import datetime
import os
import shutil
import subprocess
import urllib.request
from contextlib import closing

import numpy as np
import pandas as pd
import requests

import wbml.out

__all__ = [
    "DependencyError",
    "resource",
    "dependency",
    "asserted_dependency",
    "split_df",
    "data_path",
    "date_to_decimal_year",
]


class DependencyError(AssertionError):
    """Exception raised in case of an erroneous dependency."""


def resource(target, url, post=False, **kw_args):
    """Specify a dependency on an online resource.

    Further takes in keyword arguments that are passed to the appropriate method
    from :mod:`requests` or :mod:`urllib`.

    Args:
        target (str): Target file.
        url (str): Source URL.
        post (bool, optional): Make a POST request instead of a GET request.
            Only applicable if the URL starts with "http" or "https". Defaults
            to `False`.
    """
    if not os.path.exists(target):
        with wbml.out.Section("Downloading file"):
            wbml.out.kv("Source", url)
            wbml.out.kv("Target", target)

            # Ensure that all directories in the path exist.
            make_dirs(target)

            # If the URL starts with "ftp", use the :mod:`urllib` library.
            if url.startswith("ftp"):
                with closing(urllib.request.urlopen(url, **kw_args)) as r:
                    with open(target, "wb") as f:
                        shutil.copyfileobj(r, f)

            # By default, use the :mod:`requests` library.
            else:
                request = requests.post if post else requests.get
                with request(url, stream=True, **kw_args) as r:
                    with open(target, "wb") as f:
                        shutil.copyfileobj(r.raw, f)


def dependency(target, source, commands):
    """Specify a dependency that is generated from an existing file.

    Args:
        target (str): Target file.
        source (str): Source file.
        commands (list[str]): List of commands to generate target file.
    """
    if not os.path.exists(target):
        with wbml.out.Section("Generating file"):
            wbml.out.kv("Source", source)
            wbml.out.kv("Target", target)

            # Check that the source exists.
            if not os.path.exists(source):
                raise DependencyError(
                    f'Source "{source}" asserted to exist, but it does not.'
                )

            # Save current working directory.
            current_wd = os.getcwd()

            # Ensure that all directories in the path exist.
            make_dirs(target)

            # Perform commands.
            for command in commands:
                wbml.out.out(command)

                # Change working directory to directory of target file, run
                # command, and restore working directory afterwards.
                os.chdir(os.path.dirname(target))
                subprocess.call(command, shell=True)
                os.chdir(current_wd)


def asserted_dependency(target):
    """Specify a dependency that cannot be fetched.

    Args:
        target (str): Target file.
    """
    if not os.path.exists(target):
        raise DependencyError(
            f'Dependency "{target}" is asserted to exist, '
            f"but it does not, and it cannot be "
            f"automatically fetched. Please put the file "
            f"into place manually."
        )


def make_dirs(path):
    """Make the directories in the path of a file.

    Args:
        path (url): Path of a file.
    """
    os.makedirs(os.path.dirname(path), exist_ok=True)


def data_path(*xs):
    """Get the path of a data file.

    Args:
        *xs (str): Parts of the path.

    Returns:
        str: Absolute path.
    """
    return os.path.abspath(
        os.path.join(os.path.dirname(__file__), os.pardir, os.pardir, "data", *xs)
    )


def split_df(df, index_range, columns, iloc=False):
    """Split a data frame by selecting from columns a particular range.

    Args:
        df (:class:`pd.DataFrame`): Data frame to split.
        index_range (tuple): Tuple containing lower and upper limit of the
            range to split the index by. If `index_range = (a, b)`, then
            `[a, b)` is taken.
        columns (list[object]): Columns to select.
        iloc (bool, optional): The index range is the integer location instead
            of the index value. Defaults to `False`.

    Returns:
        tuple[:class:`pd.DataFrame`]: Selected rows from selected columns
            and the remainder.
    """
    if iloc:
        inds = np.arange(df.shape[0])
        rows = (inds >= index_range[0]) & (inds < index_range[1])
    else:
        rows = (df.index >= index_range[0]) & (df.index < index_range[1])
    selected = pd.DataFrame([df[name][rows] for name in columns]).T
    remainder = pd.DataFrame(
        [df[name][~rows] for name in columns]
        + [df[name] for name in set(df.columns) - set(columns)]
    ).T

    # Fix order of columns.
    selected_inds = [i for i, c in enumerate(df.columns) if c in columns]
    selected = selected.reindex(df.columns[np.array(selected_inds)], axis=1)
    remainder = remainder.reindex(df.columns, axis=1)

    return selected, remainder


def date_to_decimal_year(date, format=None):
    """Convert a date to decimal year.

    Args:
        date (str): Date as a string.
        format (str, optional): Format of the date if a conversion is needed.

    Returns:
        float: Decimal year corresponding to the date.
    """
    if format:
        date = datetime.datetime.strptime(date, format)
    start = datetime.date(date.year, 1, 1).toordinal()
    year_length = datetime.date(date.year + 1, 1, 1).toordinal() - start

    # Account for subday time.
    subday_time = 0
    if hasattr(date, "hour"):
        subday_time += date.hour / year_length / 24
    if hasattr(date, "minute"):
        subday_time += date.minute / year_length / 24 / 60
    if hasattr(date, "second"):
        subday_time += date.second / year_length / 24 / 60 / 60

    return date.year + float(date.toordinal() - start) / year_length + subday_time

numpy.array numpy.arange