X, w=3, dtype=np.float64, axis=1)
array([[ 60., 60.],
[100., 100.],
[ 80., 80.],
[120., 120.],
[160., 160.],
[ 80., 80.]])
See Also
--------
roll_max
"""
return _roll_max(X, w)
|
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""" Test some basic behaviour of msodde.py
Ensure that
- doc and docx are read without error
- garbage returns error return status
- dde-links are found where appropriate
"""
from __future__ import print_function
import unittest
from oletools import msodde
from tests.test_utils import DATA_BASE_DIR as BASE_DIR
import os
from os.path import join
from traceback import print_exc
class TestReturnCode(unittest.TestCase):
""" check return codes and exception behaviour (not text output) """
def test_valid_doc(self):
""" check that a valid doc file leads to 0 exit status """
for filename in (
'dde-test-from-office2003', 'dde-test-from-office2016',
'harmless-clean', 'dde-test-from-office2013-utf_16le-korean'):
self.do_test_validity(join(BASE_DIR, 'msodde',
filename + '.doc'))
def test_valid_docx(self):
""" check that a valid docx file leads to 0 exit status """
for filename in 'dde-test', 'harmless-clean':
self.do_test_validity(join(BASE_DIR, 'msodde',
filename + '.docx'))
def test_valid_docm(self):
""" check that a valid docm file leads to 0 exit status """
for filename in 'dde-test', 'harmless-clean':
self.do_test_validity(join(BASE_DIR, 'msodde',
filename + '.docm'))
def test_valid_xml(self):
""" check that xml leads to 0 exit status """
for filename in 'harmless-clean-2003.xml', 'dde-in-excel2003.xml', \
'dde-in-word2003.xml', 'dde-in-word2007.xml':
self.do_test_validity(join(BASE_DIR, 'msodde', filename))
def test_invalid_none(self):
""" check that no file argument leads to non-zero exit status """
self.do_test_validity('', True)
def test_invalid_empty(self):
""" check that empty file argument leads to non-zero exit status """
self.do_test_validity(join(BASE_DIR, 'basic/empty'), True)
def test_invalid_text(self):
""" check that text file argument leads to non-zero exit status """
self.do_test_validity(join(BASE_DIR, 'basic/text'), True)
def test_encrypted(self):
"""
check that encrypted files lead to non-zero exit status
Currently, only the encryption applied by Office 2010 (CryptoApi RC4
Encryption) is tested.
"""
CRYPT_DIR = join(BASE_DIR, 'encrypted')
ADD_ARGS = '', '-j', '-d', '-f', '-a'
for filename in os.listdir(CRYPT_DIR):
full_name = join(CRYPT_DIR, filename)
for args in ADD_ARGS:
self.do_test_validity(args + ' ' + full_name, True)
def do_test_validity(self, args, expect_error=False):
""" helper for test_valid_doc[x] """
have_exception = False
try:
msodde.process_file(args, msodde.FIELD_FILTER_BLACKLIST)
except Exception:
have_exception = True
print_exc()
except SystemExit as exc: # sys.exit() was called
have_exception = True
if exc.code is None:
have_exception = False
self.assertEqual(expect_error, have_exception,
msg='Args={0}, expect={1}, exc={2}'
.format(args, expect_error, have_exception))
class TestDdeLinks(unittest.TestCase):
""" capture output of msodde and check dde-links are found correctly """
@staticmethod
def get_dde_from_output(output):
""" helper to read dde links from captured output
"""
return [o for o in output.splitlines()]
def test_with_dde(self):
""" check that dde links appear on stdout """
filename = 'dde-test-from-office2003.doc'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_BLACKLIST)
self.assertNotEqual(len(self.get_dde_from_output(output)), 0,
msg='Found no dde links in output of ' + filename)
def test_no_dde(self):
""" check that no dde links appear on stdout """
filename = 'harmless-clean.doc'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_BLACKLIST)
self.assertEqual(len(self.get_dde_from_output(output)), 0,
msg='Found dde links in output of ' + filename)
def test_with_dde_utf16le(self):
""" check that dde links appear on stdout """
filename = 'dde-test-from-office2013-utf_16le-korean.doc'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_BLACKLIST)
self.assertNotEqual(len(self.get_dde_from_output(output)), 0,
msg='Found no dde links in output of ' + filename)
def test_excel(self):
""" check that dde links are found in excel 2007+ files """
expect = ['DDE-Link cmd /c calc.exe', ]
for extn in 'xlsx', 'xlsm', 'xlsb':
output = msodde.process_file(
join(BASE_DIR, 'msodde', 'dde-test.' + extn), msodde.FIELD_FILTER_BLACKLIST)
self.assertEqual(expect, self.get_dde_from_output(output),
msg='unexpected output for dde-test.{0}: {1}'
.format(extn, output))
def test_xml(self):
""" check that dde in xml from word / excel is found """
for name_part in 'excel2003', 'word2003', 'word2007':
filename = 'dde-in-' + name_part + '.xml'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_BLACKLIST)
links = self.get_dde_from_output(output)
self.assertEqual(len(links), 1, 'found {0} dde-links in {1}'
.format(len(links), filename))
self.assertTrue('cmd' in links[0], 'no "cmd" in dde-link for {0}'
.format(filename))
self.assertTrue('calc' in links[0], 'no "calc" in dde-link for {0}'
.format(filename))
def test_clean_rtf_blacklist(self):
""" find a lot of hyperlinks in rtf spec """
filename = 'RTF-Spec-1.7.rtf'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_BLACKLIST)
self.assertEqual(len(self.get_dde_from_output(output)), 1413)
def test_clean_rtf_ddeonly(self):
""" find no dde links in rtf spec """
filename = 'RTF-Spec-1.7.rtf'
output = msodde.process_file(
join(BASE_DIR, 'msodde', filename), msodde.FIELD_FILTER_DDE)
self.assertEqual(len(self.get_dde_from_output(output)), 0,
msg='Found dde links in output of ' + filename)
if __name__ == '__main__':
unittest.main()
|
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] | 2.129562 | 3,288 |
# -!- coding: utf-8 -!-
# Author : AWACS
# Time : 2020/06/12
# ------------------------------------
""" batch change place2dTexture Node for texture in Hypershade Editor,
if you think the default command that come with maya:
---(hold middle mouse button + Ctrl key ,and drag a place2dTexture to the texture node to plug all those slot)
is kind of trouble, or you have too many texture node to operating,here's the solution,a command with maya gui.
- How to install : you can simply run this in script editor of maya,or add it in the shelf,
or run as file like add this in the shelf :
import sys
sys.path.append( your script path(add quotation marks(") on the both side of your path ) )
import Batch_Change_Place2D_GUI
reload (Batch_Change_Place2D_GUI)
- How to use : just select place2d node to confirm,and select the multiple texture node to excute
"""
# ------------------------------------
"""在Hypershade批量替换place2dTexture节点
如果你觉得maya自带的命令：
---(按住鼠标中键+Ctrl，拽住place2dTexture节点，来连接到各种贴图节点)
有点麻烦的话，或者是你有太多贴图节点要连了，
这里是解决方案，一个有maya界面的命令
- 安装方式：你可以直接在maya的script editor里直接运行，或者添加到工具架，再或者在工具架上添加这个来以文件方式运行：
import sys
sys.path.append( 你的脚本路径(需要添加引号(")在路径两侧) )
import Batch_Change_Place2D_GUI
reload (Batch_Change_Place2D_GUI)
- 使用方式：选择好place2dTexture节点，然后点确认(Confirm)，然后选好贴图节点执行连接就行了
"""
import maya.cmds as cmds
Batch_Change_Place2D_GUI()
|
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33,
963,
62,
19400,
62,
27271,
17,
35,
62,
40156,
3419
] | 1.732254 | 803 |
U_scr = 0.5
K_scr = 40
T_air = 298.15
T_top = 303.15
g = 9.8
p_air = air_density(T_air)
p_top = air_density(T_top)
p_mean_air = (p_air + p_top)/2
input_tuple = (U_scr, K_scr, T_air, T_top, g, p_mean_air, p_air, p_top)
# The tuple order is U_ src, K_Scr , T_air, T_top, gravitational coefficient,p_mean_air, p_air, p_Top
a = air_flow_rate(input_tuple)
print(MC_air_top(a))
|
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] | 1.885714 | 210 |
from marshmallow import fields
from ....decorators.pagination import Page
from ....util import expand_message_class
from .base import AdminHolderMessage
@expand_message_class
class PresList(AdminHolderMessage):
"""Presentation get list response message."""
message_type = "presentations-list"
class Fields:
"""Fields for presentation list message."""
results = fields.List(fields.Dict(), description="Retrieved presentations.")
page = fields.Nested(
Page.Schema,
required=False,
data_key="~page",
description="Pagination decorator.",
)
|
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] | 2.768559 | 229 |
#!/usr/bin/env python3
"""
Update Wikifeat couchdb databases from 0.4.0a to 0.5.0
Note: Requires python3
Changes:
1. Added getImageFileIndex view to wiki design documents
"""
import json
import common
import sys
wiki_ddoc = 'wikit'
getImageFileIndex = dict()
getImageFileIndex['map'] = """
function(doc){
if(doc.type==="file"){
const att=doc._attachments;
const contentType=att[Object.keys(att)[0]].content_type;
if(contentType.substring(0,6)==="image/"){
emit(doc.name,doc);
}
}
}
"""
getImageFileIndex['reduce'] = "_count"
args = common.parse_args()
conn = common.get_connection(args.use_ssl, args.couch_server, args.couch_port)
credentials = common.get_credentials(args.adminuser, args.adminpass)
get_headers = common.get_headers(credentials)
put_headers = common.put_headers(credentials)
# Update all the wiki design docs
conn.request("GET", '/_all_dbs', headers=get_headers)
db_list = common.decode_response(conn.getresponse())
wiki_list = [db for db in db_list if db[0:5] == "wiki_"]
# Update the wiki dbs
for wiki in wiki_list:
print("Examining " + wiki)
# Fetch design doc
ddoc_uri = '/' + wiki + '/_design/' + wiki_ddoc
conn.request("GET", ddoc_uri, headers=get_headers)
resp = conn.getresponse()
ddoc = common.decode_response(resp)
print("Updating " + wiki)
ddoc['views']['getImageFileIndex'] = getImageFileIndex
req_body = json.dumps(ddoc)
conn.request("PUT", ddoc_uri, body=req_body, headers=put_headers)
resp = conn.getresponse()
common.decode_response(resp)
if resp.getcode() == 201 or resp.getcode() == 200:
print("Update successful.")
else:
print("Update failed.")
# Lastly, close the connection
conn.close()
|
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2,
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11,
1969,
262,
4637,
198,
37043,
13,
19836,
3419,
198
] | 2.569364 | 692 |
# Binary Logistic Regression Demo
import numpy as np
from TinyFlow.Datasets import spiral_data
from TinyFlow.Metrics import model_accuracy_sigmoid
from TinyFlow.Layers import Layer_Dense
from TinyFlow.Activations import Activation_ReLU, Activation_Sigmoid
from TinyFlow.Loss import Loss_BinaryCrossEntropy
from TinyFlow.Optimizers import Optimizer_Adam
# Create dataset
X, y = spiral_data(100, 2)
# Reshape the labels as they aren't sparse anymore, They're binary, 0 & 1
# Reshape the labels to be a list of lists
# Inner list contains one output (either 0 or 1)
# per each output neuron, 1 in this case
#
# We do this reshaping as spiral data values are mapped directly to
# the sparse class values taht were the ideal "one hot index from
# the network's output". However in this case we're trying to represent
# Binary output. IN this example we have a single output neuron, of a target
# value of either 0 or 1.
y = y.reshape(-1, 1)
# Create a dense layer with 2 input features and 3 output values
# first dense layer, 2 inputs (each sample has 2 features), 64 outputs
dense1 = Layer_Dense(2, 64, weight_regularizer_l2=5e-4,
bias_regulariser_l2=5e-4)
# Create ReLU activation
activation1 = Activation_ReLU()
# Create second dense layer with 64 input features
# (as we take output of previous layer here) and 1 output
dense2 = Layer_Dense(64, 1)
# Create Sigmoid Activation
activation2 = Activation_Sigmoid()
# Create a loss function
loss_function = Loss_BinaryCrossEntropy()
# Create an optimizer
optimizer = Optimizer_Adam(decay=1e-8)
# Train in loop
for epoch in range(10001):
# Make a forward pass of our training adaa through this layer
dense1.forward(X)
# Make a forward pass through our activation function
activation1.forward(dense1.output)
# Make forward pass through second dense layer
dense2.forward(activation1.output)
# Make a forward pass through the second activation function
activation2.forward(dense2.output)
# Calculate the losses from the second activation function
sample_losses = loss_function.forward(activation2.output, y)
# Calculate mean loss
data_loss = np.mean(sample_losses)
# Calculate regularization penalty
regularization_loss = loss_function.regularization_loss(
dense1) + loss_function.regularization_loss(dense2)
# Overall loss
loss = data_loss + regularization_loss
# Calculate accuracy from output of activation2 and targets
# Part in the brackets returns a binary maskk - array consisting
# of True/False values, multiplying it by 1 changes it into array of 1s and 0s
accuracy = model_accuracy_sigmoid(activation2.output, y)
if not epoch % 100:
print(f'epoch: {epoch}, acc: {accuracy:.3f}, loss: {loss:.3f} (data_loss: {data_loss:.3f}, reg_loss: {regularization_loss:.3f}), lr: {optimizer.current_learning_rate:.5f}')
# Backward pass
loss_function.backward(activation2.output, y)
activation2.backward(loss_function.dvalues)
dense2.backward(activation2.dvalues)
activation1.backward(dense2.dvalues)
dense1.backward(activation1.dvalues)
# Update weights
optimizer.pre_update_params()
optimizer.update_params(dense1)
optimizer.update_params(dense2)
optimizer.post_update_params()
# Validate model
# Create test dataset
X_test ,y_test = spiral_data(100, 2)
# Reshape labels to be a list of lists
# Inner list contains one output (either 0 or 1)
# per output neuron, 1 in this case
y_test = y_test.reshape(-1, 1)
# Make a forward pass of the testing data though this layer
dense1.forward(X_test)
# Make a forward pass through the activation function
activation1.forward(dense1.output)
# Make a forward pass through the second dense layer
dense2.forward(activation1.output)
# Make a forward pass through the second activation function
activation2.forward(dense2.output)
# Calculate the sample loses from output of activation2 and targets
sample_losses = loss_function.forward(activation2.output, y_test)
# Calculate mean loss
loss = np.mean(sample_losses)
# Calculate accuracy over test data
accuracy = model_accuracy_sigmoid(activation2.output, y_test)
print(f'validation, acc: {accuracy:.3f}, loss: {loss:.3f}')
|
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] | 3.111437 | 1,364 |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
FBNet classification models
Example code to create the model:
from mobile_cv.model_zoo.models.fbnet_v2 import fbnet
model = fbnet("fbnet_cse", pretrained=True)
model.eval()
Full example code is available at `examples/run_fbnet_v2.py`.
All suported architectures could be found in:
mobile_cv/arch/fbnet_v2/fbnet_modeldef_cls*.py
Architectures with pretrained weights could be found in:
mobile_cv/model_zoo/models/model_info/fbnet_v2/*.json
"""
import typing
import torch
import torch.nn as nn
from mobile_cv.arch.fbnet_v2 import fbnet_builder as mbuilder
from mobile_cv.arch.fbnet_v2 import fbnet_modeldef_cls as modeldef
from mobile_cv.arch.utils import misc
from mobile_cv.model_zoo.models import hub_utils, utils
PRETRAINED_MODELS = _load_pretrained_info()
NAME_MAPPING = {
# external name : internal name
"FBNet_a": "fbnet_a",
"FBNet_b": "fbnet_b",
"FBNet_c": "fbnet_c",
"FBNet_ase": "fbnet_ase",
"FBNet_bse": "fbnet_ase",
"FBNet_cse": "fbnet_ase",
"MobileNetV3": "mnv3",
"FBNetV2_F1": "dmasking_f1",
"FBNetV2_F5": "dmasking_l2",
}
class ClsConvHead(nn.Module):
"""Global average pooling + conv head for classification
"""
def fbnet(arch_name, pretrained=False, progress=True, **kwargs):
"""
Constructs a FBNet architecture named `arch_name`
Args:
arch_name (str): Architecture name
pretrained (bool): If True, returns a model pre-trained on ImageNet
progress (bool): If True, displays a progress bar of the download to stderr
"""
if isinstance(arch_name, str) and arch_name in NAME_MAPPING:
arch_name = NAME_MAPPING[arch_name]
model = FBNet(arch_name, **kwargs)
if pretrained:
assert (
arch_name in PRETRAINED_MODELS
), f"Invalid arch {arch_name}, supported arch {PRETRAINED_MODELS.keys()}"
model_info = PRETRAINED_MODELS[arch_name]
model_path = model_info["model_path"]
state_dict = _load_fbnet_state_dict(model_path, progress=progress)
model.load_state_dict(state_dict)
model.model_info = model_info
return model
|
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62,
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220,
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1441,
2746,
198
] | 2.463146 | 909 |
"""
Author: @ayushmankumar7
Paste this file (prepare_train_mask.py) in "leftImg8bit_trainvaltest/leftImg8bit".
There are 3 folder in this directory - test, train, val.
Paste the file inside the folder containing the 3 folders.
In Command Prompt or Terminal :
python prepare_train_image.py
Link for the label:
https://www.cityscapes-dataset.com/file-handling/?packageID=1
"""
import os
import cv2
import numpy as np
import glob
try:
os.makedirs("train_image")
except:
pass
print("It might take a few time. Be patient! Let this program run in background.")
files = glob.glob("train/*")
for file in files:
images = glob.glob(file+"\\*.png")
for image in images:
img_name = image.split("\\")[-1]
img = cv2.imread(image)
# print(f"train_image/{image}")
cv2.imwrite(f"train_image/{img_name}", img)
print(image, "----> DONE")
print("You train Images is stored in './train_image' successfully! \n You may proceed. \n Thank you")
|
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] | 2.509756 | 410 |
from django.test import TestCase
from .models import *
from django.contrib.auth.models import User
# Create your tests here.
# test for checking instance
# test for saving
# test for deleting Driver or Editor
|
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] | 3.515625 | 64 |
# @lc app=leetcode id=653 lang=python3
#
# [653] Two Sum IV - Input is a BST
#
# https://leetcode.com/problems/two-sum-iv-input-is-a-bst/description/
#
# algorithms
# Easy (57.56%)
# Likes: 2752
# Dislikes: 175
# Total Accepted: 248.7K
# Total Submissions: 430.4K
# Testcase Example: '[5,3,6,2,4,null,7]\n9'
#
# Given the root of a Binary Search Tree and a target number k, return true if
# there exist two elements in the BST such that their sum is equal to the given
# target.
#
#
# Example 1:
#
#
# Input: root = [5,3,6,2,4,null,7], k = 9
# Output: true
#
#
# Example 2:
#
#
# Input: root = [5,3,6,2,4,null,7], k = 28
# Output: false
#
#
# Example 3:
#
#
# Input: root = [2,1,3], k = 4
# Output: true
#
#
# Example 4:
#
#
# Input: root = [2,1,3], k = 1
# Output: false
#
#
# Example 5:
#
#
# Input: root = [2,1,3], k = 3
# Output: true
#
#
#
# Constraints:
#
#
# The number of nodes in the tree is in the range [1, 10^4].
# -10^4 <= Node.val <= 10^4
# root is guaranteed to be a valid binary search tree.
# -10^5 <= k <= 10^5
#
#
#
# @lc tags=tree
# @lc imports=start
from imports import *
# @lc imports=end
# @lc idea=start
#
# 在二叉搜索树中，判断是否有两个数字和为指定值。
# 直接遍历。
#
# @lc idea=end
# @lc group=
# @lc rank=
# @lc code=start
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
# @lc code=end
# @lc main=start
if __name__ == '__main__':
print('Example 1:')
print('Input : ')
print('root = [5,3,6,2,4,null,7], k = 9')
print('Exception :')
print('true')
print('Output :')
print(
str(Solution().findTarget(listToTreeNode([5, 3, 6, 2, 4, None, 7]),
9)))
print()
print('Example 2:')
print('Input : ')
print('root = [5,3,6,2,4,null,7], k = 28')
print('Exception :')
print('false')
print('Output :')
print(
str(Solution().findTarget(listToTreeNode([5, 3, 6, 2, 4, None, 7]),
28)))
print()
print('Example 3:')
print('Input : ')
print('root = [2,1,3], k = 4')
print('Exception :')
print('true')
print('Output :')
print(str(Solution().findTarget(listToTreeNode([2, 1, 3]), 4)))
print()
print('Example 4:')
print('Input : ')
print('root = [2,1,3], k = 1')
print('Exception :')
print('false')
print('Output :')
print(str(Solution().findTarget(listToTreeNode([2, 1, 3]), 1)))
print()
print('Example 5:')
print('Input : ')
print('root = [2,1,3], k = 3')
print('Exception :')
print('true')
print('Output :')
print(str(Solution().findTarget(listToTreeNode([2, 1, 3]), 3)))
print()
print(str(Solution().findTarget(listToTreeNode([1]), 2)))
pass
# @lc main=end
|
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220,
220,
220,
1208,
198,
2,
2488,
44601,
1388,
28,
437
] | 2.136228 | 1,336 |
# Given an unsorted array of integers, find the length of longest continuous increasing subsequence.
# Example 1:
# Input: [1,3,5,4,7]
# Output: 3
# Explanation: The longest continuous increasing subsequence is [1,3,5], its length is 3.
# Even though [1,3,5,7] is also an increasing subsequence, it's not a continuous one where 5 and 7 are separated by 4.
# Example 2:
# Input: [2,2,2,2,2]
# Output: 1
# Explanation: The longest continuous increasing subsequence is [2], its length is 1.
# Note: Length of the array will not exceed 10,000.
# simple DP
|
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2,
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830,
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2829,
27704,
198
] | 3.232558 | 172 |
'''
#############################
# Gerardo Galan Garzafox #
# A00821196 #
# #
# alebrije_lexer.py #
# Created_at 2021-09-25 #
# #
#############################
'''
import sys
import ply.lex as lex
reserved = {
'program' : 'PROGRAM',
'main' : 'MAIN',
'vars' : 'VARS',
'int' : 'INT',
'float' : 'FLOAT',
'bool' : 'BOOL',
'char': 'CHAR',
'string' : 'STRING',
'function' : 'FUNCTION',
'return' : 'RETURN',
'read' : 'READ',
'write' : 'WRITE',
'if' : 'IF',
'else' : 'ELSE',
'while' : 'WHILE',
'for' : 'FOR',
'to' : 'TO',
'void' : 'VOID',
'and' : 'AND',
'or' : 'OR',
'median' : 'MEDIAN',
'mode' : 'MODE',
'mean' : 'MEAN',
'variance' : 'VARIANCE',
'regression' : 'REGRESSION',
'plotxy' : 'PLOTXY',
'max' : 'MAX',
'min' : 'MIN',
}
tokens = list(reserved.values()) + [
'LESS',
'GREATER',
'LESS_EQ',
'GREATER_EQ',
'EQUIVALENT',
'DIFFERENT',
'EQUAL',
'MULT',
'DIV',
'PLUS',
'MINUS',
'REMAINDER',
'EXP',
'MULT_EQ',
'DIV_EQ',
'PLUS_EQ',
'MINUS_EQ',
'L_BRACE',
'R_BRACE',
'L_BRACKET',
'R_BRACKET',
'L_PAR',
'R_PAR',
'COLON',
'SEMICOLON',
'COMMA',
'ID',
'CTE_INT',
'CTE_FLOAT',
'CTE_BOOL',
'CTE_CHAR',
'CTE_STRING'
]
# Simple tokens
t_LESS = r'\<'
t_GREATER = r'\>'
t_LESS_EQ = r'\<\='
t_GREATER_EQ = r'\>\='
t_EQUAL = r'\='
t_MULT = r'\*'
t_DIV = r'\/'
t_PLUS = r'\+'
t_MINUS = r'\-'
t_REMAINDER = r'\%'
t_EXP = r'\^'
t_MULT_EQ = r'\*\='
t_DIV_EQ = r'\/\='
t_PLUS_EQ = r'\+\='
t_MINUS_EQ = r'\-\='
t_L_BRACE = r'\{'
t_R_BRACE = r'\}'
t_L_BRACKET = r'\['
t_R_BRACKET = r'\]'
t_L_PAR = r'\('
t_R_PAR = r'\)'
t_COLON = r'\:'
t_SEMICOLON = r'\;'
t_COMMA = r'\,'
t_EQUIVALENT = r'\=\='
t_DIFFERENT = r'\!\='
t_ignore = ' \t'
t_ignore_COMMENT = r'\/\/.*'
# complex tokens
def t_CTE_BOOL(t):
r'(True|true|False|false)'
t.type = 'CTE_BOOL'
return t
def t_ID(t):
r'[a-zA-Z][a-zA-Z_0-9]*'
reserved_type = reserved.get(t.value, False)
if reserved_type:
t.type = reserved_type
return t
else:
t.type = 'ID'
return t
def t_CTE_FLOAT(t):
r'-?\d+\.\d+'
t.value = float(t.value)
return t
def t_CTE_INT(t):
r'-?\d+'
t.value = int(t.value)
return t
def t_CTE_CHAR(t):
r'(\'((?!\').)\')|(\"((?!\").)\")'
t.type = 'CTE_CHAR'
return t
'''
the regex does a negative look ahead(?!) for ' or ' depending
on the case, so \'\'\' is invalid and so is '
'''
def t_CTE_STRING(t):
r'(\'((?!\').)*\')|(\"((?!\").)*\")'
t.type = 'CTE_STRING'
return t
# Define a rule so we can track line numbers
def t_newline(t):
r'\n+'
t.lexer.lineno += len(t.value)
# build the lexer
lexer = lex.lex()
# Tokenize
if __name__ == '__main__':
code = ''
if len(sys.argv) > 1:
file = open('{0}'.format(sys.argv[1]), 'r')
else:
file = open('Test/test_func.alebrije', 'r')
for line in file:
code += line
# Give the lexer some input
lexer.input(code)
while True:
tok = lexer.token()
if not tok:
break # No more input
print(tok)
|
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] | 1.777658 | 1,862 |
import unittest
from travel_distance_map import GPSPoint, Position
|
[
11748,
555,
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395,
198,
6738,
3067,
62,
30246,
62,
8899,
1330,
15472,
12727,
11,
23158,
628,
198
] | 3.833333 | 18 |
import numpy as np
import re
import json
import os
if __name__=='__main__':
import argparse
import os
import json
from tqdm import tqdm
import pickle
from multiprocessing import Pool
parser = argparse.ArgumentParser()
parser.add_argument("--src_dir", help="source dir", required=True )
parser.add_argument("--dst_file", help="destnation file", required=True )
parser.add_argument("--language", help="use language (ja/hi/ta/japanese/hindi/tamil)", required=True )
parser.add_argument("--num_process", help="process num", type=int, default=8 )
parser.add_argument("--combine", help="Concatenate files with <|endoftext|> separator into chunks of this minimum size", type=int, default=50000 )
parser.add_argument('--clean_text', action='store_true')
args = parser.parse_args()
language = args.language.lower()[:2]
assert language in ["ja","hi","ta"], f"unsupported language: {lang}"
vocabulary = os.path.join("vocabulary", language+"-swe24k.txt")
enc = get_encoder(vocabulary, "emoji.json", language!="ja")
array_file = []
for curDir, dirs, files in os.walk(args.src_dir):
array_file.append((curDir, dirs, files))
with Pool(args.num_process) as p:
p.map(_proc, list(range(args.num_process)))
token_chunks = []
for i in range(args.num_process):
with open('tmp%d.pkl'%i, 'rb') as f:
token_chunks.extend(pickle.load(f))
np.savez_compressed(args.dst_file, *token_chunks)
for i in range(args.num_process):
os.remove('tmp%d.pkl'%i)
print("end")
|
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437,
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198
] | 2.595432 | 613 |
from django.db import migrations, models
|
[
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 3.818182 | 11 |
"""Insall script."""
from setuptools import setup
setup(
name="symbexpr",
version="0.0.1a1",
py_modules=["symbexpr"],
zip_safe=True,
author="Alan Cristhian",
author_email="[email protected]",
description="Systems of equalities, inequalities and constraints.",
license="MIT",
keywords="data structure",
url="https://github.com/AlanCristhian/symbexpr",
)
|
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] | 2.631579 | 152 |
#!/usr/bin/env python
# Copyright 2016 Andy Chu. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
"""
cmd_parse.py - Parse high level shell commands.
"""
from __future__ import print_function
from asdl import const
from core import alloc
from core import util
from core.meta import syntax_asdl, types_asdl, Id, Kind
from frontend import match
from frontend import reader
from osh import braces
from osh import bool_parse
from osh import word
log = util.log
p_die = util.p_die
assign_op_e = syntax_asdl.assign_op_e
command = syntax_asdl.command
command_e = syntax_asdl.command_e
lhs_expr = syntax_asdl.lhs_expr
redir = syntax_asdl.redir
word_part = syntax_asdl.word_part
word_e = syntax_asdl.word_e
osh_word = syntax_asdl.word # TODO: rename
lex_mode_e = types_asdl.lex_mode_e
def _MakeLiteralHereLines(here_lines, arena):
"""Create a line_span and a token for each line."""
tokens = []
for line_id, line, start_offset in here_lines:
line_span = syntax_asdl.line_span(line_id, start_offset, len(line))
span_id = arena.AddLineSpan(line_span)
t = syntax_asdl.token(Id.Lit_Chars, line[start_offset:], span_id)
tokens.append(t)
return [word_part.LiteralPart(t) for t in tokens]
def _ParseHereDocBody(parse_ctx, h, line_reader, arena):
"""Fill in attributes of a pending here doc node."""
# "If any character in word is quoted, the delimiter shall be formed by
# performing quote removal on word, and the here-document lines shall not
# be expanded. Otherwise, the delimiter shall be the word itself."
# NOTE: \EOF counts, or even E\OF
ok, delimiter, delim_quoted = word.StaticEval(h.here_begin)
if not ok:
p_die('Invalid here doc delimiter', word=h.here_begin)
here_lines, last_line = _ReadHereLines(line_reader, h, delimiter)
if delim_quoted: # << 'EOF'
# LiteralPart for each line.
h.stdin_parts = _MakeLiteralHereLines(here_lines, arena)
else:
line_reader = reader.VirtualLineReader(here_lines, arena)
w_parser = parse_ctx.MakeWordParserForHereDoc(line_reader)
w_parser.ReadHereDocBody(h.stdin_parts) # fills this in
end_line_id, end_line, end_pos = last_line
# Create a span with the end terminator. Maintains the invariant that
# the spans "add up".
line_span = syntax_asdl.line_span(end_line_id, end_pos, len(end_line))
h.here_end_span_id = arena.AddLineSpan(line_span)
def _MakeAssignPair(parse_ctx, preparsed):
"""Create an assign_pair from a 4-tuples from DetectAssignment."""
left_token, close_token, part_offset, w = preparsed
if left_token.id == Id.Lit_VarLike: # s=1
if left_token.val[-2] == '+':
var_name = left_token.val[:-2]
op = assign_op_e.PlusEqual
else:
var_name = left_token.val[:-1]
op = assign_op_e.Equal
lhs = lhs_expr.LhsName(var_name)
lhs.spids.append(left_token.span_id)
elif left_token.id == Id.Lit_ArrayLhsOpen: # a[x++]=1
var_name = left_token.val[:-1]
if close_token.val[-2] == '+':
op = assign_op_e.PlusEqual
else:
op = assign_op_e.Equal
# Adapted from tools/osh2oil.py Cursor.PrintUntil
# TODO: Make a method like arena.AppendPieces(start, end, []), and share
# with alias.
pieces = []
for span_id in xrange(left_token.span_id + 1, close_token.span_id):
span = parse_ctx.arena.GetLineSpan(span_id)
line = parse_ctx.arena.GetLine(span.line_id)
piece = line[span.col : span.col + span.length]
pieces.append(piece)
# Now reparse everything between here
code_str = ''.join(pieces)
# NOTE: It's possible that an alias expansion underlies this, not a real file!
# We have to use a SideArena since this will happen during translation.
line_num = 99
source_name = 'TODO'
arena = alloc.SideArena('<LHS array index at line %d of %s>' %
(line_num, source_name))
a_parser = parse_ctx.MakeArithParser(code_str, arena)
expr = a_parser.Parse() # raises util.ParseError
# TODO: It reports from the wrong arena!
lhs = lhs_expr.LhsIndexedName(var_name, expr)
lhs.spids.append(left_token.span_id)
else:
raise AssertionError
# TODO: Should we also create a rhs_exp.ArrayLiteral here?
n = len(w.parts)
if part_offset == n:
val = osh_word.EmptyWord()
else:
val = osh_word.CompoundWord(w.parts[part_offset:])
val = word.TildeDetect(val) or val
pair = syntax_asdl.assign_pair(lhs, op, val)
pair.spids.append(left_token.span_id) # Do we need this?
return pair
def _AppendMoreEnv(preparsed_list, more_env):
"""Helper to modify a SimpleCommand node.
Args:
preparsed: a list of 4-tuples from DetectAssignment
more_env: a list to append env_pairs to
"""
for left_token, close_token, part_offset, w in preparsed_list:
if left_token.id != Id.Lit_VarLike: # can't be a[x]=1
p_die("Environment binding shouldn't look like an array assignment",
token=left_token)
if left_token.val[-2] == '+':
p_die('Expected = in environment binding, got +=', token=left_token)
var_name = left_token.val[:-1]
n = len(w.parts)
if part_offset == n:
val = osh_word.EmptyWord()
else:
val = osh_word.CompoundWord(w.parts[part_offset:])
pair = syntax_asdl.env_pair(var_name, val)
pair.spids.append(left_token.span_id) # Do we need this?
more_env.append(pair)
def _MakeAssignment(parse_ctx, assign_kw, suffix_words):
"""Create an command.Assignment node from a keyword and a list of words.
NOTE: We don't allow dynamic assignments like:
local $1
This can be replaced with eval 'local $1'
"""
# First parse flags, e.g. -r -x -a -A. None of the flags have arguments.
flags = []
n = len(suffix_words)
i = 1
while i < n:
w = suffix_words[i]
ok, static_val, quoted = word.StaticEval(w)
if not ok or quoted:
break # can't statically evaluate
if static_val.startswith('-'):
flags.append(static_val)
else:
break # not a flag, rest are args
i += 1
# Now parse bindings or variable names
pairs = []
while i < n:
w = suffix_words[i]
# declare x[y]=1 is valid
left_token, close_token, part_offset = word.DetectAssignment(w)
if left_token:
pair = _MakeAssignPair(parse_ctx, (left_token, close_token, part_offset, w))
else:
# In aboriginal in variables/sources: export_if_blank does export "$1".
# We should allow that.
# Parse this differently then? # dynamic-export? It sets global
# variables.
ok, static_val, quoted = word.StaticEval(w)
if not ok or quoted:
p_die("Variable names must be unquoted constants", word=w)
# No value is equivalent to ''
if not match.IsValidVarName(static_val):
p_die('Invalid variable name %r', static_val, word=w)
lhs = lhs_expr.LhsName(static_val)
lhs.spids.append(word.LeftMostSpanForWord(w))
pair = syntax_asdl.assign_pair(lhs, assign_op_e.Equal, None)
left_spid = word.LeftMostSpanForWord(w)
pair.spids.append(left_spid)
pairs.append(pair)
i += 1
node = command.Assignment(assign_kw, flags, pairs)
return node
def _SplitSimpleCommandPrefix(words):
"""Second pass of SimpleCommand parsing: look for assignment words."""
preparsed_list = []
suffix_words = []
done_prefix = False
for w in words:
if done_prefix:
suffix_words.append(w)
continue
left_token, close_token, part_offset = word.DetectAssignment(w)
if left_token:
preparsed_list.append((left_token, close_token, part_offset, w))
else:
done_prefix = True
suffix_words.append(w)
return preparsed_list, suffix_words
def _MakeSimpleCommand(preparsed_list, suffix_words, redirects):
"""Create an command.SimpleCommand node."""
# FOO=(1 2 3) ls is not allowed.
for _, _, _, w in preparsed_list:
if word.HasArrayPart(w):
p_die("Environment bindings can't contain array literals", word=w)
# echo FOO=(1 2 3) is not allowed (but we should NOT fail on echo FOO[x]=1).
for w in suffix_words:
if word.HasArrayPart(w):
p_die("Commands can't contain array literals", word=w)
# NOTE: # In bash, {~bob,~jane}/src works, even though ~ isn't the leading
# character of the initial word.
# However, this means we must do tilde detection AFTER brace EXPANSION, not
# just after brace DETECTION like we're doing here.
# The BracedWordTree instances have to be expanded into CompoundWord
# instances for the tilde detection to work.
words2 = braces.BraceDetectAll(suffix_words)
words3 = word.TildeDetectAll(words2)
node = command.SimpleCommand()
node.words = words3
node.redirects = redirects
_AppendMoreEnv(preparsed_list, node.more_env)
return node
NOT_FIRST_WORDS = (
Id.KW_Do, Id.KW_Done, Id.KW_Then, Id.KW_Fi, Id.KW_Elif,
Id.KW_Else, Id.KW_Esac
)
class CommandParser(object):
"""
Args:
word_parse: to get a stream of words
lexer: for lookahead in function def, PushHint of ()
line_reader: for here doc
"""
def Reset(self):
"""Reset our own internal state.
Called by the interactive loop.
"""
# Cursor state set by _Peek()
self.next_lex_mode = lex_mode_e.Outer
self.cur_word = None # current word
self.c_kind = Kind.Undefined
self.c_id = Id.Undefined_Tok
self.pending_here_docs = []
def ResetInputObjects(self):
"""Reset the internal state of our inputs.
Called by the interactive loop.
"""
self.w_parser.Reset()
self.lexer.ResetInputObjects()
self.line_reader.Reset()
# NOTE: If our approach to _MaybeExpandAliases isn't sufficient, we could
# have an expand_alias=True flag here? We would litter the parser with calls
# to this like dash and bash.
#
# Although it might be possible that you really need to mutate the parser
# state, and not just provide a parameter to _Next().
# You might also need a flag to indicate whether the previous expansion ends
# with ' '. I didn't see that in dash or bash code.
def _Next(self, lex_mode=lex_mode_e.Outer):
"""Helper method."""
self.next_lex_mode = lex_mode
def Peek(self):
"""Public method for REPL."""
self._Peek()
return self.cur_word
def _Peek(self):
"""Helper method.
Returns True for success and False on error. Error examples: bad command
sub word, or unterminated quoted string, etc.
"""
if self.next_lex_mode != lex_mode_e.Undefined:
w = self.w_parser.ReadWord(self.next_lex_mode)
assert w is not None
# Here docs only happen in command mode, so other kinds of newlines don't
# count.
if w.tag == word_e.TokenWord and w.token.id == Id.Op_Newline:
for h in self.pending_here_docs:
_ParseHereDocBody(self.parse_ctx, h, self.line_reader, self.arena)
del self.pending_here_docs[:] # No .clear() until Python 3.3.
self.cur_word = w
self.c_kind = word.CommandKind(self.cur_word)
self.c_id = word.CommandId(self.cur_word)
self.next_lex_mode = lex_mode_e.Undefined
def _Eat(self, c_id):
"""Consume a word of a type. If it doesn't match, return False.
Args:
c_id: either EKeyword.* or a token type like Id.Right_Subshell.
TODO: Rationalize / type check this.
"""
self._Peek()
# TODO: Printing something like KW_Do is not friendly. We can map
# backwards using the _KEYWORDS list in osh/lex.py.
if self.c_id != c_id:
p_die('Expected word type %s, got %s', c_id,
word.CommandId(self.cur_word), word=self.cur_word)
self._Next()
def _NewlineOk(self):
"""Check for optional newline and consume it."""
self._Peek()
if self.c_id == Id.Op_Newline:
self._Next()
self._Peek()
def ParseRedirect(self):
"""
Problem: You don't know which kind of redir_node to instantiate before
this? You could stuff them all in one node, and then have a switch() on
the type.
You need different types.
"""
self._Peek()
assert self.c_kind == Kind.Redir, self.cur_word
op = self.cur_word.token
# For now only supporting single digit descriptor
first_char = self.cur_word.token.val[0]
if first_char.isdigit():
fd = int(first_char)
else:
fd = const.NO_INTEGER
if op.id in (Id.Redir_DLess, Id.Redir_DLessDash): # here doc
node = redir.HereDoc()
node.op = op
node.fd = fd
self._Next()
self._Peek()
node.here_begin = self.cur_word
self._Next()
self.pending_here_docs.append(node) # will be filled on next newline.
else:
node = redir.Redir()
node.op = op
node.fd = fd
self._Next()
self._Peek()
if self.c_kind != Kind.Word:
p_die('Invalid token after redirect operator', word=self.cur_word)
new_word = word.TildeDetect(self.cur_word)
node.arg_word = new_word or self.cur_word
self._Next()
return node
def _ParseRedirectList(self):
"""Try parsing any redirects at the cursor.
This is used for blocks only, not commands.
Return None on error.
"""
redirects = []
while True:
self._Peek()
# This prediction needs to ONLY accept redirect operators. Should we
# make them a separate TokeNkind?
if self.c_kind != Kind.Redir:
break
node = self.ParseRedirect()
redirects.append(node)
self._Next()
return redirects
def _ScanSimpleCommand(self):
"""First pass: Split into redirects and words."""
redirects = []
words = []
# Set a reference so we can inspect state after a failed parse!
self.parse_ctx.trail.SetLatestWords(words, redirects)
while True:
self._Peek()
if self.c_kind == Kind.Redir:
node = self.ParseRedirect()
redirects.append(node)
elif self.c_kind == Kind.Word:
words.append(self.cur_word)
else:
break
self._Next()
return redirects, words
def _MaybeExpandAliases(self, words, cur_aliases):
"""Try to expand aliases.
Our implementation of alias has two design choices:
- Where to insert it in parsing. We do it at the end of ParseSimpleCommand.
- What grammar rule to parse the expanded alias buffer with. In our case
it's ParseCommand().
This doesn't quite match what other shells do, but I can't figure out a
better places.
Most test cases pass, except for ones like:
alias LBRACE='{'
LBRACE echo one; echo two; }
alias MULTILINE='echo 1
echo 2
echo 3'
MULTILINE
NOTE: dash handles aliases in a totally diferrent way. It has a global
variable checkkwd in parser.c. It assigns it all over the grammar, like
this:
checkkwd = CHKNL | CHKKWD | CHKALIAS;
The readtoken() function checks (checkkwd & CHKALIAS) and then calls
lookupalias(). This seems to provide a consistent behavior among shells,
but it's less modular and testable.
Bash also uses a global 'parser_state & PST_ALEXPNEXT'.
Returns:
A command node if any aliases were expanded, or None otherwise.
"""
# The last char that we might parse.
right_spid = word.RightMostSpanForWord(words[-1])
first_word_str = None # for error message
expanded = []
i = 0
n = len(words)
while i < n:
w = words[i]
ok, word_str, quoted = word.StaticEval(w)
if not ok or quoted:
break
alias_exp = self.aliases.get(word_str)
if alias_exp is None:
break
# Prevent infinite loops. This is subtle: we want to prevent infinite
# expansion of alias echo='echo x'. But we don't want to prevent
# expansion of the second word in 'echo echo', so we add 'i' to
# "cur_aliases".
if (word_str, i) in cur_aliases:
break
if i == 0:
first_word_str = word_str # for error message
#log('%r -> %r', word_str, alias_exp)
cur_aliases.append((word_str, i))
expanded.append(alias_exp)
i += 1
if not alias_exp.endswith(' '):
# alias e='echo [ ' is the same expansion as
# alias e='echo ['
# The trailing space indicates whether we should continue to expand
# aliases; it's not part of it.
expanded.append(' ')
break # No more expansions
if not expanded: # No expansions; caller does parsing.
return None
# We got some expansion. Now copy the rest of the words.
# We need each NON-REDIRECT word separately! For example:
# $ echo one >out two
# dash/mksh/zsh go beyond the first redirect!
while i < n:
w = words[i]
left_spid = word.LeftMostSpanForWord(w)
right_spid = word.RightMostSpanForWord(w)
# Adapted from tools/osh2oil.py Cursor.PrintUntil
for span_id in xrange(left_spid, right_spid + 1):
span = self.arena.GetLineSpan(span_id)
line = self.arena.GetLine(span.line_id)
piece = line[span.col : span.col + span.length]
expanded.append(piece)
expanded.append(' ') # Put space back between words.
i += 1
code_str = ''.join(expanded)
lines = code_str.splitlines(True) # Keep newlines
line_info = []
# TODO: Add location information
self.arena.PushSource(
'<expansion of alias %r at line %d of %s>' %
(first_word_str, -1, 'TODO'))
try:
for i, line in enumerate(lines):
line_id = self.arena.AddLine(line, i+1)
line_info.append((line_id, line, 0))
finally:
self.arena.PopSource()
line_reader = reader.VirtualLineReader(line_info, self.arena)
cp = self.parse_ctx.MakeOshParser(line_reader)
try:
node = cp.ParseCommand(cur_aliases=cur_aliases)
except util.ParseError as e:
# Failure to parse alias expansion is a fatal error
# We don't need more handling here/
raise
if 0:
log('AFTER expansion:')
from osh import ast_lib
ast_lib.PrettyPrint(node)
return node
# Flags that indicate an assignment should be parsed like a command.
_ASSIGN_COMMANDS = set([
(Id.Assign_Declare, '-f'), # function defs
(Id.Assign_Declare, '-F'), # function names
(Id.Assign_Declare, '-p'), # print
(Id.Assign_Typeset, '-f'),
(Id.Assign_Typeset, '-F'),
(Id.Assign_Typeset, '-p'),
(Id.Assign_Local, '-p'),
(Id.Assign_Readonly, '-p'),
# Hm 'export -p' is more like a command. But we're parsing it
# dynamically now because of some wrappers.
# Maybe we could change this.
#(Id.Assign_Export, '-p'),
])
# Flags to parse like assignments: -a -r -x (and maybe -i)
def ParseSimpleCommand(self, cur_aliases):
"""
Fixed transcription of the POSIX grammar (TODO: port to grammar/Shell.g)
io_file : '<' filename
| LESSAND filename
...
io_here : DLESS here_end
| DLESSDASH here_end
redirect : IO_NUMBER (io_redirect | io_here)
prefix_part : ASSIGNMENT_WORD | redirect
cmd_part : WORD | redirect
assign_kw : Declare | Export | Local | Readonly
# Without any words it is parsed as a command, not an assigment
assign_listing : assign_kw
# Now we have something to do (might be changing assignment flags too)
# NOTE: any prefixes should be a warning, but they are allowed in shell.
assignment : prefix_part* assign_kw (WORD | ASSIGNMENT_WORD)+
# an external command, a function call, or a builtin -- a "word_command"
word_command : prefix_part* cmd_part+
simple_command : assign_listing
| assignment
| proc_command
Simple imperative algorithm:
1) Read a list of words and redirects. Append them to separate lists.
2) Look for the first non-assignment word. If it's declare, etc., then
keep parsing words AND assign words. Otherwise, just parse words.
3) If there are no non-assignment words, then it's a global assignment.
{ redirects, global assignments } OR
{ redirects, prefix_bindings, words } OR
{ redirects, ERROR_prefix_bindings, keyword, assignments, words }
THEN CHECK that prefix bindings don't have any array literal parts!
global assignment and keyword assignments can have the of course.
well actually EXPORT shouldn't have them either -- WARNING
3 cases we want to warn: prefix_bindings for assignment, and array literal
in prefix bindings, or export
A command can be an assignment word, word, or redirect on its own.
ls
>out.txt
>out.txt FOO=bar # this touches the file, and hten
Or any sequence:
ls foo bar
<in.txt ls foo bar >out.txt
<in.txt ls >out.txt foo bar
Or add one or more environment bindings:
VAR=val env
>out.txt VAR=val env
here_end vs filename is a matter of whether we test that it's quoted. e.g.
<<EOF vs <<'EOF'.
"""
result = self._ScanSimpleCommand()
redirects, words = result
if not words: # e.g. >out.txt # redirect without words
node = command.SimpleCommand()
node.redirects = redirects
return node
preparsed_list, suffix_words = _SplitSimpleCommandPrefix(words)
if not suffix_words: # ONE=1 a[x]=1 TWO=2 (with no other words)
if redirects:
left_token, _, _, _ = preparsed_list[0]
p_die("Global assignment shouldn't have redirects", token=left_token)
pairs = []
for preparsed in preparsed_list:
pairs.append(_MakeAssignPair(self.parse_ctx, preparsed))
node = command.Assignment(Id.Assign_None, [], pairs)
left_spid = word.LeftMostSpanForWord(words[0])
node.spids.append(left_spid) # no keyword spid to skip past
return node
kind, kw_token = word.KeywordToken(suffix_words[0])
if kind == Kind.Assign:
# Here we StaticEval suffix_words[1] to see if we have an ASSIGNMENT COMMAND
# like 'typeset -p', which lists variables -- a SimpleCommand rather than
# an Assignment.
#
# Note we're not handling duplicate flags like 'typeset -pf'. I see this
# in bashdb (bash debugger) but it can just be changed to 'typeset -p
# -f'.
is_command = False
if len(suffix_words) > 1:
ok, val, _ = word.StaticEval(suffix_words[1])
if ok and (kw_token.id, val) in self._ASSIGN_COMMANDS:
is_command = True
if is_command: # declare -f, declare -p, typeset -p, etc.
node = _MakeSimpleCommand(preparsed_list, suffix_words, redirects)
return node
if redirects:
# Attach the error location to the keyword. It would be more precise
# to attach it to the
p_die("Assignments shouldn't have redirects", token=kw_token)
if preparsed_list: # FOO=bar local spam=eggs not allowed
# Use the location of the first value. TODO: Use the whole word
# before splitting.
left_token, _, _, _ = preparsed_list[0]
p_die("Assignments shouldn't have environment bindings", token=left_token)
# declare str='', declare -a array=()
node = _MakeAssignment(self.parse_ctx, kw_token.id, suffix_words)
node.spids.append(kw_token.span_id)
return node
if kind == Kind.ControlFlow:
if redirects:
p_die("Control flow shouldn't have redirects", token=kw_token)
if preparsed_list: # FOO=bar local spam=eggs not allowed
# TODO: Change location as above
left_token, _, _, _ = preparsed_list[0]
p_die("Control flow shouldn't have environment bindings",
token=left_token)
# Attach the token for errors. (Assignment may not need it.)
if len(suffix_words) == 1:
arg_word = None
elif len(suffix_words) == 2:
arg_word = suffix_words[1]
else:
p_die('Unexpected argument to %r', kw_token.val, word=suffix_words[2])
return command.ControlFlow(kw_token, arg_word)
# If any expansions were detected, then parse again.
node = self._MaybeExpandAliases(suffix_words, cur_aliases)
if node:
# NOTE: There are other types of nodes with redirects. Do they matter?
if node.tag == command_e.SimpleCommand:
node.redirects = redirects
_AppendMoreEnv(preparsed_list, node.more_env)
return node
# TODO check that we don't have env1=x x[1]=y env2=z here.
# FOO=bar printenv.py FOO
node = _MakeSimpleCommand(preparsed_list, suffix_words, redirects)
return node
def ParseBraceGroup(self):
"""
brace_group : LBrace command_list RBrace ;
"""
left_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.Lit_LBrace)
c_list = self._ParseCommandList()
assert c_list is not None
# Not needed
#right_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.Lit_RBrace)
node = command.BraceGroup(c_list.children)
node.spids.append(left_spid)
return node
def ParseDoGroup(self):
"""
Used by ForEach, ForExpr, While, Until. Should this be a Do node?
do_group : Do command_list Done ; /* Apply rule 6 */
"""
self._Eat(Id.KW_Do)
do_spid = word.LeftMostSpanForWord(self.cur_word) # after _Eat
c_list = self._ParseCommandList() # could be any thing
assert c_list is not None
self._Eat(Id.KW_Done)
done_spid = word.LeftMostSpanForWord(self.cur_word) # after _Eat
node = command.DoGroup(c_list.children)
node.spids.extend((do_spid, done_spid))
return node
def ParseForWords(self):
"""
for_words : WORD* for_sep
;
for_sep : ';' newline_ok
| NEWLINES
;
"""
words = []
# The span_id of any semi-colon, so we can remove it.
semi_spid = const.NO_INTEGER
while True:
self._Peek()
if self.c_id == Id.Op_Semi:
semi_spid = self.cur_word.token.span_id # TokenWord
self._Next()
self._NewlineOk()
break
elif self.c_id == Id.Op_Newline:
self._Next()
break
if self.cur_word.tag != word_e.CompoundWord:
# TODO: Can we also show a pointer to the 'for' keyword?
p_die('Invalid word in for loop', word=self.cur_word)
words.append(self.cur_word)
self._Next()
return words, semi_spid
def _ParseForExprLoop(self):
"""
for (( init; cond; update )) for_sep? do_group
"""
node = self.w_parser.ReadForExpression()
assert node is not None
self._Next()
self._Peek()
if self.c_id == Id.Op_Semi:
self._Next()
self._NewlineOk()
elif self.c_id == Id.Op_Newline:
self._Next()
elif self.c_id == Id.KW_Do: # missing semicolon/newline allowed
pass
else:
p_die('Invalid word after for expression', word=self.cur_word)
body_node = self.ParseDoGroup()
assert body_node is not None
node.body = body_node
return node
def ParseFor(self):
"""
for_clause : For for_name newline_ok (in for_words? for_sep)? do_group ;
| For '((' ... TODO
"""
self._Eat(Id.KW_For)
self._Peek()
if self.c_id == Id.Op_DLeftParen:
node = self._ParseForExprLoop()
else:
node = self._ParseForEachLoop()
return node
def ParseWhileUntil(self):
"""
while_clause : While command_list do_group ;
until_clause : Until command_list do_group ;
"""
keyword = self.cur_word.parts[0].token
# This is ensured by the caller
assert keyword.id in (Id.KW_While, Id.KW_Until), keyword
self._Next() # skip while
cond_node = self._ParseCommandList()
assert cond_node is not None
body_node = self.ParseDoGroup()
assert body_node is not None
return command.WhileUntil(keyword, cond_node.children, body_node)
def ParseCaseItem(self):
"""
case_item: '('? pattern ('|' pattern)* ')'
newline_ok command_term? trailer? ;
"""
self.lexer.PushHint(Id.Op_RParen, Id.Right_CasePat)
left_spid = word.LeftMostSpanForWord(self.cur_word)
if self.c_id == Id.Op_LParen:
self._Next()
pat_words = []
while True:
self._Peek()
pat_words.append(self.cur_word)
self._Next()
self._Peek()
if self.c_id == Id.Op_Pipe:
self._Next()
else:
break
rparen_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.Right_CasePat)
self._NewlineOk()
if self.c_id not in (Id.Op_DSemi, Id.KW_Esac):
c_list = self._ParseCommandTerm()
assert c_list is not None
action_children = c_list.children
else:
action_children = []
dsemi_spid = const.NO_INTEGER
last_spid = const.NO_INTEGER
self._Peek()
if self.c_id == Id.KW_Esac:
last_spid = word.LeftMostSpanForWord(self.cur_word)
elif self.c_id == Id.Op_DSemi:
dsemi_spid = word.LeftMostSpanForWord(self.cur_word)
self._Next()
else:
# Happens on EOF
p_die('Expected ;; or esac', word=self.cur_word)
self._NewlineOk()
arm = syntax_asdl.case_arm(pat_words, action_children)
arm.spids.extend((left_spid, rparen_spid, dsemi_spid, last_spid))
return arm
def ParseCaseList(self, arms):
"""
case_list: case_item (DSEMI newline_ok case_item)* DSEMI? newline_ok;
"""
self._Peek()
while True:
# case item begins with a command word or (
if self.c_id == Id.KW_Esac:
break
if self.c_kind != Kind.Word and self.c_id != Id.Op_LParen:
break
arm = self.ParseCaseItem()
assert arm is not None
arms.append(arm)
self._Peek()
# Now look for DSEMI or ESAC
def ParseCase(self):
"""
case_clause : Case WORD newline_ok in newline_ok case_list? Esac ;
"""
case_node = command.Case()
case_spid = word.LeftMostSpanForWord(self.cur_word)
self._Next() # skip case
self._Peek()
case_node.to_match = self.cur_word
self._Next()
self._NewlineOk()
in_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.KW_In)
self._NewlineOk()
if self.c_id != Id.KW_Esac: # empty case list
self.ParseCaseList(case_node.arms)
# TODO: should it return a list of nodes, and extend?
self._Peek()
esac_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.KW_Esac)
self._Next()
case_node.spids.extend((case_spid, in_spid, esac_spid))
return case_node
def _ParseElifElse(self, if_node):
"""
else_part: (Elif command_list Then command_list)* Else command_list ;
"""
arms = if_node.arms
self._Peek()
while self.c_id == Id.KW_Elif:
elif_spid = word.LeftMostSpanForWord(self.cur_word)
self._Next() # skip elif
cond = self._ParseCommandList()
assert cond is not None
then_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.KW_Then)
body = self._ParseCommandList()
assert body is not None
arm = syntax_asdl.if_arm(cond.children, body.children)
arm.spids.extend((elif_spid, then_spid))
arms.append(arm)
if self.c_id == Id.KW_Else:
else_spid = word.LeftMostSpanForWord(self.cur_word)
self._Next()
body = self._ParseCommandList()
assert body is not None
if_node.else_action = body.children
else:
else_spid = const.NO_INTEGER
if_node.spids.append(else_spid)
def ParseIf(self):
"""
if_clause : If command_list Then command_list else_part? Fi ;
"""
if_node = command.If()
self._Next() # skip if
cond = self._ParseCommandList()
assert cond is not None
then_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.KW_Then)
body = self._ParseCommandList()
assert body is not None
arm = syntax_asdl.if_arm(cond.children, body.children)
arm.spids.extend((const.NO_INTEGER, then_spid)) # no if spid at first?
if_node.arms.append(arm)
if self.c_id in (Id.KW_Elif, Id.KW_Else):
self._ParseElifElse(if_node)
else:
if_node.spids.append(const.NO_INTEGER) # no else spid
fi_spid = word.LeftMostSpanForWord(self.cur_word)
self._Eat(Id.KW_Fi)
if_node.spids.append(fi_spid)
return if_node
def ParseTime(self):
"""
time [-p] pipeline
According to bash help.
"""
self._Next() # skip time
pipeline = self.ParsePipeline()
assert pipeline is not None
return command.TimeBlock(pipeline)
def ParseCompoundCommand(self):
"""
compound_command : brace_group
| subshell
| for_clause
| while_clause
| until_clause
| if_clause
| case_clause
| time_clause
| [[ BoolExpr ]]
| (( ArithExpr ))
;
"""
if self.c_id == Id.Lit_LBrace:
return self.ParseBraceGroup()
if self.c_id == Id.Op_LParen:
return self.ParseSubshell()
if self.c_id == Id.KW_For:
return self.ParseFor()
if self.c_id in (Id.KW_While, Id.KW_Until):
return self.ParseWhileUntil()
if self.c_id == Id.KW_If:
return self.ParseIf()
if self.c_id == Id.KW_Case:
return self.ParseCase()
if self.c_id == Id.KW_Time:
return self.ParseTime()
# Example of redirect that is observable:
# $ (( $(echo one 1>&2; echo 2) > 0 )) 2> out.txt
if self.c_id == Id.KW_DLeftBracket:
return self.ParseDBracket()
if self.c_id == Id.Op_DLeftParen:
return self.ParseDParen()
# This never happens?
p_die('Unexpected word while parsing compound command', word=self.cur_word)
def ParseFunctionBody(self, func):
"""
function_body : compound_command io_redirect* ; /* Apply rule 9 */
"""
body = self.ParseCompoundCommand()
assert body is not None
redirects = self._ParseRedirectList()
assert redirects is not None
func.body = body
func.redirects = redirects
def ParseFunctionDef(self):
"""
function_header : fname '(' ')'
function_def : function_header newline_ok function_body ;
Precondition: Looking at the function name.
Post condition:
NOTE: There is an ambiguity with:
function foo ( echo hi ) and
function foo () ( echo hi )
Bash only accepts the latter, though it doesn't really follow a grammar.
"""
left_spid = word.LeftMostSpanForWord(self.cur_word)
ok, name = word.AsFuncName(self.cur_word)
if not ok:
p_die('Invalid function name', word=self.cur_word)
self._Next() # skip function name
# Must be true beacuse of lookahead
self._Peek()
assert self.c_id == Id.Op_LParen, self.cur_word
self.lexer.PushHint(Id.Op_RParen, Id.Right_FuncDef)
self._Next()
self._Eat(Id.Right_FuncDef)
after_name_spid = word.LeftMostSpanForWord(self.cur_word) + 1
self._NewlineOk()
func = command.FuncDef()
func.name = name
self.ParseFunctionBody(func)
func.spids.append(left_spid)
func.spids.append(after_name_spid)
return func
def ParseKshFunctionDef(self):
"""
ksh_function_def : 'function' fname ( '(' ')' )? newline_ok function_body
"""
left_spid = word.LeftMostSpanForWord(self.cur_word)
self._Next() # skip past 'function'
self._Peek()
ok, name = word.AsFuncName(self.cur_word)
if not ok:
p_die('Invalid KSH-style function name', word=self.cur_word)
after_name_spid = word.LeftMostSpanForWord(self.cur_word) + 1
self._Next() # skip past 'function name
self._Peek()
if self.c_id == Id.Op_LParen:
self.lexer.PushHint(Id.Op_RParen, Id.Right_FuncDef)
self._Next()
self._Eat(Id.Right_FuncDef)
# Change it: after )
after_name_spid = word.LeftMostSpanForWord(self.cur_word) + 1
self._NewlineOk()
func = command.FuncDef()
func.name = name
self.ParseFunctionBody(func)
func.spids.append(left_spid)
func.spids.append(after_name_spid)
return func
def ParseCoproc(self):
"""
TODO:
"""
raise NotImplementedError
def ParseDBracket(self):
"""
Pass the underlying word parser off to the boolean expression parser.
"""
maybe_error_word = self.cur_word
# TODO: Test interactive. Without closing ]], you should get > prompt
# (PS2)
self._Next() # skip [[
b_parser = bool_parse.BoolParser(self.w_parser)
bnode = b_parser.Parse() # May raise
return command.DBracket(bnode)
def ParseCommand(self, cur_aliases=None):
"""
command : simple_command
| compound_command io_redirect*
| function_def
| ksh_function_def
;
"""
cur_aliases = cur_aliases or []
self._Peek()
if self.c_id in NOT_FIRST_WORDS:
p_die('Unexpected word when parsing command', word=self.cur_word)
if self.c_id == Id.KW_Function:
return self.ParseKshFunctionDef()
# NOTE: We should have another Kind for "initial keywords". And then
# NOT_FIRST_WORDS are "secondary keywords".
if self.c_id in (
Id.KW_DLeftBracket, Id.Op_DLeftParen, Id.Op_LParen, Id.Lit_LBrace,
Id.KW_For, Id.KW_While, Id.KW_Until, Id.KW_If, Id.KW_Case, Id.KW_Time):
node = self.ParseCompoundCommand()
assert node is not None
if node.tag != command_e.TimeBlock: # The only one without redirects
node.redirects = self._ParseRedirectList()
assert node.redirects is not None
return node
# NOTE: I added this to fix cases in parse-errors.test.sh, but it doesn't
# work because Lit_RBrace is in END_LIST below.
# TODO: KW_Do is also invalid here.
if self.c_id == Id.Lit_RBrace:
p_die('Unexpected right brace', word=self.cur_word)
if self.c_kind == Kind.Redir: # Leading redirect
return self.ParseSimpleCommand(cur_aliases)
if self.c_kind == Kind.Word:
if (self.w_parser.LookAhead() == Id.Op_LParen and
not word.IsVarLike(self.cur_word)):
return self.ParseFunctionDef() # f() { echo; } # function
# echo foo
# f=(a b c) # array
# array[1+2]+=1
return self.ParseSimpleCommand(cur_aliases)
if self.c_kind == Kind.Eof:
p_die("Unexpected EOF while parsing command", word=self.cur_word)
# e.g. )
p_die("Invalid word while parsing command", word=self.cur_word)
def ParsePipeline(self):
"""
pipeline : Bang? command ( '|' newline_ok command )* ;
"""
negated = False
self._Peek()
if self.c_id == Id.KW_Bang:
negated = True
self._Next()
child = self.ParseCommand()
assert child is not None
children = [child]
self._Peek()
if self.c_id not in (Id.Op_Pipe, Id.Op_PipeAmp):
if negated:
node = command.Pipeline(children, negated)
return node
else:
return child
pipe_index = 0
stderr_indices = []
if self.c_id == Id.Op_PipeAmp:
stderr_indices.append(pipe_index)
pipe_index += 1
while True:
self._Next() # skip past Id.Op_Pipe or Id.Op_PipeAmp
self._NewlineOk()
child = self.ParseCommand()
assert child is not None
children.append(child)
self._Peek()
if self.c_id not in (Id.Op_Pipe, Id.Op_PipeAmp):
break
if self.c_id == Id.Op_PipeAmp:
stderr_indices.append(pipe_index)
pipe_index += 1
node = command.Pipeline(children, negated)
node.stderr_indices = stderr_indices
return node
def ParseAndOr(self):
"""
and_or : and_or ( AND_IF | OR_IF ) newline_ok pipeline
| pipeline
Note that it is left recursive and left associative. We parse it
iteratively with a token of lookahead.
"""
child = self.ParsePipeline()
assert child is not None
self._Peek()
if self.c_id not in (Id.Op_DPipe, Id.Op_DAmp):
return child
ops = []
children = [child]
while True:
ops.append(self.c_id)
self._Next() # skip past || &&
self._NewlineOk()
child = self.ParsePipeline()
assert child is not None
children.append(child)
self._Peek()
if self.c_id not in (Id.Op_DPipe, Id.Op_DAmp):
break
node = command.AndOr(ops, children)
return node
# NOTE: _ParseCommandLine and _ParseCommandTerm are similar, but different.
# At the top level, We want to execute after every line:
# - to process alias
# - to process 'exit', because invalid syntax might appear after it
# But for say a while loop body, we want to parse the whole thing at once, and
# then execute it. We don't want to parse it over and over again!
# COMPARE
# command_line : and_or (sync_op and_or)* trailer? ; # TOP LEVEL
# command_term : and_or (trailer and_or)* ; # CHILDREN
def _ParseCommandLine(self):
"""
command_line : and_or (sync_op and_or)* trailer? ;
trailer : sync_op newline_ok
| NEWLINES;
sync_op : '&' | ';';
NOTE: This rule causes LL(k > 1) behavior. We would have to peek to see if
there is another command word after the sync op.
But it's easier to express imperatively. Do the following in a loop:
1. ParseAndOr
2. Peek.
a. If there's a newline, then return. (We're only parsing a single
line.)
b. If there's a sync_op, process it. Then look for a newline and
return. Otherwise, parse another AndOr.
"""
# NOTE: This is slightly different than END_LIST in _ParseCommandTerm, and
# unfortunately somewhat ad hoc.
END_LIST = (Id.Op_Newline, Id.Eof_Real, Id.Op_RParen)
children = []
done = False
while not done:
child = self.ParseAndOr()
assert child is not None
self._Peek()
if self.c_id in (Id.Op_Semi, Id.Op_Amp): # also Id.Op_Amp.
child = command.Sentence(child, self.cur_word.token)
self._Next()
self._Peek()
if self.c_id in END_LIST:
done = True
elif self.c_id in END_LIST:
done = True
else:
# e.g. echo a(b)
p_die('Unexpected word while parsing command line',
word=self.cur_word)
children.append(child)
# Simplify the AST.
if len(children) > 1:
return command.CommandList(children)
else:
return children[0]
def _ParseCommandTerm(self):
""""
command_term : and_or (trailer and_or)* ;
trailer : sync_op newline_ok
| NEWLINES;
sync_op : '&' | ';';
This is handled in imperative style, like _ParseCommandLine.
Called by _ParseCommandList for all blocks, and also for ParseCaseItem,
which is slightly different. (HOW? Is it the DSEMI?)
Returns:
syntax_asdl.command
"""
# Token types that will end the command term.
END_LIST = (self.eof_id, Id.Right_Subshell, Id.Lit_RBrace, Id.Op_DSemi)
# NOTE: This is similar to _ParseCommandLine.
#
# - Why aren't we doing END_LIST in _ParseCommandLine?
# - Because you will never be inside $() at the top level.
# - We also know it will end in a newline. It can't end in "fi"!
# - example: if true; then { echo hi; } fi
children = []
done = False
while not done:
self._Peek()
# Most keywords are valid "first words". But do/done/then do not BEGIN
# commands, so they are not valid.
if self.c_id in NOT_FIRST_WORDS:
break
child = self.ParseAndOr()
assert child is not None
self._Peek()
if self.c_id == Id.Op_Newline:
self._Next()
self._Peek()
if self.c_id in END_LIST:
done = True
elif self.c_id in (Id.Op_Semi, Id.Op_Amp):
child = command.Sentence(child, self.cur_word.token)
self._Next()
self._Peek()
if self.c_id == Id.Op_Newline:
self._Next() # skip over newline
# Test if we should keep going. There might be another command after
# the semi and newline.
self._Peek()
if self.c_id in END_LIST: # \n EOF
done = True
elif self.c_id in END_LIST: # ; EOF
done = True
elif self.c_id in END_LIST: # EOF
done = True
else:
pass # e.g. "} done", "fi fi", ") fi", etc. is OK
children.append(child)
self._Peek()
return command.CommandList(children)
# TODO: Make this private.
def _ParseCommandList(self):
"""
command_list : newline_ok command_term trailer? ;
This one is called by all the compound commands. It's basically a command
block.
NOTE: Rather than translating the CFG directly, the code follows a style
more like this: more like this: (and_or trailer)+. It makes capture
easier.
"""
self._NewlineOk()
node = self._ParseCommandTerm()
assert node is not None
return node
def ParseLogicalLine(self):
"""Parse a single line for main_loop.
A wrapper around _ParseCommandLine(). Similar but not identical to
_ParseCommandList() and ParseCommandSub().
Raises:
ParseError
We want to be able catch ParseError all in one place.
"""
self._NewlineOk()
self._Peek()
if self.c_id == Id.Eof_Real:
return None
node = self._ParseCommandLine()
assert node is not None
return node
def ParseCommandSub(self):
"""Parse $(echo hi) and `echo hi` for word_parse.py.
They can have multiple lines, like this:
echo $(
echo one
echo two
)
"""
self._NewlineOk()
if self.c_kind == Kind.Eof: # e.g. $()
return command.NoOp()
# This calls ParseAndOr(), but I think it should be a loop that calls
# _ParseCommandLine(), like oil.InteractiveLoop.
node = self._ParseCommandTerm()
assert node is not None
return node
|
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] | 2.404145 | 19,300 |
from abc import abstractmethod
from typing import Union
import numpy as np
class GLIDEError(Exception):
"""Raised when an error related to the ASF classes is encountered.
"""
class GLIDEBase:
"""
Implements the non-differentiable variant of GLIDE-II as proposed in
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Note:
Additional contraints produced by the GLIDE-II formulation are implemented
such that if the returned values are negative, the corresponding constraint is
violated. The returned value may be positive. In such cases, the returned value
is a measure of how close or far the corresponding feasible solution is from
violating the constraint.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
def __call__(self, objective_vector: np.ndarray, preference: dict) -> np.ndarray:
"""Evaluate the scalarization function value based on objective vectors and
DM preference.
Args:
objective_vector (np.ndarray): 2-dimensional array of objective values of solutions.
preference (dict): The preference given by the decision maker. The required
dictionary keys and their meanings can be found in self.required_keys variable.
Returns:
np.ndarray: The scalarized value obtained by using GLIDE-II over
objective_vector.
"""
self.preference = preference
self.objective_vector = objective_vector
f_minus_q = np.atleast_2d(objective_vector - self.q)
mu = np.atleast_2d(self.mu)
I_alpha = self.I_alpha
max_term = np.max(mu[:, I_alpha] * f_minus_q[:, I_alpha], axis=1)
sum_term = self.rho * np.sum(self.w * f_minus_q, axis=1)
return max_term + sum_term
def evaluate_constraints(
self, objective_vector: np.ndarray, preference: dict
) -> Union[None, np.ndarray]:
"""Evaluate the additional contraints generated by the GLIDE-II formulation.
Note:
Additional contraints produced by the GLIDE-II formulation are implemented
such that if the returned values are negative, the corresponding constraint is
violated. The returned value may be positive. In such cases, the returned value
is a measure of how close or far the corresponding feasible solution is from
violating the constraint.
Args:
objective_vector (np.ndarray): [description]
preference (dict): [description]
Returns:
Union[None, np.ndarray]: [description]
"""
if not self.has_additional_constraints:
return None
self.preference = preference
self.objective_vector = objective_vector
constraints = (
self.epsilon[self.I_epsilon]
+ self.s_epsilon * self.delta_epsilon[self.I_epsilon]
- objective_vector[:, self.I_epsilon]
)
return constraints
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
@property
@abstractmethod
class reference_point_method_GLIDE(GLIDEBase):
"""
Implements the reference point method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
class GUESS_GLIDE(GLIDEBase):
"""
Implements the GUESS method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
class AUG_GUESS_GLIDE(GUESS_GLIDE):
"""
Implements the Augmented GUESS method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
class NIMBUS_GLIDE(GLIDEBase):
"""
Implements the NIMBUS method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
@property
@property
@property
@property
@property
class STEP_GLIDE(GLIDEBase):
"""
Implements the STEP method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
@property
@property
class STOM_GLIDE(GLIDEBase):
"""
Implements the STOM method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Has no effect on STOM calculation. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
class AUG_STOM_GLIDE(STOM_GLIDE):
"""
Implements the Augmented STOM method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Has no effect on STOM calculation. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
class Tchebycheff_GLIDE(GLIDEBase):
"""
Implements the Tchebycheff method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
class PROJECT_GLIDE(GLIDEBase):
"""
Implements the PROJECT method of preference elicitation and scalarization
using the non-differentiable variant of GLIDE-II as proposed in:
Ruiz, Francisco, Mariano Luque, and Kaisa Miettinen.
"Improving the computational efficiency in a global formulation (GLIDE)
for interactive multiobjective optimization."
Annals of Operations Research 197.1 (2012): 47-70.
Args:
utopian (np.ndarray, optional): The utopian point. Defaults to None.
nadir (np.ndarray, optional): The nadir point. Defaults to None.
rho (float, optional): The augmentation term for the scalarization function.
Defaults to 1e-6.
"""
@property
@property
@property
@property
@property
@property
@property
@property
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] | 2.794184 | 3,989 |
import numpy as np
from statespace_model import solver
from scipy.spatial.distance import cdist
from pyomac.misc import mac_value, err_rel
|
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] | 3.227273 | 44 |
# encoding: utf-8
from __future__ import print_function
from pybooru import Danbooru
from pybooru import Moebooru
konachan = Moebooru("konachan")
kona_tags = konachan.tag_list(order='date')
print(konachan.last_call)
kona_post = konachan.post_list()
print(konachan.last_call)
lolibooru = Moebooru("lolibooru")
kona_tags = lolibooru.tag_list(order='date')
print(lolibooru.last_call)
kona_post = lolibooru.post_list()
print(lolibooru.last_call)
danbooru = Danbooru('danbooru')
dan_tags = danbooru.tag_list(order='name')
print(danbooru.last_call)
dan_post = danbooru.post_list(tags="computer")
print(danbooru.last_call)
|
[
2,
21004,
25,
3384,
69,
12,
23,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
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198,
6738,
12972,
2127,
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74,
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571,
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62,
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3419,
198,
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7,
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13,
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62,
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8,
198,
198,
25604,
2127,
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796,
6035,
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10786,
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11537,
198,
198,
25604,
62,
31499,
796,
46078,
2127,
27786,
13,
12985,
62,
4868,
7,
2875,
11639,
3672,
11537,
198,
4798,
7,
25604,
2127,
27786,
13,
12957,
62,
13345,
8,
198,
25604,
62,
7353,
796,
46078,
2127,
27786,
13,
7353,
62,
4868,
7,
31499,
2625,
33215,
4943,
198,
4798,
7,
25604,
2127,
27786,
13,
12957,
62,
13345,
8,
198
] | 2.401544 | 259 |
str_year = input("what is your birth year:")
year = int(str_year)
age = 2020-year-1
print(f"hello, your age is {age}")
|
[
2536,
62,
1941,
796,
5128,
7203,
10919,
318,
534,
4082,
614,
25,
4943,
198,
198,
1941,
796,
493,
7,
2536,
62,
1941,
8,
198,
198,
496,
796,
12131,
12,
1941,
12,
16,
628,
198,
4798,
7,
69,
1,
31373,
11,
534,
2479,
318,
1391,
496,
92,
4943,
628
] | 2.583333 | 48 |
import threading
import base64
import hashlib
import webbrowser
import secrets
from time import sleep
from werkzeug.serving import make_server
from flask import Flask, request
global_dict = {
'received_callback': False,
'received_state': None,
'authorization_code': None,
'error_message': None
}
app = Flask(__name__)
@app.route("/callback")
def callback():
"""
The callback is invoked after a completed login attempt (succesful or otherwise).
It sets global variables with the auth code or error messages, then sets the
polling flag received_callback.
:return:
"""
if 'error' in request.args:
global_dict['error_message'] = request.args['error'] + ': ' + request.args['error_description']
else:
global_dict['authorization_code'] = request.args['code']
global_dict['received_state'] = request.args['state']
global_dict['received_callback'] = True
return "Please close this window and return to python-neurostore."
class ServerThread(threading.Thread):
"""
The Flask server is done this way to allow shutting down after a single request has been received.
"""
def auth0_url_encode(byte_data):
"""
Safe encoding handles + and /, and also replace = with nothing
:param byte_data:
:return:
"""
return base64.urlsafe_b64encode(byte_data).decode('utf-8').replace('=', '')
|
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11748,
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62,
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25,
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220,
220,
220,
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7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
2779,
2414,
13,
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62,
65,
2414,
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7,
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62,
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12501,
1098,
10786,
40477,
12,
23,
27691,
33491,
10786,
28,
3256,
10148,
8
] | 3.04386 | 456 |
# -*- coding: utf-8 -*-
from pas.plugins.ldap.plugin import LDAPPlugin
from zope.component.hooks import getSite
TITLE = "LDAP plugin (pas.plugins.ldap)"
def remove_persistent_import_step(context):
"""Remove broken persistent import step.
profile/import_steps.xml defined an import step with id
"pas.plugins.ldap.setup" which pointed to
pas.plugins.ldap.setuphandlers.setupPlugin.
This function no longer exists, and the import step is not needed,
because a post_install handler is now used for this.
But you get an error in the log whenever you import a profile:
GenericSetup Step pas.plugins.ldap.setup has an invalid import handler
So we remove the step.
"""
registry = context.getImportStepRegistry()
import_step = "pas.plugins.ldap.setup"
if import_step in registry._registered:
registry.unregisterStep(import_step)
|
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2,
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9,
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25,
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13,
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13,
335,
499,
13,
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13,
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628,
220,
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262,
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13,
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220,
220,
220,
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198,
220,
220,
220,
20478,
796,
4732,
13,
1136,
20939,
8600,
8081,
4592,
3419,
198,
220,
220,
220,
1330,
62,
9662,
796,
366,
44429,
13,
37390,
13,
335,
499,
13,
40406,
1,
198,
220,
220,
220,
611,
1330,
62,
9662,
287,
20478,
13557,
33736,
25,
198,
220,
220,
220,
220,
220,
220,
220,
20478,
13,
403,
30238,
8600,
7,
11748,
62,
9662,
8,
628,
198
] | 3.09375 | 288 |
# Copyright 2016 ZTE Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import sys
import traceback
import threading
from lcm.pub.nfvi.vim.api.openstack import glancebase
from lcm.pub.nfvi.vim.lib.syscomm import fun_name
from lcm.pub.nfvi.vim import const
logger = logging.getLogger(__name__)
|
[
2,
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1584,
1168,
9328,
10501,
13,
198,
2,
198,
2,
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262,
24843,
13789,
11,
10628,
362,
13,
15,
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3672,
198,
6738,
300,
11215,
13,
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13,
77,
69,
8903,
13,
31124,
1330,
1500,
198,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
628,
628,
628,
198
] | 3.411523 | 243 |
"""This script is responsible for building the API reference. The API reference is located in
docs/api. The script scans through all the modules, classes, and functions. It processes
the __doc__ of each object and formats it so that MkDocs can process it in turn.
"""
import argparse
import functools
import importlib
import inspect
import os
import pathlib
import re
import shutil
from numpydoc.docscrape import ClassDoc, FunctionDoc
from yamp import md
from yamp import utils
def print_docstring(obj, file, depth, linkifier):
"""Prints a classes's docstring to a file."""
doc = ClassDoc(obj) if inspect.isclass(obj) else FunctionDoc(obj)
printf = functools.partial(print, file=file)
printf(md.h1(obj.__name__))
printf(linkifier.linkify_fences(md.line(concat_lines(doc["Summary"])), depth))
printf(
linkifier.linkify_fences(md.line(concat_lines(doc["Extended Summary"])), depth)
)
# We infer the type annotations from the signatures, and therefore rely on the signature
# instead of the docstring for documenting parameters
try:
signature = inspect.signature(obj)
except ValueError:
signature = (
inspect.Signature()
) # TODO: this is necessary for Cython classes, but it's not correct
params_desc = {param.name: " ".join(param.desc) for param in doc["Parameters"]}
# Parameters
if signature.parameters:
printf(md.h2("Parameters"))
for param in signature.parameters.values():
# Name
printf(f"- **{param.name}**", end="")
# Type annotation
if param.annotation is not param.empty:
anno = inspect.formatannotation(param.annotation)
anno = linkifier.linkify_dotted(anno, depth)
printf(f" (*{anno}*)", end="")
# Default value
if param.default is not param.empty:
printf(f" – defaults to `{param.default}`", end="")
printf("\n", file=file)
# Description
desc = params_desc[param.name]
if desc:
printf(f" {desc}\n")
printf("")
# Attributes
if doc["Attributes"]:
printf(md.h2("Attributes"))
for attr in doc["Attributes"]:
# Name
printf(f"- **{attr.name}**", end="")
# Type annotation
if attr.type:
printf(f" (*{attr.type}*)", end="")
printf("\n", file=file)
# Description
desc = " ".join(attr.desc)
if desc:
printf(f" {desc}\n")
printf("")
# Examples
if doc["Examples"]:
printf(md.h2("Examples"))
in_code = False
after_space = False
for line in inspect.cleandoc("\n".join(doc["Examples"])).splitlines():
if (
in_code
and after_space
and line
and not line.startswith(">>>")
and not line.startswith("...")
):
printf("```\n")
in_code = False
after_space = False
if not in_code and line.startswith(">>>"):
printf("```python")
in_code = True
after_space = False
if not line:
after_space = True
printf(line)
if in_code:
printf("```")
printf("")
# Methods
if inspect.isclass(obj) and doc["Methods"]:
printf(md.h2("Methods"))
printf_indent = lambda x, **kwargs: printf(f" {x}", **kwargs)
for meth in doc["Methods"]:
printf(md.line(f'???- note "{meth.name}"'))
# Parse method docstring
docstring = utils.find_method_docstring(klass=obj, method=meth.name)
if not docstring:
continue
meth_doc = FunctionDoc(func=None, doc=docstring)
printf_indent(md.line(" ".join(meth_doc["Summary"])))
if meth_doc["Extended Summary"]:
printf_indent(md.line(" ".join(meth_doc["Extended Summary"])))
# We infer the type annotations from the signatures, and therefore rely on the signature
# instead of the docstring for documenting parameters
signature = utils.find_method_signature(obj, meth.name)
params_desc = {
param.name: " ".join(param.desc) for param in doc["Parameters"]
}
# Parameters
if (
len(signature.parameters) > 1
): # signature is never empty, but self doesn't count
printf_indent("**Parameters**\n")
for param in signature.parameters.values():
if param.name == "self":
continue
# Name
printf_indent(f"- **{param.name}**", end="")
# Type annotation
if param.annotation is not param.empty:
printf_indent(
f" (*{inspect.formatannotation(param.annotation)}*)", end=""
)
# Default value
if param.default is not param.empty:
printf_indent(f" – defaults to `{param.default}`", end="")
printf_indent("", file=file)
# Description
desc = params_desc.get(param.name)
if desc:
printf_indent(f" {desc}")
printf_indent("")
# Returns
if meth_doc["Returns"]:
printf_indent("**Returns**\n")
return_val = meth_doc["Returns"][0]
if signature.return_annotation is not inspect._empty:
if inspect.isclass(signature.return_annotation):
printf_indent(
f"*{signature.return_annotation.__name__}*: ", end=""
)
else:
printf_indent(f"*{signature.return_annotation}*: ", end="")
printf_indent(return_val.type)
printf_indent("")
# Notes
if doc["Notes"]:
printf(md.h2("Notes"))
printf(md.line("\n".join(doc["Notes"])))
# References
if doc["References"]:
printf(md.h2("References"))
printf(md.line("\n".join(doc["References"])))
def cli_hook():
"""Command-line interface."""
parser = argparse.ArgumentParser()
parser.add_argument(
"library",
nargs="?",
help="the library to document",
)
parser.add_argument("--out", default="docs/api", help="where to dump the docs")
parser.add_argument("--verbose", dest="verbose", action="store_true")
parser.set_defaults(verbose=False)
args = parser.parse_args()
print_library(
library=args.library, output_dir=pathlib.Path(args.out), verbose=args.verbose
)
|
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] | 2.121015 | 3,231 |
# Script to run several runs after each other. The runs are specified by the run-configurations
# located in the folder runs/several_runs/
import sys
import os
sys.path.append('..')
import run_script
run_files = os.listdir("runs/several_runs/")
run_files.sort()
for run_file_name in run_files:
try:
run_script.main(["run_several.py", run_file_name], "runs/several_runs/")
except Exception as e:
print((str(type(e)) + ": " + str(e)).replace('\n', ' '))
#os.system("shutdown now -h")
|
[
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198,
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2902,
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] | 2.65625 | 192 |
from django.db import models
from Client.models import Student, Parent, Teacher, Subject, Course
from django.contrib.auth.models import User
|
[
6738,
42625,
14208,
13,
9945,
1330,
4981,
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13,
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11,
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13,
18439,
13,
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1330,
11787,
628,
198
] | 3.864865 | 37 |
# stdlib
from typing import List
from typing import Optional
# syft relative
from .serde.serializable import Serializable
from .uid import UID
|
[
2,
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8019,
198,
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1330,
7343,
198,
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2,
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13821,
1330,
23283,
13821,
198,
6738,
764,
27112,
1330,
25105,
628
] | 3.918919 | 37 |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Dict, List, Mapping, Optional, Tuple, Union
from .. import _utilities, _tables
from . import outputs
from ._inputs import *
__all__ = ['DataTransferConfig']
|
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198,
834,
439,
834,
796,
37250,
6601,
43260,
16934,
20520,
628,
198
] | 3.537815 | 119 |
# -*- coding: utf-8 -*-
"""Tags for dependency injection."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from django import template
from ralph.util.di import get_extra_data
register = template.Library()
@register.simple_tag
|
[
2,
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3419,
628,
198,
31,
30238,
13,
36439,
62,
12985,
198
] | 3.463918 | 97 |
import sys
import os.path
from urlparse import urljoin
import time
import urllib2
from bs4 import BeautifulSoup
|
[
11748,
25064,
198,
11748,
28686,
13,
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220,
220,
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220,
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] | 2.904762 | 42 |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
__all__ = [
'ListRemoteRenderingAccountKeysResult',
'AwaitableListRemoteRenderingAccountKeysResult',
'list_remote_rendering_account_keys',
]
@pulumi.output_type
class ListRemoteRenderingAccountKeysResult:
"""
Developer Keys of account
"""
@property
@pulumi.getter(name="primaryKey")
def primary_key(self) -> str:
"""
value of primary key.
"""
return pulumi.get(self, "primary_key")
@property
@pulumi.getter(name="secondaryKey")
def secondary_key(self) -> str:
"""
value of secondary key.
"""
return pulumi.get(self, "secondary_key")
# pylint: disable=using-constant-test
def list_remote_rendering_account_keys(account_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableListRemoteRenderingAccountKeysResult:
"""
Developer Keys of account
:param str account_name: Name of an Mixed Reality Account.
:param str resource_group_name: Name of an Azure resource group.
"""
__args__ = dict()
__args__['accountName'] = account_name
__args__['resourceGroupName'] = resource_group_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-native:mixedreality/v20210301preview:listRemoteRenderingAccountKeys', __args__, opts=opts, typ=ListRemoteRenderingAccountKeysResult).value
return AwaitableListRemoteRenderingAccountKeysResult(
primary_key=__ret__.primary_key,
secondary_key=__ret__.secondary_key)
|
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9233,
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28,
834,
1186,
834,
13,
38238,
62,
2539,
8,
198
] | 2.598742 | 795 |
# Generated by Django 3.1.5 on 2021-03-24 21:08
from django.db import migrations, models
import django.db.models.deletion
|
[
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
20,
319,
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12,
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42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
628
] | 2.818182 | 44 |
from core import models
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
"""Need to import the default Django user admin, need to change some
of the class variables to support our custom user admin using email
instead of username"""
from django.utils.translation import gettext as _
"""Import gettext function to convert strings in python to human
readable text, in this context, the strings get passed through the
transalation engine so we're not doing anything with translation.
If you want to extend the code to support multiple languages then this
would make easier for you to do that bcoz you just set up the transalation
files and then it'll convert the text appropriately"""
class UserAdmin(BaseUserAdmin):
""""Create our custom user admin by extending the BaseUserAdmin"""
ordering = ['id']
list_display = ['email', 'name']
"""Define the field set for test 2, each bracket is a section,
1st section: no title, contains 2 fields email, pw
2nd section: title: personal info, contains 1 field, needs to
add a comma after the only field otherwise it'll be recognised as
a string and won't work
3rd section: permission, contains 3 fields
4th section: Important dates, contains 1 field"""
fieldsets = (
(None, {'fields': ('email', 'password')}),
(_('Personal Info'), {'fields': ('name',)}),
(
_('Permissions'),
{'fields': ('is_active', 'is_staff', 'is_superuser')}
),
(_('Important dates'), {'fields': ('last_login',)}),
)
"""Define the additional field set for test 3 to include email,
password, password 2 to create a new user. The user admin by
default takes an add field sets which defines the fields that you
include on the add page which is the same as the create user page,
remember to add the comma at the end of the first item as it's the
only item, w/o the comma, python will be confused it as a string.
Classes assigned to the form: default option"""
add_fieldsets = (
(None, {
'classes': ('wide',),
'fields': ('email', 'password1', 'password2')
}),
)
admin.site.register(models.User, UserAdmin)
"""Register the site in the Django admin"""
|
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] | 3.20306 | 719 |
import numpy as np
import math
from compas.datastructures import Mesh
import compas_slicer.utilities as utils
import logging
import networkx as nx
from compas_slicer.slicers.slice_utilities import create_graph_from_mesh_vkeys
from compas_slicer.pre_processing.preprocessing_utils.geodesics import get_igl_EXACT_geodesic_distances, \
get_custom_HEAT_geodesic_distances
import statistics
logger = logging.getLogger('logger')
__all__ = ['CompoundTarget',
'blend_union_list',
'stairs_union_list',
'chamfer_union_list']
class CompoundTarget:
"""
Represents a desired user-provided target. It acts as a key-frame that controls the print paths
orientations. After the curved slicing , the print paths will be aligned to the compound target close to
its area. The vertices that belong to the target are marked with their vertex attributes; they have
data['v_attr'] = value.
Attributes
----------
mesh: :class:`compas.datastructures.Mesh`
v_attr : str
The key of the attribute dict to be checked.
value: int
The value of the attribute dict with key=v_attr. If in a vertex data[v_attr]==value then the vertex is part of
this target.
DATA_PATH: str
has_blend_union: bool
blend_radius : float
geodesics_method: str
'exact_igl' exact igl geodesic distances
'heat' custom heat geodesic distances
anisotropic_scaling: bool
This is not yet implemented
"""
# --- Neighborhoods clustering
def find_targets_connected_components(self):
"""
Clusters all the vertices that belong to the target into neighborhoods using a graph.
Each target can have an arbitrary number of neighborhoods/clusters.
Fills in the attributes: self.all_target_vkeys, self.clustered_vkeys, self.number_of_boundaries
"""
self.all_target_vkeys = [vkey for vkey, data in self.mesh.vertices(data=True) if
data[self.v_attr] == self.value]
assert len(self.all_target_vkeys) > 0, "There are no vertices in the mesh with the attribute : " \
+ self.v_attr + ", value : %d" % self.value + " .Probably you made a " \
"mistake while creating the targets. "
G = create_graph_from_mesh_vkeys(self.mesh, self.all_target_vkeys)
assert len(list(G.nodes())) == len(self.all_target_vkeys)
self.number_of_boundaries = len(list(nx.connected_components(G)))
for i, cp in enumerate(nx.connected_components(G)):
self.clustered_vkeys.append(list(cp))
logger.info("Compound target with 'boundary'=%d. Number of connected_components : %d" % (
self.value, len(list(nx.connected_components(G)))))
# --- Geodesic distances
def compute_geodesic_distances(self):
"""
Computes the geodesic distances from each of the target's neighborhoods to all the mesh vertices.
Fills in the distances attributes.
"""
if self.geodesics_method == 'exact_igl':
distances_lists = [get_igl_EXACT_geodesic_distances(self.mesh, vstarts) for vstarts in
self.clustered_vkeys]
elif self.geodesics_method == 'heat':
distances_lists = [get_custom_HEAT_geodesic_distances(self.mesh, vstarts, self.OUTPUT_PATH) for vstarts in
self.clustered_vkeys]
else:
raise ValueError('Unknown geodesics method : ' + self.geodesics_method)
distances_lists = [list(dl) for dl in distances_lists] # number_of_boundaries x #V
self.update_distances_lists(distances_lists)
def update_distances_lists(self, distances_lists):
"""
Fills in the distances attributes.
"""
self._distances_lists = distances_lists
self._distances_lists_flipped = [] # empty
for i in range(self.VN):
current_values = [self._distances_lists[list_index][i] for list_index in range(self.number_of_boundaries)]
self._distances_lists_flipped.append(current_values)
self._np_distances_lists_flipped = np.array(self._distances_lists_flipped)
self._max_dist = np.max(self._np_distances_lists_flipped)
# --- Uneven weights
@property
def has_uneven_weights(self):
""" Returns True if the target has uneven_weights calculated, False otherwise. """
return len(self.weight_max_per_cluster) > 0
def compute_uneven_boundaries_weight_max(self, other_target):
"""
If the target has multiple neighborhoods/clusters of vertices, then it computes their maximum distance from
the other_target. Based on that it calculates their weight_max for the interpolation process
"""
if self.number_of_boundaries > 1:
ds_avg_HIGH = self.get_boundaries_rel_dist_from_other_target(other_target)
max_param = max(ds_avg_HIGH)
for i, d in enumerate(ds_avg_HIGH): # offset all distances except the maximum one
if abs(d - max_param) > 0.01: # if it isn't the max value
ds_avg_HIGH[i] = d + self.offset
self.weight_max_per_cluster = [d / max_param for d in ds_avg_HIGH]
logger.info('weight_max_per_cluster : ' + str(self.weight_max_per_cluster))
else:
logger.info("Did not compute_norm_of_gradient uneven boundaries, target consists of single component")
# --- Relation to other target
def get_boundaries_rel_dist_from_other_target(self, other_target, avg_type='median'):
"""
Returns a list, one relative distance value per connected boundary neighborhood.
That is the average of the distances of the vertices of that boundary neighborhood from the other_target.
"""
distances = []
for vi_starts in self.clustered_vkeys:
ds = [other_target.get_distance(vi) for vi in vi_starts]
if avg_type == 'mean':
distances.append(statistics.mean(ds))
else: # 'median'
distances.append(statistics.median(ds))
return distances
def get_avg_distances_from_other_target(self, other_target):
"""
Returns the minimum and maximum distance of the vertices of this target from the other_target
"""
extreme_distances = []
for v_index in other_target.all_target_vkeys:
extreme_distances.append(self.get_all_distances()[v_index])
return np.average(np.array(extreme_distances))
#############################
# --- get all distances
# All distances
def get_all_distances(self):
""" Returns the resulting distances per every vertex. """
return [self.get_distance(i) for i in range(self.VN)]
def get_all_clusters_distances_dict(self):
""" Returns dict. keys: index of connected target neighborhood, value: list, distances (one per vertex). """
return {i: self._distances_lists[i] for i in range(self.number_of_boundaries)}
def get_max_dist(self):
""" Returns the maximum distance that the target has on a mesh vertex. """
return self._max_dist
#############################
# --- per vkey distances
def get_all_distances_for_vkey(self, i):
""" Returns distances from each cluster separately for vertex i. Smooth union doesn't play here any role. """
return [self._distances_lists[list_index][i] for list_index in range(self.number_of_boundaries)]
def get_distance(self, i):
""" Return get_distance for vertex with vkey i. """
if self.union_method == 'min':
# --- simple union
return np.min(self._np_distances_lists_flipped[i])
elif self.union_method == 'smooth':
# --- blend (smooth) union
return blend_union_list(values=self._np_distances_lists_flipped[i], r=self.union_params[0])
elif self.union_method == 'chamfer':
# --- blend (smooth) union
return chamfer_union_list(values=self._np_distances_lists_flipped[i], r=self.union_params[0])
elif self.union_method == 'stairs':
# --- stairs union
return stairs_union_list(values=self._np_distances_lists_flipped[i], r=self.union_params[0],
n=self.union_params[1])
else:
raise ValueError("Unknown Union method : ", self.union_method)
#############################
# --- scalar field smoothing
def laplacian_smoothing(self, iterations, strength):
""" Smooth the distances on the mesh, using iterative laplacian smoothing. """
L = utils.get_mesh_cotmatrix_igl(self.mesh, fix_boundaries=True)
new_distances_lists = []
logger.info('Laplacian smoothing of all distances')
for i, a in enumerate(self._distances_lists):
a = np.array(a) # a: numpy array containing the attribute to be smoothed
for _ in range(iterations): # iterative smoothing
a_prime = a + strength * L * a
a = a_prime
new_distances_lists.append(list(a))
self.update_distances_lists(new_distances_lists)
#############################
# ------ output
def save_distances(self, name):
"""
Save distances to json.
Saves one list with distance values (one per vertex).
Parameters
----------
name: str, name of json to be saved
"""
utils.save_to_json(self.get_all_distances(), self.OUTPUT_PATH, name)
# ------ assign new Mesh
def assign_new_mesh(self, mesh):
""" When the base mesh changes, a new mesh needs to be assigned. """
mesh.to_json(self.OUTPUT_PATH + "/temp.obj")
mesh = Mesh.from_json(self.OUTPUT_PATH + "/temp.obj")
self.mesh = mesh
self.VN = len(list(self.mesh.vertices()))
####################
# unions on lists
def blend_union_list(values, r):
""" Returns a smooth union of all the elements in the list, with blend radius blend_radius. """
d_result = 9999999 # very big number
for d in values:
d_result = blend_union(d_result, d, r)
return d_result
def stairs_union_list(values, r, n):
""" Returns a stairs union of all the elements in the list, with blend radius r and number of peaks n-1."""
d_result = 9999999 # very big number
for i, d in enumerate(values):
d_result = stairs_union(d_result, d, r, n)
return d_result
####################
# unions on pairs
def blend_union(da, db, r):
""" Returns a smooth union of the two elements da, db with blend radius blend_radius. """
e = max(r - abs(da - db), 0)
return min(da, db) - e * e * 0.25 / r
def chamfer_union(a, b, r):
""" Returns a chamfer union of the two elements da, db with radius r. """
return min(min(a, b), (a - r + b) * math.sqrt(0.5))
def stairs_union(a, b, r, n):
""" Returns a stairs union of the two elements da, db with radius r. """
s = r / n
u = b - r
return min(min(a, b), 0.5 * (u + a + abs((u - a + s) % (2 * s) - s)))
if __name__ == "__main__":
pass
|
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] | 2.43133 | 4,660 |
#----------------------------------
# Models / new_app
#----------------------------------
from django.db import models
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
|
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] | 8.380952 | 42 |
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import List, Type
from ....core import OperandType, ChunkGraph
from ..core import Optimizer, OptimizationRule, OptimizationRecords
class ChunkOptimizer(Optimizer):
"""
Tileable Optimizer
"""
|
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import logging
import platform
from pathlib import Path
logger = Log("caterpillar_log")
|
[
11748,
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#!/usr/bin/env python3
us_invasion = [{'ip':'10.10.1.2', 'un':'john', 'pw':'allstar'}, {'ip':'10.10.1.3', 'un':'paul', 'pw':'iils20s3'}, {'ip':'10.10.1.4', 'un':'george', 'pw':'hunkydoryzory'}, {'ip':'10.10.1.5', 'un':'stuart', 'pw':'alta3'}, {'ip':'10.10.1.6', 'un':'pete', 'pw':'a8dd827z3'}]
listbyusername = sorted(us_invasion, key=byUserName)
print('\nThe list us_invasion looks like: ', us_invasion)
print('\nResult of sorted(us_invasion, key=byUserName): ', listbyusername)
print('\nBut the value of the list us_invasion hasn\'t actually changed: ', us_invasion)
|
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] | 2.125926 | 270 |
from flask_wtf import FlaskForm
from wtforms import ValidationError
from wtforms.validators import Required, Email, EqualTo
from wtforms import StringField, PasswordField, SubmitField
from .models import User
|
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#
# @lc app=leetcode id=362 lang=python3
#
# [362] Design Hit Counter
#
import collections
# @lc code=start
# Your HitCounter object will be instantiated and called as such:
# obj = HitCounter()
# ls = [[1],[2],[3],[300],[301]]
# for param in ls:
# obj.hit(param[0])
# print(obj.q)
# # param_2 = obj.getHits(timestamp)
# @lc code=end
|
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# date: 2019.07.09
# https://stackoverflow.com/questions/56951383/tkinter-disable-buttons-while-thread-is-running/56953613#56953613
import tkinter as tk
from threading import Thread
import time
#-----------------------------------------------------
# counter displayed when thread is running
counter = 0
root = tk.Tk()
l = tk.Label(root)
l.pack()
b = tk.Button(root, text="Start", command=start_thread)
b.pack()
root.mainloop()
|
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from robot.api import logger
class MyLibrary:
"""マイライブラリ
| =タイトル= | =もう一つタイトル= |
| 1行1列目 | 1行2列目 |
| | 1列目が空白 |
| 2列目が空白 | |
= カスタムセクション =
ここがカスタムセクション
= 次のセクション =
`カスタムセクション` へのリンク
セクションへのリンク
- `introduction`
- `importing`
- `shortcuts`
- `keywords`
*太字です*
_イタリックです_
普通です
- リスト1
- リスト2
Googleへ https://google.co.jp
こちらも [https://google.co.jp|Googleへ]
`Hello World` へ
``インラインコードスタイル``
複数行の *bold\n
try* みる
"""
ROBOT_LIBRARY_SCOPE = 'TEST SUITE'
def hello_world(self, name='foo'):
"""ハローワールドを出力します"""
logger.console(f'hello, world {name} !')
|
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"""
Django settings for auswertung project.
For more information on this file, see
https://docs.djangoproject.com/en/1.7/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.7/ref/settings/
"""
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
import os
from django.contrib.messages import constants as messages
from django.utils.translation import ugettext_lazy as _
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.7/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'ys-#t((t5g8^p-@9sn3@artu2_5my==hvd&vgmc1ho_@$nu(gw'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = (
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'bootstrap3',
'widget_tweaks',
'common',
'athletes',
'clubs',
'utils',
'squads',
'streams',
'teams',
'tournaments',
'debug_toolbar',
)
MIDDLEWARE_CLASSES = (
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.locale.LocaleMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.auth.middleware.SessionAuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'debug_toolbar.middleware.DebugToolbarMiddleware',
)
ROOT_URLCONF = 'Turnauswertung.urls'
WSGI_APPLICATION = 'Turnauswertung.wsgi.application'
MEDIA_ROOT = 'static/'
# Database
# https://docs.djangoproject.com/en/1.7/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.mysql',
'NAME': 'TURNAUSWERTUNG',
'USER': 'root',
'PASSWORD': 'root',
},
'sqlite_fallback': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Internationalization
# https://docs.djangoproject.com/en/1.7/topics/i18n/
# Local time zone for this installation. Choices can be found here:
# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name
# although not all choices may be available on all operating systems.
# In a Windows environment this must be set to your system time zone.
TIME_ZONE = 'Europe/Berlin'
# Language code for this installation. All choices can be found here:
# http://www.i18nguy.com/unicode/language-identifiers.html
LANGUAGE_CODE = 'en-us'
# If you set this to False, Django will make some optimizations so as not
# to load the internationalization machinery.
USE_I18N = True
# If you set this to False, Django will not format dates, numbers and
# calendars according to the current locale.
USE_L10N = True
# USE_THOUSAND_SEPARATOR = True
# If you set this to False, Django will not use timezone-aware datetimes.
USE_TZ = False
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.7/howto/static-files/
STATIC_URL = '/static/'
# List of finder classes that know how to find static files in
# various locations.
STATICFILES_FINDERS = (
'django.contrib.staticfiles.finders.FileSystemFinder',
'django.contrib.staticfiles.finders.AppDirectoriesFinder',
'django.contrib.staticfiles.finders.DefaultStorageFinder',
)
MESSAGE_TAGS = {
messages.ERROR: 'danger'
}
# Multi-language support
LOCALE_PATHS = (
os.path.join(BASE_DIR, 'locale/'),
)
LANGUAGES = (
('en', _('English')),
('de', _('German')),
)
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.contrib.auth.context_processors.auth',
'django.template.context_processors.i18n',
],
'debug': DEBUG,
},
},
]
|
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] | 2.51261 | 1,705 |
"""Support for Telegram bot using polling."""
import logging
from telegram import Update
from telegram.error import NetworkError, RetryAfter, TelegramError, TimedOut
from telegram.ext import CallbackContext, TypeHandler, Updater
from homeassistant.const import EVENT_HOMEASSISTANT_START, EVENT_HOMEASSISTANT_STOP
from . import BaseTelegramBotEntity
_LOGGER = logging.getLogger(__name__)
async def async_setup_platform(hass, bot, config):
"""Set up the Telegram polling platform."""
pollbot = PollBot(hass, bot, config)
hass.bus.async_listen_once(EVENT_HOMEASSISTANT_START, pollbot.start_polling)
hass.bus.async_listen_once(EVENT_HOMEASSISTANT_STOP, pollbot.stop_polling)
return True
def process_error(update: Update, context: CallbackContext):
"""Telegram bot error handler."""
try:
raise context.error
except (TimedOut, NetworkError, RetryAfter):
# Long polling timeout or connection problem. Nothing serious.
pass
except TelegramError:
_LOGGER.error('Update "%s" caused error: "%s"', update, context.error)
class PollBot(BaseTelegramBotEntity):
"""
Controls the Updater object that holds the bot and a dispatcher.
The dispatcher is set up by the super class to pass telegram updates to `self.handle_update`
"""
def __init__(self, hass, bot, config):
"""Create Updater and Dispatcher before calling super()."""
self.bot = bot
self.updater = Updater(bot=bot, workers=4)
self.dispatcher = self.updater.dispatcher
self.dispatcher.add_handler(TypeHandler(Update, self.handle_update))
self.dispatcher.add_error_handler(process_error)
super().__init__(hass, config)
def start_polling(self, event=None):
"""Start the polling task."""
_LOGGER.debug("Starting polling")
self.updater.start_polling()
def stop_polling(self, event=None):
"""Stop the polling task."""
_LOGGER.debug("Stopping polling")
self.updater.stop()
|
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] | 2.734143 | 741 |
'''
Problem: Xenny and Partially Sorted Strings
Accept number of testcases as t
for each test case:
Given 3 integers N, K, M for each test case. Do the following steps-
Accept all N number of strings and store them in a list
sort the list by only considering first m charcaters in every element of list
output the Kth element from the above sorted list
'''
#Accept the first integer which denotes the number of testcases
#For accepting input as int use int() function while accepting the input()
#The accepted input is stored in variable t
t=int(input())
#Now iterating through every testcase i.e for each testcase
#As we neednot store the number of that iteration we can use '_' here
for _ in range(t):
#Accept 3 integers N,K,M respectively
#input() function accepts the input
#split function is used to convert the accepted input in to a list based on delimiters like space or empty
#int function is used to convert the accepted input to Integers
#map function maps or applies the int function to the each and every element of list and assigns to n,k,m variables
n,k,m=map(int,input().split())
#Declaring an empty list to store 'n' strings
l=[]
#As n denotes the number of strings ,we use a for loop to accept input 'n' times
for _ in range(n):
#In each iteration an input is accepted using input() and then converted to string
#We use append method of list to store the accepted string for future computation
l.append(str(input()))
#Hence by end of 'n' interations we will have a list containing of 'n' string which need to be sorted
#The sorting need to be done based on only first m charcaters of each string in the list
#List has inbuilt sort method to sort elements in a list
#Sort method has 2 paramenters
#reverse: It accepts a boolean value(true/false) i.e to sort in descending or acending order
#key: On what basis/condition/criteria we need to sort the list(like sort based on lengths etc)
#Incase of sorting on criteria of lengths we use len function i.e key=len will be assigned
#This will make the list sorted based on length of strings
#We can use lambda which is an anonmyous function
#Hence in order to sort based on first 'm' charcaters of each element we assign as follows
#key=lambda x:x[0:m]
#Here x[0:m]------>returns first m charcater of an element
#key condition is applied to each and every element of the list
#So as all the first m charcaters are identified sorting is done based on them
#sort function is an inplace function which means that it sorts and places the sorted order in the same list, here it is 'l'
l.sort(key=lambda x:x[0:m])
#As we need kth string ,for suppose we want 2nd string will be at index '1' i.e (2-1)
#Therefore similarly if we want kth string then we need to access (k-1) index
print(l[k-1])
|
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357,
17,
12,
16,
8,
198,
220,
220,
220,
1303,
26583,
12470,
611,
356,
765,
479,
400,
4731,
788,
356,
761,
284,
1895,
357,
74,
12,
16,
8,
6376,
198,
220,
220,
220,
3601,
7,
75,
58,
74,
12,
16,
12962,
198
] | 3.212973 | 925 |
from store.api.handlers.base import BaseView
from http import HTTPStatus
from typing import Generator
from datetime import datetime
from aiohttp.web_response import Response
from aiohttp.web_exceptions import HTTPNotFound
from aiohttp_apispec import docs, request_schema, response_schema
from sqlalchemy import and_, or_
from store.api.schema import OrdersAssignPostRequestSchema, OrdersAssignPostResponseSchema
from store.db.schema import orders_table, couriers_table, orders_delivery_hours_table, delivery_hours_table, \
working_hours_table, couriers_working_hours_table
from ..query import AVAILABLE_ORDERS_QUERY
from ...domain import CouriersOrdersResolver, CourierConfigurator
|
[
6738,
3650,
13,
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13,
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62,
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62,
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62,
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62,
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62,
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198,
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6738,
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8910,
35422,
364,
4965,
14375,
11,
34268,
16934,
333,
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628
] | 3.484848 | 198 |
from enum import Enum
from nest import Create, Connect
from the_second_level.src.tools.multimeter import add_multimeter
|
[
6738,
33829,
1330,
2039,
388,
198,
6738,
16343,
1330,
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11,
8113,
198,
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62,
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62,
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13,
10677,
13,
31391,
13,
16680,
16912,
1330,
751,
62,
16680,
16912,
628,
628
] | 3.727273 | 33 |
import pytest
from demisto_sdk.commands.common.constants import PACKS_DIR, PLAYBOOKS_DIR
from demisto_sdk.commands.common.content.errors import (ContentInitializeError,
ContentSerializeError)
from demisto_sdk.commands.common.content.objects.abstract_objects import \
YAMLObject
from demisto_sdk.commands.common.handlers import YAML_Handler
from demisto_sdk.commands.common.tools import src_root
TEST_DATA = src_root() / 'tests' / 'test_files'
TEST_CONTENT_REPO = TEST_DATA / 'content_slim'
TEST_VALID_YAML = TEST_CONTENT_REPO / PACKS_DIR / 'Sample01' / PLAYBOOKS_DIR / 'playbook-sample_new.yml'
TEST_NOT_VALID_YAML = TEST_DATA / 'malformed.yaml'
yaml = YAML_Handler(width=50000)
|
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] | 2.339623 | 318 |
#!/usr/bin/env python
#
# Copyright (c) 2016, SICS, Swedish ICT
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# 3. Neither the name of the Institute nor the names of its contributors
# may be used to endorse or promote products derived from this software
# without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE INSTITUTE AND CONTRIBUTORS ``AS IS'' AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE INSTITUTE OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
# OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
# HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
# SUCH DAMAGE.
#
# Author: Joakim Eriksson, [email protected]
#
#
import sys, binascii, argparse, re
parser = argparse.ArgumentParser(description='convert hex to binary - and add padding.')
parser.add_argument("-i", help="input file - stdin is default.")
parser.add_argument("-o", help="input file - stdout is default.")
parser.add_argument("-c", help="byte value for padding - 0xff is default.")
parser.add_argument("-p", help="number of pad bytes AFTER infile or with minus - the total size of the file to pad.")
parser.add_argument("-P", help="number of pad bytes BEFORE infile.")
parser.add_argument("-B", action="store_true", help="file is binary - no hex to bin conversion.")
parser.add_argument("-V", action="store_true", help="print version and exit.")
args = parser.parse_args()
if args.V:
print "Sparrow binfile tool - Version 1.0"
exit()
# setup the in and out files
infile = open(args.i, 'r') if args.i else sys.stdin
outfile = open(args.o, 'w') if args.o else sys.stdout
padc = chr(int(args.c if args.c else "0xff", 16))
pad_after = int(args.p if args.p else 0)
pad_before = int(args.P if args.P else 0)
data = infile.read()
if not args.B:
data = re.sub(r'(?m)^#.*\n?', '', data)
data = binascii.unhexlify(''.join(data.split()))
# pad at the end
if pad_after < 0:
data = data + padc * ((-pad_after) - len(data))
else:
data = data + padc * pad_after
# pad at start
data = padc * pad_before + data
# write the file
outfile.write(data)
|
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1635,
14808,
12,
15636,
62,
8499,
8,
532,
18896,
7,
7890,
4008,
198,
17772,
25,
198,
220,
220,
220,
1366,
796,
1366,
1343,
14841,
66,
1635,
14841,
62,
8499,
198,
198,
2,
14841,
379,
923,
198,
7890,
796,
14841,
66,
1635,
14841,
62,
19052,
1343,
1366,
198,
198,
2,
3551,
262,
2393,
198,
448,
7753,
13,
13564,
7,
7890,
8,
198
] | 3.108136 | 971 |
#!/usr/bin/env python2.6
#
# Copyright (C) 2011 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# Generates a table of prime numbers for use in BasicHashtable.cpp.
#
# Each prime is chosen such that it is a little more than twice as large as
# the previous prime in the table. This makes it easier to choose a new
# hashtable size when the underlying array is grown by as nominal factor
# of two each time.
#
print "static size_t PRIMES[] = {"
n = 5
max = 2**31 - 1
while n < max:
print " %d," % (n)
n = n * 2 + 1
while not is_odd_prime(n):
n += 2
print " 0,"
print "};"
|
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2,
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14629,
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17,
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2,
198,
198,
2,
198,
2,
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618,
262,
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7177,
318,
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416,
355,
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5766,
198,
2,
286,
734,
1123,
640,
13,
198,
2,
198,
198,
4798,
366,
12708,
2546,
62,
83,
4810,
3955,
1546,
21737,
796,
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198,
198,
77,
796,
642,
198,
9806,
796,
362,
1174,
3132,
532,
352,
198,
4514,
299,
1279,
3509,
25,
198,
220,
3601,
366,
220,
220,
220,
4064,
67,
553,
4064,
357,
77,
8,
198,
220,
299,
796,
299,
1635,
362,
1343,
352,
198,
220,
981,
407,
318,
62,
5088,
62,
35505,
7,
77,
2599,
198,
220,
220,
220,
299,
15853,
362,
198,
198,
4798,
366,
220,
220,
220,
657,
553,
198,
4798,
366,
19629,
1,
198
] | 3.285714 | 343 |
"""
In this file, I am messing around with using generator functions
to handle things like pattern matching in LifeEventRules and
timestep sizes when handling level-of-detail changes
"""
from abc import abstractmethod
from typing import Generator, List, Protocol, Tuple
from dataclasses import dataclass
from neighborly.core.ecs import GameObject, Component
from neighborly.core.life_event import (
ILifeEventListener,
LifeEvent,
check_gameobject_preconditions,
handle_gameobject_effects,
)
strength_greater_than_10 = strength_greater_than(10)
@dataclass
@dataclass
if __name__ == "__main__":
main()
|
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7,
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31,
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6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 3.308901 | 191 |
"""
This file implements different preprocessing utils functions.
"""
import pandas as pd
import re
from stopwords import stopwords_nltk, stopwords_specific
import spacy
import unicodedata
def preprocess_string(nlp, input_string):
"""
Wraps all operations to ensure common normalization.
"""
processed_string = input_string.lower()
processed_string = special_structures(processed_string)
#NA for match processed_string = remove_stopwords(processed_string)
processed_string = replace_digit(processed_string)
processed_string = remove_trailings(processed_string)
processed_string = strip_accents(processed_string)
#processed_string = lemmatize(nlp, processed_string)
return processed_string
"""#############"""
"""Sub-functions"""
"""#############"""
def lemmatize(nlp, input_string):
"""
Lemmatizes an input string
"""
# Can use spacy pipeline to increase speed
doc = nlp(input_string)
return " ".join([token.lemma_ for token in doc])
def remove_stopwords(input_string):
"""
This function removes stopwords from an input string.
"""
stopwords = stopwords_nltk + stopwords_specific
output_string = " ".join(
[word for word in input_string.split() if word not in stopwords]
)
return output_string
def replace_digit(input_string):
"""
Remove all digits from an input string (Slow on large corpuses).
"""
output_string = "".join([i for i in input_string if not i.isdigit()])
return output_string
def remove_trailings(input_string):
"""
Remove duplicated spaces.
"""
output_string = " ".join(input_string.split())
return output_string
def special_structures(input_string):
"""
Replace some special structures by space.
"""
input_string = input_string.replace("'", " ")
input_string = input_string.replace("(", " ")
input_string = input_string.replace(")", " ")
input_string = input_string.replace("1er ", " ")
input_string = input_string.replace(",", " ")
input_string = input_string.replace("«", " ")
input_string = input_string.replace("»", " ")
output_string = input_string.replace("n°", " ")
return output_string
def strip_accents(text):
"""
Removes accents.
"""
try:
text = unicode(text, 'utf-8')
except NameError: # unicode is a default on python 3
pass
text = unicodedata.normalize('NFD', text)\
.encode('ascii', 'ignore')\
.decode("utf-8")
return str(text)
# UNUSED
def regex_loi(input_series: pd.Series) -> pd.Series:
"""
Finds the law patterns that match a given token.
"""
token = r"(\w+).*\s\d{4}\s"
replace_by = "<LOI> "
# Finds patterns that match tokens
types = input_series.apply(
lambda s: m.group(1).lower() if (m := re.match(token, s)) else None
)
types = set(types)
types.discard(None)
# Change "arrêté du ... 2021" en <LOI>
patterns = [rf"{type_loi}(.*?)\s\d{{4}}\s" for type_loi in types]
for pattern in patterns:
output_series = input_series.apply(
lambda s: re.sub(pattern, replace_by, s, flags=re.IGNORECASE)
)
return output_series
|
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] | 2.645902 | 1,220 |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Dict, List, Tuple, Union
import torch
import torch.utils.checkpoint as checkpoint
from fairseq import utils
def checkpoint_wrapper(m):
"""
A friendlier wrapper for performing activation checkpointing.
Compared to the PyTorch version, this version:
- wraps an nn.Module, so that all subsequent calls will use checkpointing
- handles keyword arguments in the forward
- handles non-Tensor outputs from the forward
Usage::
checkpointed_module = checkpoint_wrapper(my_module)
a, b = checkpointed_module(x, y=3, z=torch.Tensor([1]))
"""
original_forward = m.forward
m.forward = _checkpointed_forward
return m
def pack_kwargs(*args, **kwargs) -> Tuple[List[str], List[Any]]:
"""
Usage::
kwarg_keys, flat_args = pack_kwargs(1, 2, a=3, b=4)
args, kwargs = unpack_kwargs(kwarg_keys, flat_args)
assert args == [1, 2]
assert kwargs == {"a": 3, "b": 4}
"""
kwarg_keys = []
flat_args = list(args)
for k, v in kwargs.items():
kwarg_keys.append(k)
flat_args.append(v)
return kwarg_keys, flat_args
def split_non_tensors(
mixed: Union[torch.Tensor, Tuple[Any]]
) -> Tuple[Tuple[torch.Tensor], Dict[str, List[Any]]]:
"""
Usage::
x = torch.Tensor([1])
y = torch.Tensor([2])
tensors, packed_non_tensors = split_non_tensors((x, y, None, 3))
recon = unpack_non_tensors(tensors, packed_non_tensors)
assert recon == (x, y, None, 3)
"""
if isinstance(mixed, torch.Tensor):
return (mixed,), None
tensors = []
packed_non_tensors = {"is_tensor": [], "objects": []}
for o in mixed:
if isinstance(o, torch.Tensor):
packed_non_tensors["is_tensor"].append(True)
tensors.append(o)
else:
packed_non_tensors["is_tensor"].append(False)
packed_non_tensors["objects"].append(o)
return tuple(tensors), packed_non_tensors
class CheckpointFunction(torch.autograd.Function):
"""Similar to the torch version, but support non-Tensor outputs.
The caller is expected to provide a dict (*parent_ctx_dict*) that will hold
the non-Tensor outputs. These should be combined with the Tensor *outputs*
by calling ``unpack_non_tensors``.
"""
@staticmethod
@staticmethod
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2488,
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628,
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198
] | 2.457971 | 1,035 |
from dataclasses import dataclass
from civic_jabber_ingest.models.base import DataModel
from civic_jabber_ingest.utils.xml import get_jinja_template
@dataclass
|
[
6738,
4818,
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] | 3.134615 | 52 |
# coding=utf-8
from collections import OrderedDict
EXPECTED = OrderedDict(
[
(
"bibjson",
OrderedDict(
[
(
"abstract",
"The inflammatory environment of demyelinated lesions in multiple sclerosis (MS) patients contributes to remyelination failure. Inflammation activates a cytoprotective pathway, the integrated stress response (ISR), but it remains unclear whether enhancing the ISR can improve remyelination in an inflammatory environment. To examine this possibility, the remyelination stage of experimental autoimmune encephalomyelitis (EAE), as well as a mouse model that incorporates cuprizone-induced demyelination along with CNS delivery of the proinflammatory cytokine IFN-γ were used here. We demonstrate that either genetic or pharmacological ISR enhancement significantly increased the number of remyelinating oligodendrocytes and remyelinated axons in the inflammatory lesions. Moreover, the combined treatment of the ISR modulator Sephin1 with the oligodendrocyte differentiation enhancing reagent bazedoxifene increased myelin thickness of remyelinated axons to pre-lesion levels. Taken together, our findings indicate that prolonging the ISR protects remyelinating oligodendrocytes and promotes remyelination in the presence of inflammation, suggesting that ISR enhancement may provide reparative benefit to MS patients.",
),
(
"author",
[
OrderedDict(
[
(
"affiliation",
"Department of Neurology, Division of Multiple Sclerosis and Neuroimmunology, Northwestern University Feinberg School of Medicine, Chicago, United States",
),
("name", "Yanan Chen"),
(
"orcid_id",
"https://orcid.org/0000-0001-5510-231X",
),
]
),
OrderedDict(
[
(
"affiliation",
"Department of Neurology, Division of Multiple Sclerosis and Neuroimmunology, Northwestern University Feinberg School of Medicine, Chicago, United States",
),
("name", "Rejani B Kunjamma"),
]
),
OrderedDict(
[
(
"affiliation",
"Department of Neurology, Division of Multiple Sclerosis and Neuroimmunology, Northwestern University Feinberg School of Medicine, Chicago, United States",
),
("name", "Molly Weiner"),
]
),
OrderedDict(
[
(
"affiliation",
"Weill Institute for Neuroscience, Department of Neurology, University of California, San Francisco, San Francisco, United States",
),
("name", "Jonah R Chan"),
(
"orcid_id",
"https://orcid.org/0000-0002-2176-1242",
),
]
),
OrderedDict(
[
(
"affiliation",
"Department of Neurology, Division of Multiple Sclerosis and Neuroimmunology, Northwestern University Feinberg School of Medicine, Chicago, United States",
),
("name", "Brian Popko"),
(
"orcid_id",
"https://orcid.org/0000-0001-9948-2553",
),
]
),
],
),
(
"identifier",
[
OrderedDict(
[("id", "10.7554/eLife.65469"), ("type", "doi")]
),
OrderedDict([("id", "2050-084X"), ("type", "eissn")]),
OrderedDict([("id", "e65469"), ("type", "elocationid")]),
],
),
("journal", OrderedDict([("volume", "10")])),
(
"keywords",
[
"integrated stress response",
"remyelination",
"interferon gamma",
"oligodendrocyte",
"cuprizone",
"multiple sclerosis",
],
),
(
"link",
[
OrderedDict(
[
("content_type", "text/html"),
("type", "fulltext"),
("url", "https://elifesciences.org/articles/65469"),
]
)
],
),
("month", "3"),
(
"title",
"Prolonging the integrated stress response enhances CNS remyelination in an inflammatory environment",
),
("year", "2021"),
]
),
)
]
)
|
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220,
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220,
1267,
198,
220,
220,
220,
2361,
198,
8,
198
] | 1.579424 | 4,199 |
# Copyright 2022 The BladeDISC Authors. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
__TF_LOG_ENV = 'TF_CPP_MIN_LOG_LEVEL'
__ENV_VALUE = os.environ.get(__TF_LOG_ENV, None)
try:
import tf2onnx # noqa: F401
finally:
if __ENV_VALUE is not None:
os.environ[__TF_LOG_ENV] = __ENV_VALUE
else:
del os.environ[__TF_LOG_ENV]
|
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25,
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220,
220,
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220,
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13,
268,
2268,
58,
834,
10234,
62,
25294,
62,
1677,
53,
60,
198
] | 2.996552 | 290 |
import subprocess
import os
import sys
def download_file_from_storage(gs_file_path):
"""download a file from GCS into ml-engine running container
Arguments:
gs_ile_path: string path to the MOJO file.
Returns:
string: path of the downloaded file
"""
file_name = "{0}".format(gs_file_path.split("/")[-1])
subprocess.check_call(['gsutil','-q', 'cp', gs_file_path, file_name], stderr=sys.stdout)
path = "{0}/{1}".format(os.getcwd(),file_name)
return path
def save_in_gcs(file_path, gcs_path):
"""Store a file into GCS
Arguments:
file_path: string with the file path.
gcs_path: string path to the GCS folder
"""
subprocess.check_call(['gsutil','-q', 'cp', file_path, gcs_path], stderr=sys.stdout)
|
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25,
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220,
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62,
6978,
4357,
336,
1082,
81,
28,
17597,
13,
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448,
8
] | 2.314121 | 347 |
import csv
import os
from purchases import Purchase
if __name__ == '__main__':
main()
|
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11748,
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] | 2.939394 | 33 |
'''
Collection of Text Classification Keras Algorithms for Toxic Comment Classification Challenge.
https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge
'''
# Keras
from keras.layers import (Dense, Input, Bidirectional, Activation, Dropout, Embedding, Flatten, CuDNNLSTM, CuDNNGRU,
Conv2D, MaxPool2D, concatenate, K, Reshape, LSTM)
from keras.models import Model
from keras import regularizers
from keras.utils import multi_gpu_model
def blstm_2dcnn(maxlen, max_features, embed_size, embedding_matrix,
embedding_dropout = .5,
blstm_units = 300,
blstm_dropout = .2,
cnn_filters = 100,
cnn_kernel_size = (5,5),
max_pool_size = (5,5),
dense_dropout = .4,
l2_reg = .00001,
gpus = 1):
'''
Bidirectional LSTM with Two-dimensional Max Pooling
:param maxlen: max length of sequence
:param max_features: max number of word embeddings
:param embed_size: dimension of word embeddings
:param embedding_matrix: embedding matrix created from embed file
:param embedding_dropout: dropout after embedding layer
:param blstm_units: number of lstm units for the biderectional lstm
:param blstm_dropout: dropout after the blstm layer
:param cnn_filters: number of CNN filters
:param cnn_kernel_size: kernel size of the convolution
:param max_pool_size: max pool size
:param dense_dropout: dropout before dense layer
:param l2_reg: l2 kernel regularizer parameter
:gpus: number of gpus
:returns: Keras parallel model
'''
inp = Input(shape=(maxlen, ))
x = Embedding(max_features, embed_size, weights=[embedding_matrix], input_length=maxlen)(inp)
x = Dropout(embedding_dropout)(x)
x = Bidirectional(CuDNNLSTM(blstm_units, return_sequences=True), merge_mode='sum')(x)
x = Dropout(blstm_dropout)(x)
x = Reshape((maxlen, blstm_units, 1))(x)
x = Conv2D(cnn_filters, kernel_size=cnn_kernel_size, padding='valid', kernel_initializer='glorot_uniform')(x)
x = MaxPool2D(pool_size=max_pool_size)(x)
x = Flatten()(x)
x = Dropout(dense_dropout)(x)
x = Dense(6, activation = "sigmoid", kernel_regularizer=regularizers.l2(l2_reg))(x)
parallel_model = Model(inputs = inp, outputs = x)
parallel_model = multi_gpu_model(parallel_model, gpus=gpus)
parallel_model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
return parallel_model
def bgru_2dcnn(maxlen, max_features, embed_size, embedding_matrix,
embedding_dropout = .5,
bgru_units = 300,
bgru_dropout = .2,
cnn_filters = 100,
cnn_kernel_size = (5,5),
max_pool_size = (5,5),
dense_dropout = .4,
l2_reg = .00001,
gpus = 1):
'''
Bidirectional GRU with Two-dimensional Max Pooling
:param maxlen: max length of sequence
:param max_features: max number of word embeddings
:param embed_size: dimension of word embeddings
:param embedding_matrix: embedding matrix created from embed file
:param embedding_dropout: dropout after embedding layer
:param bgru_units: number of gru units for the biderectional gru
:param bgru_dropout: dropout after the bgru layer
:param cnn_filters: number of cnn filters
:param cnn_kernel_size: kernel size of the convolution
:param max_pool_size: max pool size
:param dense_dropout: dropout before dense layer
:param l2_reg: l2 kernel regularizer parameter
:gpus: number of gpus
:returns: Keras parallel model
'''
inp = Input(shape=(maxlen, ))
x = Embedding(max_features, embed_size, weights=[embedding_matrix], input_length=maxlen)(inp)
x = Dropout(embedding_dropout)(x)
x = Bidirectional(CuDNNGRU(bgru_units, return_sequences=True), merge_mode='sum')(x)
x = Dropout(bgru_dropout)(x)
x = Reshape((maxlen, bgru_units, 1))(x)
x = Conv2D(cnn_filters, kernel_size=cnn_kernel_size, padding='valid', kernel_initializer='glorot_uniform')(x)
x = MaxPool2D(pool_size=max_pool_size)(x)
x = Flatten()(x)
x = Dropout(dense_dropout)(x)
x = Dense(6, activation = "sigmoid", kernel_regularizer=regularizers.l2(l2_reg))(x)
parallel_model = Model(inputs = inp, outputs = x)
parallel_model = multi_gpu_model(parallel_model, gpus=gpus)
parallel_model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
return parallel_model
|
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] | 2.352463 | 1,969 |
#!/usr/bin/python
import socket
from thread import *
import threading
from terminaltables import AsciiTable
from chat_module import *
reset="\033[0;0m"
red="\033[38;5;9m"
byellow="\033[38;5;3m"
yellowb="\033[38;5;11m"
blue="\033[38;5;27m"
purple="\033[1;33;35m"
cyan="\033[38;5;6m"
white="\033[38;5;7m"
orange="\033[38;5;202m"
lblue="\033[38;5;117m"
green="\033[38;5;2m"
host = ''
port = 8888
TR_num = []
clients_lists = []
TR_ip = []
TR_port = []
thread_num = 0
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind((host, port))
print "[+] Binded successfully."
s.listen(5)
print "[+] Listening on port {}".format(green + str(port) + reset)
start_new_thread(CMD, ())
while 1:
try:
c, addr = s.accept()
clients_lists.append(c)
thread_num += 1
print "[+] Client%s connected. IP : %s PORT : %s" % (red + str(thread_num) + reset, red + str(addr[0]) + reset, red + str(addr[1]) + reset)
conn_data = {'IP':str(addr[0]), 'PORT':str(addr[1])}
start_new_thread(threaded, (c,thread_num, conn_data))
except KeyboardInterrupt:
print "[+] Closing.."
break
s.close()
|
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] | 1.994048 | 672 |
# -*- coding: utf-8 -*-
# @Time : 2019/7/11 10:32
# @Author : hoo
# @Site :
# @File : korok.py
# @Software: PyCharm Community Edition
'''
2019/7/9 : 日志清理脚本
'''
import codecs
import glob
import traceback
import tarfile
import subprocess
import sys
import datetime
import time
import shutil
import os
import logging
import optparse
import shlex
import socket
import fnmatch
import re
import platform
# python2 python3 import diff
from sys import version_info
if version_info.major == 2:
import ConfigParser
else:
import configparser as ConfigParser
'''
# 数据备份
[archive-eg]
action=archive
# 备份原路径
src=/home/ap/dev/app/logs
dst=/home/ap/dev/backup
pattern=/home/ap/dev/app/logs/2018*.log
# 备份文件是否带时间戳
timestamp=y
# 是否保存原文件
reserve=y
# day-hour-minute-second
mtime=0-0-0-01
'''
'''
# 数据清理
[clear-test]
action=clear
src=./test_folder/dst
pattern=*.tar.gz
mtime=0-0-0-01
timestamp=y
recursive=y
'''
def ParseArgs():
'''
参数解析
:return: option args
'''
parser = optparse.OptionParser()
parser.add_option(
"-f",
"--file",
type="string",
dest="filename",
help="Specify the Config file",
default="setting.ini")
parser.add_option(
"-n",
"--node",
type="string",
dest="node",
help="Specify the the name of Server/Node")
parser.add_option(
"-s",
"--section",
type="string",
dest="section",
help="Specify the Section to Run",
default="clear-test")
parser.add_option(
"-l",
"--log",
type="string",
dest="log",
help="Specify the log path")
parser.add_option(
"-d",
action="store_true",
default='True',
dest="debug",
help="Indicate whether to log debug info")
(options, args) = parser.parse_args()
if not options.filename:
options.error(
'Error : Config file Missing. Use -f or --file to specify the config file')
print('*' * 50)
print(options)
print('*' * 50)
return options, args
if __name__ == '__main__':
main()
|
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9,
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8,
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7,
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8,
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1441,
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834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
628
] | 2.116071 | 1,008 |
import doctest
from pkgutil import iter_modules
|
[
11748,
10412,
395,
220,
198,
6738,
279,
10025,
22602,
1330,
11629,
62,
18170,
628
] | 3.571429 | 14 |
__version__ = '0.2.9'
__title__ = 'tfpromote'
__description__ = 'Compare and promote Terraform files from dev to prod environments.'
__url__ = 'https://github.com/billtrust/terraform-promote'
__author__ = 'Doug Kerwin'
__author_email__ = '[email protected]'
__license__ = 'MIT'
__keywords__ = ['terraform']
|
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] | 2.780702 | 114 |
from zorg.driver import Driver
from multiprocessing import Queue
from threading import Thread
import time
|
[
6738,
1976,
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13,
26230,
1330,
12434,
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] | 4.115385 | 26 |
import random
import uuid
import os
import gevent
from jumpscale.clients.explorer.models import NextAction, WorkloadType
from jumpscale.loader import j
from jumpscale.sals.reservation_chatflow import deployer
from jumpscale.sals.reservation_chatflow.deployer import DeploymentFailed
from .base_component import VDCBaseComponent
from .scheduler import Scheduler
from textwrap import dedent
VDC_PARENT_DOMAIN = j.core.config.get("VDC_PARENT_DOMAIN", "grid.tf")
PROXY_SERVICE_TEMPLATE = """
kind: Service
apiVersion: v1
metadata:
name: {{ service_name }}
spec:
type: ClusterIP
ports:
- port: {{ port }}
"""
PROXY_ENDPOINT_TEMPLATE = """
kind: Endpoints
apiVersion: v1
metadata:
name: {{ endpoint_name }}
subsets:
- addresses:
{% for address in addresses %}
- ip: {{ address }}
{% endfor %}
ports:
- port: {{ port }}
"""
PROXY_INGRESS_TEMPLATE = """
apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
name: {{ ingress_name }}
{% if force_https %}
annotations:
ingress.kubernetes.io/ssl-redirect: "true"
{% endif %}
spec:
rules:
- host: {{ hostname }}
http:
paths:
- path: /
backend:
serviceName: {{ service_name }}
servicePort: {{ service_port }}
"""
|
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62,
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13,
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1420,
263,
1330,
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434,
37,
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4,
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220,
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220,
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25,
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13,
74,
23,
82,
13,
952,
14,
85,
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25,
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220,
220,
220,
532,
2583,
25,
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2583,
3672,
34949,
198,
220,
220,
220,
220,
220,
2638,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13532,
25,
198,
220,
220,
220,
220,
220,
220,
220,
532,
3108,
25,
1220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30203,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2139,
5376,
25,
22935,
2139,
62,
3672,
34949,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2139,
13924,
25,
22935,
2139,
62,
634,
34949,
198,
37811,
628
] | 2.603696 | 487 |
"""UR URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path
from django.conf.urls import url,include
from urmovie.views import main_view,movie_view,actor_view,contact_view
"""
URMovie应用下的路由系统
"""
urlpatterns = [
path('', main_view.index),
path('index', main_view.index),
path('movie_class', main_view.movie_class),
path('actor_class', main_view.actor_class),
path('contact', main_view.contact),
url(r'^recommend-(?P<name>\d+)',movie_view.recommend),
url(r'^queryMovieByAge-(?P<age>\d+)-(?P<pageid>\d+)',movie_view.queryMovieByAge),
url(r'^queryMovieByCate-(?P<cate>\d+)-(?P<pageid>\d+)',movie_view.queryMovieByCate),
url(r'^queryMovie-(?P<id>\d+)',movie_view.queryMovie),
url(r'^queryActorByNation-(?P<nation>\d+)-(?P<pageid>\d+)',actor_view.queryActorByNation),
url(r'^queryActor-(?P<id>\d+)',actor_view.queryActor)
]
|
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3256,
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40277,
3886,
46108,
828,
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220,
220,
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19016,
7,
81,
6,
61,
22766,
40277,
30420,
30,
47,
27,
312,
29,
59,
67,
28988,
3256,
11218,
62,
1177,
13,
22766,
40277,
8,
198,
60,
198
] | 2.505863 | 597 |
import os
from os.path import isfile, join
import time
import ctypes
folderpath = r"E:\All Projects\Auto Wallpaper"
all_files = [ f for f in os.listdir(folderpath) if isfile(join(folderpath, f))]
for image in all_files:
print(image)
ctypes.windll.user32.SystemParametersInfoW(20, 0, folderpath+ "\\" + image, 0)
time.sleep(1)
|
[
11748,
28686,
198,
6738,
28686,
13,
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1330,
318,
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11,
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198,
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269,
19199,
198,
198,
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6978,
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374,
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36,
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7,
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220,
220,
220,
269,
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13,
7972,
297,
13,
7220,
2624,
13,
11964,
48944,
12360,
54,
7,
1238,
11,
657,
11,
9483,
6978,
10,
366,
6852,
1,
1343,
2939,
11,
657,
8,
198,
220,
220,
220,
640,
13,
42832,
7,
16,
8,
198
] | 2.685039 | 127 |
import matplotlib.pyplot as plt
import numpy as np
import os
import re
plotsDir = "plots"
# function to add an output, if experiment and value are both defined
# function to parse a csv timeFile
# with lines s.t. "experiment,logFile,elapsedTime,fileSize,timePerMB"
# function to adapt a given "experimentValue"
# - if load rate (of the form "0.x"), translated to rate of requests/s
# - if probability (of the form "x%"), unchanged
# - if name of root causing service, translated to length of corresponding cascade
# function to plot "experiment" list
# function to print experiment results
if __name__ == "__main__":
print("Generating plots...",end="",flush=True)
# create folder where to store plots (if not existing)
if not os.path.exists(plotsDir):
os.makedirs(plotsDir)
# confige plt's defaults
plt.rcParams.update({'font.size': 28})
plt.figure(figsize=(7, 4.3))
# ----------------
# plot outputs
# ----------------
outputs = parseOutputs("outputs.txt")
for o in outputs["count"]:
plot("count",outputs["count"][o],"explanations",outputs["roots"][o],"root causes",o,6)
plot("success_percentage",outputs["accuracy"][o],None,None,None,o,100)
# ----------------
# plot times
# ----------------
times = parseTimes("times.csv")
for t in times:
plot("time",times[t],None,None,None,t,501)
print("done!")
printResults("count (cascades)",outputs["count"])
printResults("count (root causes)",outputs["roots"])
printResults("success_percentage",outputs["accuracy"])
printResults("times",times)
|
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] | 2.798623 | 581 |
# -*- coding: utf-8 -*-
"""
DC Resistivity Forward Simulation in 2.5D
=========================================
Here we use the module *SimPEG.electromagnetics.static.resistivity* to predict
DC resistivity data and plot using a pseudosection. In this tutorial, we focus
on the following:
- How to define the survey
- How to define the forward simulation
- How to predict normalized voltage data for a synthetic conductivity model
- How to include surface topography
- The units of the model and resulting data
"""
#########################################################################
# Import modules
# --------------
#
from discretize import TreeMesh
from discretize.utils import mkvc, refine_tree_xyz
from SimPEG.utils import model_builder, surface2ind_topo
from SimPEG.utils.io_utils.io_utils_electromagnetics import write_dcip2d_ubc
from SimPEG import maps, data
from SimPEG.electromagnetics.static import resistivity as dc
from SimPEG.electromagnetics.static.utils.static_utils import (
generate_dcip_sources_line,
apparent_resistivity_from_voltage,
plot_pseudosection,
)
import os
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
try:
from pymatsolver import Pardiso as Solver
except ImportError:
from SimPEG import SolverLU as Solver
write_output = False
mpl.rcParams.update({"font.size": 16})
# sphinx_gallery_thumbnail_number = 3
###############################################################
# Defining Topography
# -------------------
#
# Here we define surface topography as an (N, 3) numpy array. Topography could
# also be loaded from a file. In our case, our survey takes place within a set
# of valleys that run North-South.
#
x_topo, y_topo = np.meshgrid(
np.linspace(-3000, 3000, 601), np.linspace(-3000, 3000, 101)
)
z_topo = 40.0 * np.sin(2 * np.pi * x_topo / 800) - 40.0
x_topo, y_topo, z_topo = mkvc(x_topo), mkvc(y_topo), mkvc(z_topo)
topo_xyz = np.c_[x_topo, y_topo, z_topo]
# Create 2D topography. Since our 3D topography only changes in the x direction,
# it is easy to define the 2D topography projected along the survey line. For
# arbitrary topography and for an arbitrary survey orientation, the user must
# define the 2D topography along the survey line.
topo_2d = np.unique(topo_xyz[:, [0, 2]], axis=0)
#####################################################################
# Create Dipole-Dipole Survey
# ---------------------------
#
# Here we define a single EW survey line that uses a dipole-dipole configuration.
# For the source, we must define the AB electrode locations. For the receivers
# we must define the MN electrode locations. Instead of creating the survey
# from scratch (see 1D example), we will use the *generat_dcip_survey_line* utility.
#
# Define survey line parameters
survey_type = "dipole-dipole"
dimension_type = "2D"
data_type = "volt"
end_locations = np.r_[-400.0, 400.0]
station_separation = 40.0
num_rx_per_src = 10
# Generate source list for DC survey line
source_list = generate_dcip_sources_line(
survey_type,
data_type,
dimension_type,
end_locations,
topo_2d,
num_rx_per_src,
station_separation,
)
# Define survey
survey = dc.survey.Survey(source_list, survey_type=survey_type)
###############################################################
# Create Tree Mesh
# ------------------
#
# Here, we create the Tree mesh that will be used to predict DC data.
#
dh = 4 # base cell width
dom_width_x = 3200.0 # domain width x
dom_width_z = 2400.0 # domain width z
nbcx = 2 ** int(np.round(np.log(dom_width_x / dh) / np.log(2.0))) # num. base cells x
nbcz = 2 ** int(np.round(np.log(dom_width_z / dh) / np.log(2.0))) # num. base cells z
# Define the base mesh
hx = [(dh, nbcx)]
hz = [(dh, nbcz)]
mesh = TreeMesh([hx, hz], x0="CN")
# Mesh refinement based on topography
mesh = refine_tree_xyz(
mesh,
topo_xyz[:, [0, 2]],
octree_levels=[0, 0, 4, 4],
method="surface",
finalize=False,
)
# Mesh refinement near transmitters and receivers. First we need to obtain the
# set of unique electrode locations.
electrode_locations = np.c_[
survey.locations_a,
survey.locations_b,
survey.locations_m,
survey.locations_n,
]
unique_locations = np.unique(
np.reshape(electrode_locations, (4 * survey.nD, 2)), axis=0
)
mesh = refine_tree_xyz(
mesh, unique_locations, octree_levels=[4, 4], method="radial", finalize=False
)
# Refine core mesh region
xp, zp = np.meshgrid([-600.0, 600.0], [-400.0, 0.0])
xyz = np.c_[mkvc(xp), mkvc(zp)]
mesh = refine_tree_xyz(
mesh, xyz, octree_levels=[0, 0, 2, 8], method="box", finalize=False
)
mesh.finalize()
###############################################################
# Create Conductivity Model and Mapping for Tree Mesh
# -----------------------------------------------------
#
# It is important that electrodes are not modeled as being in the air. Even if the
# electrodes are properly located along surface topography, they may lie above
# the discretized topography. This step is carried out to ensure all electrodes
# lie on the discretized surface.
#
# Define conductivity model in S/m (or resistivity model in Ohm m)
air_conductivity = 1e-8
background_conductivity = 1e-2
conductor_conductivity = 1e-1
resistor_conductivity = 1e-3
# Find active cells in forward modeling (cell below surface)
ind_active = surface2ind_topo(mesh, topo_xyz[:, [0, 2]])
# Define mapping from model to active cells
nC = int(ind_active.sum())
conductivity_map = maps.InjectActiveCells(mesh, ind_active, air_conductivity)
# Define model
conductivity_model = background_conductivity * np.ones(nC)
ind_conductor = model_builder.getIndicesSphere(np.r_[-120.0, -160.0], 60.0, mesh.gridCC)
ind_conductor = ind_conductor[ind_active]
conductivity_model[ind_conductor] = conductor_conductivity
ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -100.0], 60.0, mesh.gridCC)
ind_resistor = ind_resistor[ind_active]
conductivity_model[ind_resistor] = resistor_conductivity
# Plot Conductivity Model
fig = plt.figure(figsize=(9, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
norm = LogNorm(vmin=1e-3, vmax=1e-1)
ax1 = fig.add_axes([0.14, 0.17, 0.68, 0.7])
mesh.plot_image(
plotting_map * conductivity_model, ax=ax1, grid=False, pcolor_opts={"norm": norm}
)
ax1.set_xlim(-600, 600)
ax1.set_ylim(-600, 0)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax2 = fig.add_axes([0.84, 0.17, 0.03, 0.7])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label(r"$\sigma$ (S/m)", rotation=270, labelpad=15, size=12)
plt.show()
###############################################################
# Project Survey to Discretized Topography
# ----------------------------------------
#
# It is important that electrodes are not model as being in the air. Even if the
# electrodes are properly located along surface topography, they may lie above
# the discretized topography. This step is carried out to ensure all electrodes
# like on the discretized surface.
#
survey.drape_electrodes_on_topography(mesh, ind_active, option="top")
#######################################################################
# Predict DC Resistivity Data
# ---------------------------
#
# Here we predict DC resistivity data. If the keyword argument *sigmaMap* is
# defined, the simulation will expect a conductivity model. If the keyword
# argument *rhoMap* is defined, the simulation will expect a resistivity model.
#
simulation = dc.simulation_2d.Simulation2DNodal(
mesh, survey=survey, sigmaMap=conductivity_map, solver=Solver
)
# Predict the data by running the simulation. The data are the raw voltage in
# units of volts.
dpred = simulation.dpred(conductivity_model)
#######################################################################
# Plotting in Pseudo-Section
# --------------------------
#
# Here, we demonstrate how to plot 2D data in pseudo-section.
# First, we plot the voltages in pseudo-section as a scatter plot. This
# allows us to visualize the pseudo-sensitivity locations for our survey.
# Next, we plot the apparent conductivities in pseudo-section as a filled
# contour plot.
#
# Plot voltages pseudo-section
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_axes([0.1, 0.15, 0.75, 0.78])
plot_pseudosection(
survey,
dobs=np.abs(dpred),
plot_type="scatter",
ax=ax1,
scale="log",
cbar_label="V/A",
scatter_opts={"cmap": mpl.cm.viridis},
)
ax1.set_title("Normalized Voltages")
plt.show()
# Get apparent conductivities from volts and survey geometry
apparent_conductivities = 1 / apparent_resistivity_from_voltage(survey, dpred)
# Plot apparent conductivity pseudo-section
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_axes([0.1, 0.15, 0.75, 0.78])
plot_pseudosection(
survey,
dobs=apparent_conductivities,
plot_type="contourf",
ax=ax1,
scale="log",
cbar_label="S/m",
mask_topography=True,
contourf_opts={"levels": 20, "cmap": mpl.cm.viridis},
)
ax1.set_title("Apparent Conductivity")
plt.show()
#######################################################################
# Optional: Write out dpred
# -------------------------
#
# Write DC resistivity data, topography and true model
#
if write_output:
dir_path = os.path.dirname(__file__).split(os.path.sep)
dir_path.extend(["outputs"])
dir_path = os.path.sep.join(dir_path) + os.path.sep
if not os.path.exists(dir_path):
os.mkdir(dir_path)
# Add 10% Gaussian noise to each datum
np.random.seed(225)
std = 0.05 * np.abs(dpred)
dc_noise = std * np.random.rand(len(dpred))
dobs = dpred + dc_noise
# Create a survey with the original electrode locations
# and not the shifted ones
# Generate source list for DC survey line
source_list = generate_dcip_sources_line(
survey_type,
data_type,
dimension_type,
end_locations,
topo_xyz,
num_rx_per_src,
station_separation,
)
survey_original = dc.survey.Survey(source_list)
# Write out data at their original electrode locations (not shifted)
data_obj = data.Data(survey_original, dobs=dobs, standard_deviation=std)
fname = dir_path + "dc_data.obs"
write_dcip2d_ubc(fname, data_obj, "volt", "dobs")
fname = dir_path + "topo_xyz.txt"
np.savetxt(fname, topo_xyz, fmt="%.4e")
|
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78,
62,
5431,
89,
11,
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2625,
7225,
19,
68,
4943,
198
] | 2.878471 | 3,637 |
#!/bin/env python3
from os import walk
from os.path import abspath, dirname, join, realpath, splitext
from subprocess import call
from sys import argv, stderr
checks = [
"clang-analyzer-*",
"cppcoreguidelines-*",
"llvm-namespace-comment",
"modernize-*",
"performance-*",
"readability-*",
]
if __name__ == "__main__":
if len(argv) < 2:
print("Specify path to build directory", file=stderr)
exit(1)
build_dir = argv[1]
project_dir = abspath(join(dirname(realpath(__file__)), ".."))
for root, _, files in walk("src"):
for file in files:
path = join(root, file)
if splitext(path)[1] != ".cpp":
continue
cmd = [
"clang-tidy",
"-p", build_dir,
"-header-filter=" + join(project_dir, "include", "ieompp")+".*",
"-checks=" + ','.join(checks),
"-fix",
path
]
print(path)
call(cmd)
|
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198,
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220,
220,
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220,
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13049,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
869,
7,
28758,
8,
198
] | 1.95977 | 522 |
import random
from PIL import Image
import lmdb
import h5py
import numpy as np
import torch
from torch.utils.data import Dataset
import torchvision
from torchvision.transforms import transforms
|
[
11748,
4738,
198,
6738,
350,
4146,
1330,
7412,
198,
11748,
300,
9132,
65,
198,
11748,
289,
20,
9078,
198,
11748,
299,
32152,
355,
45941,
198,
198,
11748,
28034,
198,
6738,
28034,
13,
26791,
13,
7890,
1330,
16092,
292,
316,
198,
11748,
28034,
10178,
198,
6738,
28034,
10178,
13,
7645,
23914,
1330,
31408,
628,
628,
198
] | 3.618182 | 55 |
import pathlib
import numbers
import random
from typing import Any, Optional
import numpy as np
import torch
from torch import Tensor
from torch.jit.annotations import List, Tuple
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
import torchvision.datasets as datasets
import torchvision.transforms.functional as TF
from torchvision.transforms import InterpolationMode
from PIL import Image
import cv2
try:
import accimage
except ImportError:
accimage = None
# Custom Augment Classes that can be put into Compose
def apply_color_distortion(x: Tensor, bright: float=1., contrast: float=1., saturation: float=1., hue: float=0., gamma: float=1.) -> Tensor:
"""Applies the Pytorchvision functional HSV+G color adjustments in a deterministic manner.
Args:
x ([type]): [description]
bright (float, optional): How much to adjust the brightness. Can be
any non negative number. 0 gives a black image, 1 gives the
original image while 2 increases the brightness by a factor of 2. Defaults to 1..
contrast (float, optional): How much to adjust the contrast. Can be any
non negative number. 0 gives a solid gray image, 1 gives the
original image while 2 increases the contrast by a factor of 2. Defaults to 1..
saturation (float, optional): How much to adjust the saturation. 0 will
give a black and white image, 1 will give the original image while
2 will enhance the saturation by a factor of 2. Defaults to 1..
hue (float, optional): How much to shift the hue channel. Should be in
[-0.5, 0.5]. 0.5 and -0.5 give complete reversal of hue channel in
HSV space in positive and negative direction respectively.
0 means no shift. Therefore, both -0.5 and 0.5 will give an image
with complementary colors while 0 gives the original image. Defaults to 0..
gamma (float, optional): Non negative real number, same as :math:`\gamma` in the equation.
gamma larger than 1 make the shadows darker,
while gamma smaller than 1 make dark regions lighter. Defaults to 1..
use_gray (bool, optional): Applies grayscale conversion after all others.
Returns:
PIL Image or Tensor: Gamma correction adjusted image.
"""
x = transforms.functional.adjust_contrast(x, contrast)
x = transforms.functional.adjust_brightness(x, bright)
x = transforms.functional.adjust_saturation(x, saturation)
x = transforms.functional.adjust_hue(x, hue)
x = transforms.functional.adjust_gamma(x, gamma)
return x
|
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] | 3.0907 | 871 |
# Copyright 2021 NREL
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
import os
from matplotlib import pyplot as plt
import pandas as pd
from flasc.dataframe_operations import (
dataframe_filtering as dff,
dataframe_manipulations as dfm,
)
if __name__ == "__main__":
# In this script, we do some very basic filtering steps, such as filtering
# for negative wind speeds and power productions. We also filter the data
# by one or multiple variables that inherently already tells us if data
# is good or bad according to the data logger/turbine itself. In our case,
# this self-flagged variable is "is_operational_normal_00x".
# Load data and get properties
df = load_data()
num_turbines = dfm.get_num_turbines(df)
root_path = os.path.dirname(os.path.abspath(__file__))
out_path = os.path.join(root_path, "data", "02_basic_filtered")
figs_path = os.path.join(out_path, "figures")
os.makedirs(figs_path, exist_ok=True)
# Basic filters: address self flags and obviously wrong points
for ti in range(num_turbines):
# Specify filtering conditions
conds = [
~df["is_operation_normal_{:03d}".format(ti)], # Self-status
df["ws_{:03d}".format(ti)] <= 0.0, # Non-negative wind speeds
df["pow_{:03d}".format(ti)] <= 0.0,
] # Non-negative powers
# Retrieve a single, combined condition array
conds_combined = conds[0]
for cond in conds:
conds_combined = conds_combined | cond
# Plot time vs filtered data
fig, ax = dff.plot_highlight_data_by_conds(df, conds, ti)
ax.legend(
["All data", "Bad self-status", "Negative WS", "Negative power"]
)
fp = os.path.join(figs_path, "basic_filtering_%03d.png" % ti)
print("Saving figure to {:s} for turbine {:03d}.".format(fp, ti))
fig.savefig(fp, dpi=200)
plt.close(fig)
# Apply filtering to dataframe
df = dff.df_mark_turbdata_as_faulty(
df, conds_combined, ti, verbose=True
)
# Remove unnecessary columns after filtering
self_status_cols = [
"is_operation_normal_%03d" % ti for ti in range(num_turbines)
]
df = df.drop(columns=self_status_cols) # Remove self status columns
# Save as a single file and as batch files
fout = os.path.join(out_path, "scada_data_60s.ftr")
print("Savig filtered data to {:s}.".format(fout))
os.makedirs(out_path, exist_ok=True)
df = df.reset_index(drop=("time" in df.columns))
df.to_feather(fout)
|
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] | 2.572264 | 1,197 |
import math
from scrappybara.langmodel.token_context import TokenContext
from scrappybara.preprocessing.tokenizer import Tokenizer
from scrappybara.utils.files import txt_file_reader
from scrappybara.utils.mutables import append_to_dict_list
|
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] | 3.641791 | 67 |
#!/usr/bin/env python3
#
# Copyright 2016 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Input socket plugin.
Waits for events from an output socket plugin running on another Instalog node.
See socket_common.py for protocol definition.
See input_socket_unittest.py for reference examples.
"""
import hashlib
import logging
import socket
import tempfile
import threading
import time
from cros.factory.instalog import datatypes
from cros.factory.instalog import log_utils
from cros.factory.instalog import plugin_base
from cros.factory.instalog.plugins import socket_common
from cros.factory.instalog.utils.arg_utils import Arg
from cros.factory.instalog.utils import file_utils
_DEFAULT_HOSTNAME = '0.0.0.0'
class ChecksumError(Exception):
"""Represents a checksum mismatch."""
class InputSocketReceiver(log_utils.LoggerMixin):
"""Receives a request from an output socket plugin."""
def ProcessRequest(self):
"""Receives a request from an output socket plugin."""
# Create the temporary directory for attachments.
with file_utils.TempDirectory(prefix='input_socket_') as self._tmp_dir:
self.debug('Temporary directory for attachments: %s', self._tmp_dir)
try:
events = []
num_events = self.RecvInt()
while num_events == 0:
self.Pong()
num_events = self.RecvInt()
total_bytes = 0
start_time = time.time()
for event_id in range(num_events):
event_bytes, event = self.RecvEvent()
self.debug('Received event[%d] size: %.2f kB', event_id,
event_bytes / 1024)
total_bytes += event_bytes
events.append(event)
receive_time = time.time() - start_time
except socket.timeout:
self.error('Socket timeout error, remote connection closed?')
self.Close()
return
except ChecksumError:
self.error('Checksum mismatch, abort')
self.Close()
return
except Exception:
self.exception('Unknown exception encountered')
self.Close()
return
self.debug('Notifying transmitting side of data-received (syn)')
self._conn.sendall(socket_common.DATA_RECEIVED_CHAR)
self.debug('Waiting for request-emit (ack)...')
if self._conn.recv(1) != socket_common.REQUEST_EMIT_CHAR:
self.error('Did not receive request-emit (ack), aborting')
self.Close()
return
self.debug('Calling Emit()...')
start_time = time.time()
if not self._plugin_api.Emit(events):
self.error('Unable to emit, aborting')
self.Close()
return
emit_time = time.time() - start_time
try:
self.debug('Success; sending emit-success to transmitting side '
'(syn-ack)')
self._conn.sendall(socket_common.EMIT_SUCCESS_CHAR)
except Exception:
self.exception('Received events were emitted successfully, but failed '
'to confirm success with remote side: duplicate data '
'may occur')
finally:
total_kbytes = total_bytes / 1024
self.info('Received %d events, total %.2f kB in %.1f+%.1f sec '
'(%.2f kB/sec)',
len(events), total_kbytes, receive_time, emit_time,
total_kbytes / receive_time)
self.Close()
def Pong(self):
"""Called for an empty transfer (0 events)."""
self.debug('Empty transfer: Pong!')
try:
self._conn.sendall(socket_common.PING_RESPONSE)
except Exception:
pass
def Close(self):
"""Shuts down and closes the socket stream."""
try:
self.debug('Closing socket')
self._conn.shutdown(socket.SHUT_RDWR)
self._conn.close()
except Exception:
self.exception('Error closing socket')
def RecvItem(self):
"""Returns the next item in socket stream."""
buf = b''
while True:
data = self._conn.recv(1)
if not data:
raise socket.timeout
if data == socket_common.SEPARATOR:
break
buf += data
return buf
def RecvInt(self):
"""Returns the next integer in socket stream."""
return int(self.RecvItem())
def RecvFieldParts(self):
"""Returns a generator to retrieve the next field in socket stream."""
total = self.RecvInt()
self.debug('RecvFieldParts total = %d bytes' % total)
progress = 0
local_hash = hashlib.sha1()
while progress < total:
recv_size = total - progress
# Recv may return any number of bytes <= recv_size, so it's important
# to check the size of its output.
out = self._conn.recv(recv_size)
if not out:
raise socket.timeout
local_hash.update(out)
progress += len(out)
yield progress, out
# Verify SHA1 checksum.
remote_checksum = self.RecvItem()
local_checksum = local_hash.hexdigest()
if remote_checksum.decode('utf-8') != local_checksum:
raise ChecksumError
def RecvField(self):
"""Returns the next field in socket stream."""
buf = b''
for unused_progress, field in self.RecvFieldParts():
buf += field
return buf
def RecvEvent(self):
"""Returns the next event in socket stream.
Returns:
A tuple with (total bytes, Event object)
"""
total_bytes = 0
# Retrieve the event itself.
event_field = self.RecvField()
total_bytes += len(event_field)
event = datatypes.Event.Deserialize(event_field.decode('utf-8'))
# An event is followed by its number of attachments.
num_atts = self.RecvInt()
self.debug('num_atts = %d', num_atts)
for att_index in range(num_atts):
# Attachment format: <attachment_id> <attachment_data>
att_id = self.RecvField()
total_bytes += len(att_id)
att_size, att_path = self.RecvAttachmentData()
total_bytes += att_size
self.debug('Attachment[%d] %s: %d bytes', att_index, att_id, att_size)
event.attachments[att_id] = att_path
self.debug('Retrieved event (%d bytes): %s', total_bytes, event)
return total_bytes, event
def RecvAttachmentData(self):
"""Receives attachment data and writes to a temporary file on disk.
Returns:
A tuple with (total bytes received, temporary path).
"""
progress = 0
with tempfile.NamedTemporaryFile('wb', dir=self._tmp_dir,
delete=False) as f:
for progress, bin_part in self.RecvFieldParts():
f.write(bin_part)
return progress, f.name
if __name__ == '__main__':
plugin_base.main()
|
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] | 2.506372 | 2,668 |
'''
Copyright (C) 2019 Simon D. Levy
MIT License
'''
from gym.envs.registration import register
register(
id='Lander-v0',
entry_point='gym_copter.envs:Lander2D',
max_episode_steps=2000
)
register(
id='Lander3D-v0',
entry_point='gym_copter.envs:Lander3D',
max_episode_steps=2000
)
register(
id='Lander3D-v1',
entry_point='gym_copter.envs:TargetedLander3D',
max_episode_steps=2000
)
register(
id='Distance-v0',
entry_point='gym_copter.envs:Distance',
max_episode_steps=1000
)
register(
id='Takeoff-v0',
entry_point='gym_copter.envs:Takeoff',
max_episode_steps=1000
)
|
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] | 2.064815 | 324 |
import ast
import logging
import argparse
import xml.etree.ElementTree as ET
import cv2
import vision_genprog.tasks.image_processing as image_processing
import vision_genprog.semanticSegmentersPop as semanticSegmentersPop
import os
import ast
import synthetic_heatmap.generators.stop_sign as stop_sign
logging.basicConfig(level=logging.DEBUG, format='%(asctime)-15s %(message)s')
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('validationPairsDirectory', help="The filepath to the validation image pairs")
parser.add_argument('--primitivesFilepath', help="The filepath to the primitives xml file. Default: 'vision_genprog/tasks/image_processing.xml'", default='vision_genprog/tasks/image_processing.xml')
parser.add_argument('--imageShapeHW', help="The image shape (height, width). Default='(256, 256)'", default='(256, 256)')
parser.add_argument('--outputDirectory', help="The output directory. Default: './outputs'", default='./outputs')
parser.add_argument('--numberOfIndividuals', help="The number of individuals. Default: 200", type=int, default=200)
parser.add_argument('--levelToFunctionProbabilityDict',
help="The probability to generate a function, at each level. Default: '{0: 1, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}'",
default='{0: 1, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}')
parser.add_argument('--proportionOfConstants',
help='The probability to generate a constant, when a variable could be used. Default: 0',
type=float, default=0)
parser.add_argument('--constantCreationParametersList',
help="The parameters to use when creating constants: [minFloat, maxFloat, minInt, maxInt, width, height]. Default: '[-1, 1, 0, 255, 256, 256]'",
default='[-1, 1, 0, 255, 256, 256]')
parser.add_argument('--numberOfGenerations', help="The number of generations to run. Default: 32", type=int,
default=32)
parser.add_argument('--weightForNumberOfNodes',
help="Penalty term proportional to the number of nodes. Default: 0.001", type=float,
default=0.001)
parser.add_argument('--numberOfTournamentParticipants',
help="The number of participants in selection tournaments. Default: 2", type=int, default=2)
parser.add_argument('--mutationProbability', help="The probability to mutate a child. Default: 0.1", type=float,
default=0.1)
parser.add_argument('--proportionOfNewIndividuals',
help="The proportion of randomly generates individuals per generation. Default: 0.1",
type=float, default=0.1)
parser.add_argument('--maximumNumberOfMissedCreationTrials',
help="The maximum number if missed creation trials. Default: 1000", type=int, default=1000)
parser.add_argument('--numberOfTrainingPairs', help="The number of generated training pairs, per epoch. Default: 160", type=int, default=160)
args = parser.parse_args()
imageShapeHW = ast.literal_eval(args.imageShapeHW)
levelToFunctionProbabilityDict = ast.literal_eval(args.levelToFunctionProbabilityDict)
constantCreationParametersList = ast.literal_eval(args.constantCreationParametersList)
main(
args.validationPairsDirectory,
args.primitivesFilepath,
imageShapeHW,
args.outputDirectory,
args.numberOfIndividuals,
levelToFunctionProbabilityDict,
args.proportionOfConstants,
constantCreationParametersList,
args.numberOfGenerations,
args.weightForNumberOfNodes,
args.numberOfTournamentParticipants,
args.mutationProbability,
args.proportionOfNewIndividuals,
args.maximumNumberOfMissedCreationTrials,
args.numberOfTrainingPairs
)
|
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] | 2.576094 | 1,531 |
import sys
from textwrap import indent as __indent_text
import click
CONTEXT_SETTINGS = {'help_option_names': ['-h', '--help']}
UNKNOWN_OPTIONS = {'help_option_names': [], 'ignore_unknown_options': True}
DEFAULT_INDENT = 4
|
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10354,
685,
29001,
71,
3256,
705,
438,
16794,
20520,
92,
198,
4944,
44706,
62,
3185,
51,
11053,
796,
1391,
6,
16794,
62,
18076,
62,
14933,
10354,
685,
4357,
705,
46430,
62,
34680,
62,
25811,
10354,
6407,
92,
198,
7206,
38865,
62,
12115,
3525,
796,
604,
628,
628,
628,
628
] | 2.795181 | 83 |
# ------------------------------------------------------------------
# Warp Sequencer
# (C) 2020 Michael DeHaan <[email protected]> & contributors
# Apache2 Licensed
# ------------------------------------------------------------------
# uses the code in smart.py or literal.py to evaluate a symbol that
# might be supported by either of those other classes. Also processes
# any mod expressions after those symbols. Used in clip evaluation.
from ..api.exceptions import *
from ..model.note import Note, NOTES, EQUIVALENCE
from ..model.chord import Chord, CHORD_TYPES
from .mod import ModExpression
import functools
import traceback
import re
import time
NOTE_SHORTCUT_REGEX = re.compile("([A-Za-z#]+)([0-9]*)")
CHORD_SYMBOLS = dict(
I = [ 1, 'major' ],
II = [ 2, 'major' ],
III = [ 3, 'major' ],
IV = [ 4, 'major' ],
V = [ 5, 'major' ],
VI = [ 6, 'major' ],
VII = [ 7, 'major' ],
i = [ 1, 'minor' ],
ii = [ 2, 'minor' ],
iii = [ 3, 'minor' ],
iv = [ 4, 'minor' ],
v = [ 5, 'minor' ],
vi = [ 6, 'minor' ],
vii = [ 7, 'minor' ],
)
CHORD_KEYS = CHORD_SYMBOLS.keys()
|
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6,
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6,
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220,
220,
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220,
220,
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6,
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220,
220,
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11,
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6,
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198,
220,
220,
410,
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685,
767,
11,
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6,
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8,
198,
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3398,
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62,
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16309,
796,
5870,
12532,
62,
23060,
10744,
3535,
50,
13,
13083,
3419,
628
] | 2.741546 | 414 |
import logging
from typing import Literal
import arrow
import discord
from discord.ext import commands
from naotimes.bot import naoTimesBot
from naotimes.context import naoTimesContext
from naotimes.converters import StealedEmote
IconLiteral = Literal[
"mfa_none",
"mfa_low",
"mfa_medium",
"mfa_high",
"mfa_extreme",
"boost",
"s_ol",
"s_off",
"s_idle",
"s_dnd",
]
|
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366,
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62,
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198,
220,
220,
220,
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62,
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1600,
198,
220,
220,
220,
366,
82,
62,
312,
293,
1600,
198,
220,
220,
220,
366,
82,
62,
67,
358,
1600,
198,
60,
628,
628
] | 2.409357 | 171 |
import os
import importlib
import pbx_gs_python_utils # needed for dependency import
from osbot_aws.Globals import Globals
from pbx_gs_python_utils.utils.Files import Files
from osbot_aws.tmp_utils.Temp_Files import Temp_Files
from osbot_aws.apis.Lambda import Lambda
from osbot_aws.apis.test_helpers.Temp_Aws_Roles import Temp_Aws_Roles
|
[
11748,
28686,
198,
11748,
1330,
8019,
198,
198,
11748,
279,
65,
87,
62,
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62,
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62,
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220,
220,
220,
220,
220,
220,
220,
220,
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220,
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220,
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220,
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9288,
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49,
4316,
1330,
24189,
62,
32,
18504,
62,
49,
4316,
628,
198
] | 2.283237 | 173 |
from dji_asdk_to_python.utils.message_builder import MessageBuilder
from dji_asdk_to_python.errors import DJIError
from dji_asdk_to_python.utils.shared import checkParameters
from dji_asdk_to_python.utils.socket_utils import SocketUtils
|
[
6738,
288,
7285,
62,
292,
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62,
1462,
62,
29412,
13,
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13,
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62,
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1330,
47068,
18274,
4487,
628
] | 3.131579 | 76 |
# streamlit run pydantic_streamlit_input.py
import streamlit as st
from pydantic import BaseModel
from typing import List, Dict
import streamlit_pydantic as sp
from pydantic import BaseModel, Field, HttpUrl
from enum import Enum
st.title("Use of pydantic for complex inputs")
data = sp.pydantic_input(key="my_form", model=ExampleModel)
if data:
st.write(data)
|
[
2,
4269,
18250,
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279,
5173,
5109,
62,
5532,
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62,
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361,
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25,
198,
220,
220,
220,
336,
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7,
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8,
198
] | 3.057851 | 121 |
# Django settings for openlets project.
import os
# Environment path should match settings/<module name>
ENVIRONMENT = os.environ.get('OPENLETS_ENV', 'dev')
if ENVIRONMENT == 'dev':
from .dev import *
elif ENVIRONMENT == 'stage':
from .stage import *
elif ENVIRONMENT == 'prod':
from .prod import *
else:
raise ImportError("Unknown environment: %s" % ENVIRONMENT)
# Absolute filesystem path to the directory that will hold user-uploaded files.
# Example: "/home/media/media.lawrence.com/media/"
MEDIA_ROOT = ''
# URL that handles the media served from MEDIA_ROOT. Make sure to use a
# trailing slash.
# Examples: "http://media.lawrence.com/media/", "http://example.com/media/"
MEDIA_URL = '/media/'
# Absolute path to the directory static files should be collected to.
# Don't put anything in this directory yourself; store your static files
# in apps' "static/" subdirectories and in STATICFILES_DIRS.
# Example: "/home/media/media.lawrence.com/static/"
STATIC_ROOT = os.path.join(PROJECT_PATH, 'www_root')
# URL prefix for static files.
# Example: "http://media.lawrence.com/static/"
STATIC_URL = '/m/'
# URL prefix for admin static files -- CSS, JavaScript and images.
# Make sure to use a trailing slash.
# Examples: "http://foo.com/static/admin/", "/static/admin/".
ADMIN_MEDIA_PREFIX = STATIC_URL + 'admin/'
# Additional locations of static files
STATICFILES_DIRS = (
)
# List of finder classes that know how to find static files in
# various locations.
STATICFILES_FINDERS = (
'django.contrib.staticfiles.finders.FileSystemFinder',
'django.contrib.staticfiles.finders.AppDirectoriesFinder',
)
# List of callables that know how to import templates from various sources.
TEMPLATE_LOADERS = (
'django.template.loaders.filesystem.Loader',
'django.template.loaders.app_directories.Loader',
)
MIDDLEWARE_CLASSES = (
'django.middleware.common.CommonMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
)
ROOT_URLCONF = 'openlets.urls'
TEMPLATE_DIRS = (
os.path.join(PROJECT_PATH, "openletsweb/templates"),
)
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.sites',
'django.contrib.messages',
'django.contrib.staticfiles',
'django.contrib.admin',
'django.contrib.admindocs',
'django.contrib.markup',
'openlets.core',
'openlets.openletsweb'
)
# Default post-login url
LOGIN_REDIRECT_URL = '/home'
# User Profile class
AUTH_PROFILE_MODULE = 'core.Person'
|
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] | 2.848812 | 926 |
"""The lightly.models package provides model implementations.
*Note that the high-level building blocks will be deprecated with
lightly version 1.2.0. Instead, use low-level building blocks to build the
models yourself.
Have a look at the benchmark code to see a reference implementation:*
`lightly benchmarks <https://github.com/lightly-ai/lightly/tree/master/docs/source/getting_started/benchmarks>`_
The package contains an implementation of the commonly used ResNet and
adaptations of the architecture which make self-supervised learning simpler.
The package also hosts the Lightly model zoo - a list of downloadable ResNet
checkpoints.
"""
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
from lightly.models.resnet import ResNetGenerator
from lightly.models.barlowtwins import BarlowTwins
from lightly.models.simclr import SimCLR
from lightly.models.simsiam import SimSiam
from lightly.models.byol import BYOL
from lightly.models.moco import MoCo
from lightly.models.nnclr import NNCLR
from lightly.models.zoo import ZOO
from lightly.models.zoo import checkpoints
from lightly.models import utils
|
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] | 3.841216 | 296 |
import os
def server_lcd(cmd, data):
"""Changes the local directory
Usage: lcd /dir
"""
pass
|
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from typing import Dict
class ImagePosition:
"""
The positions and rotations of the avatar and object for an image.
Positions are stored as (x, y, z) dictionaries, for example: `{"x": 0, "y": 0, "z": 0}`.
Rotations are stored as (x, y, z, w) dictionaries, for example: `{"x": 0, "y": 0, "z": 0, "w": 1}`.
"""
def __init__(self, avatar_position: Dict[str, float],
camera_rotation: Dict[str, float],
object_position: Dict[str, float],
object_rotation: Dict[str, float]):
"""
:param avatar_position: The position of the avatar.
:param camera_rotation: The rotation of the avatar.
:param object_position: The position of the object.
:param object_rotation: The rotation of the object.
"""
""":field
The position of the avatar.
"""
self.avatar_position: Dict[str, float] = avatar_position
""":field
The rotation of the avatar.
"""
self.camera_rotation: Dict[str, float] = camera_rotation
""":field
The position of the object.
"""
self.object_position: Dict[str, float] = object_position
""":field
The rotation of the object.
"""
self.object_rotation: Dict[str, float] = object_rotation
|
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341,
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] | 2.325217 | 575 |
import TestKit
from UnderGUI import *
from UnderGUI._Private import *
from OpenGL.GL import *
from OpenGL.GLU import *
from OpenGL.GLUT import *
################################################################################
WIDTH = 800
HEIGHT = 600
g = Global()
################################################################################
################################################################################
if __name__ == "__main__":
glutInit()
glutInitDisplayMode(GLUT_RGBA)
glutInitWindowSize(WIDTH, HEIGHT)
x = int((glutGet(GLUT_SCREEN_WIDTH) - WIDTH) / 2)
y = int((glutGet(GLUT_SCREEN_HEIGHT) - HEIGHT) / 2)
glutInitWindowPosition(x, y)
window = glutCreateWindow(b"OpenGL Window")
glutDisplayFunc(display)
glutIdleFunc(do_on_idle)
glutMouseFunc(do_on_mouse)
glutSetOption(GLUT_ACTION_ON_WINDOW_CLOSE, GLUT_ACTION_CONTINUE_EXECUTION)
create()
glutMainLoop()
destroy()
|
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