PEP: 258 Title: Docutils Design Specification Version: $Revision$
Last-Modified: $Date$ Author: David Goodger <goodger@python.org>
Discussions-To: doc-sig@python.org Status: Rejected Type: Standards
Track Content-Type: text/x-rst Requires: 256, 257 Created: 31-May-2001
Post-History: 13-Jun-2001

Rejection Notice

While this may serve as an interesting design document for the
now-independent docutils, it is no longer slated for inclusion in the
standard library.

Abstract

This PEP documents design issues and implementation details for
Docutils, a Python Docstring Processing System (DPS). The rationale and
high-level concepts of a DPS are documented in PEP 256, "Docstring
Processing System Framework". Also see PEP 256 for a "Road Map to the
Docstring PEPs".

Docutils is being designed modularly so that any of its components can
be replaced easily. In addition, Docutils is not limited to the
processing of Python docstrings; it processes standalone documents as
well, in several contexts.

No changes to the core Python language are required by this PEP. Its
deliverables consist of a package for the standard library and its
documentation.

Specification

Docutils Project Model

Project components and data flow:

    +---------------------------+
    |        Docutils:          |
    | docutils.core.Publisher,  |
    | docutils.core.publish_*() |
    +---------------------------+
     /            |            \
    /             |             \
    1,3,5   /        6     |              \ 7
    +--------+       +-------------+       +--------+
    | READER | ----> | TRANSFORMER | ====> | WRITER |
    +--------+       +-------------+       +--------+
    /     \\                                  |
    /       \\                                 |
    2    /      4  \\                             8  |
    +-------+   +--------+                        +--------+
    | INPUT |   | PARSER |                        | OUTPUT |
    +-------+   +--------+                        +--------+

The numbers above each component indicate the path a document's data
takes. Double-width lines between Reader & Parser and between
Transformer & Writer indicate that data sent along these paths should be
standard (pure & unextended) Docutils doc trees. Single-width lines
signify that internal tree extensions or completely unrelated
representations are possible, but they must be supported at both ends.

Publisher

The docutils.core module contains a "Publisher" facade class and several
convenience functions: "publish_cmdline()" (for command-line front
ends), "publish_file()" (for programmatic use with file-like I/O), and
"publish_string()" (for programmatic use with string I/O). The Publisher
class encapsulates the high-level logic of a Docutils system. The
Publisher class has overall responsibility for processing, controlled by
the Publisher.publish() method:

1.  Set up internal settings (may include config files & command-line
    options) and I/O objects.
2.  Call the Reader object to read data from the source Input object and
    parse the data with the Parser object. A document object is
    returned.
3.  Set up and apply transforms via the Transformer object attached to
    the document.
4.  Call the Writer object which translates the document to the final
    output format and writes the formatted data to the destination
    Output object. Depending on the Output object, the output may be
    returned from the Writer, and then from the publish() method.

Calling the "publish" function (or instantiating a "Publisher" object)
with component names will result in default behavior. For custom
behavior (customizing component settings), create custom component
objects first, and pass them to the Publisher or publish_* convenience
functions.

Readers

Readers understand the input context (where the data is coming from),
send the whole input or discrete "chunks" to the parser, and provide the
context to bind the chunks together back into a cohesive whole.

Each reader is a module or package exporting a "Reader" class with a
"read" method. The base "Reader" class can be found in the
docutils/readers/__init__.py module.

Most Readers will have to be told what parser to use. So far (see the
list of examples below), only the Python Source Reader ("PySource";
still incomplete) will be able to determine the parser on its own.

Responsibilities:

-   Get input text from the source I/O.
-   Pass the input text to the parser, along with a fresh document tree
    root.

Examples:

-   Standalone (Raw/Plain): Just read a text file and process it. The
    reader needs to be told which parser to use.

    The "Standalone Reader" has been implemented in module
    docutils.readers.standalone.

-   Python Source: See Python Source Reader below. This Reader is
    currently in development in the Docutils sandbox.

-   Email: 822 headers, quoted excerpts, signatures, MIME parts.

-   PEP: 822 headers, "PEP xxxx" and "RFC xxxx" conversion to URIs. The
    "PEP Reader" has been implemented in module docutils.readers.pep;
    see PEP 287 and PEP 12.

-   Wiki: Global reference lookups of "wiki links" incorporated into
    transforms. (CamelCase only or unrestricted?) Lazy indentation?

-   Web Page: As standalone, but recognize meta fields as meta tags.
    Support for templates of some sort? (After <body>, before </body>?)

-   FAQ: Structured "question & answer(s)" constructs.

-   Compound document: Merge chapters into a book. Master manifest file?

Parsers

Parsers analyze their input and produce a Docutils document tree. They
don't know or care anything about the source or destination of the data.

Each input parser is a module or package exporting a "Parser" class with
a "parse" method. The base "Parser" class can be found in the
docutils/parsers/__init__.py module.

Responsibilities: Given raw input text and a doctree root node, populate
the doctree by parsing the input text.

Example: The only parser implemented so far is for the reStructuredText
markup. It is implemented in the docutils/parsers/rst/ package.

The development and integration of other parsers is possible and
encouraged.

Transformer

The Transformer class, in docutils/transforms/__init__.py, stores
transforms and applies them to documents. A transformer object is
attached to every new document tree. The Publisher calls
Transformer.apply_transforms() to apply all stored transforms to the
document tree. Transforms change the document tree from one form to
another, add to the tree, or prune it. Transforms resolve references and
footnote numbers, process interpreted text, and do other
context-sensitive processing.

Some transforms are specific to components (Readers, Parser, Writers,
Input, Output). Standard component-specific transforms are specified in
the default_transforms attribute of component classes. After the Reader
has finished processing, the Publisher calls
Transformer.populate_from_components() with a list of components and all
default transforms are stored.

Each transform is a class in a module in the docutils/transforms/
package, a subclass of docutils.transforms.Transform. Transform classes
each have a default_priority attribute which is used by the Transformer
to apply transforms in order (low to high). The default priority can be
overridden when adding transforms to the Transformer object.

Transformer responsibilities:

-   Apply transforms to the document tree, in priority order.
-   Store a mapping of component type name ('reader', 'writer', etc.) to
    component objects. These are used by certain transforms (such as
    "components.Filter") to determine suitability.

Transform responsibilities:

-   Modify a doctree in-place, either purely transforming one structure
    into another, or adding new structures based on the doctree and/or
    external data.

Examples of transforms (in the docutils/transforms/ package):

-   frontmatter.DocInfo: Conversion of document metadata (bibliographic
    information).
-   references.AnonymousHyperlinks: Resolution of anonymous references
    to corresponding targets.
-   parts.Contents: Generates a table of contents for a document.
-   document.Merger: Combining multiple populated doctrees into one.
    (Not yet implemented or fully understood.)
-   document.Splitter: Splits a document into a tree-structure of
    subdocuments, perhaps by section. It will have to transform
    references appropriately. (Neither implemented not remotely
    understood.)
-   components.Filter: Includes or excludes elements which depend on a
    specific Docutils component.

Writers

Writers produce the final output (HTML, XML, TeX, etc.). Writers
translate the internal document tree structure into the final data
format, possibly running Writer-specific transforms first.

By the time the document gets to the Writer, it should be in final form.
The Writer's job is simply (and only) to translate from the Docutils
doctree structure to the target format. Some small transforms may be
required, but they should be local and format-specific.

Each writer is a module or package exporting a "Writer" class with a
"write" method. The base "Writer" class can be found in the
docutils/writers/__init__.py module.

Responsibilities:

-   Translate doctree(s) into specific output formats.
    -   Transform references into format-native forms.
-   Write the translated output to the destination I/O.

Examples:

-   XML: Various forms, such as:
    -   Docutils XML (an expression of the internal document tree,
        implemented as docutils.writers.docutils_xml).
    -   DocBook (being implemented in the Docutils sandbox).
-   HTML (XHTML implemented as docutils.writers.html4css1).
-   PDF (a ReportLabs interface is being developed in the Docutils
    sandbox).
-   TeX (a LaTeX Writer is being implemented in the sandbox).
-   Docutils-native pseudo-XML (implemented as
    docutils.writers.pseudoxml, used for testing).
-   Plain text
-   reStructuredText?

Input/Output

I/O classes provide a uniform API for low-level input and output.
Subclasses will exist for a variety of input/output mechanisms. However,
they can be considered an implementation detail. Most applications
should be satisfied using one of the convenience functions associated
with the Publisher.

I/O classes are currently in the preliminary stages; there's a lot of
work yet to be done. Issues:

-   How to represent multi-file input (files & directories) in the API?
-   How to represent multi-file output? Perhaps "Writer" variants, one
    for each output distribution type? Or Output objects with associated
    transforms?

Responsibilities:

-   Read data from the input source (Input objects) or write data to the
    output destination (Output objects).

Examples of input sources:

-   A single file on disk or a stream (implemented as
    docutils.io.FileInput).
-   Multiple files on disk (MultiFileInput?).
-   Python source files: modules and packages.
-   Python strings, as received from a client application (implemented
    as docutils.io.StringInput).

Examples of output destinations:

-   A single file on disk or a stream (implemented as
    docutils.io.FileOutput).
-   A tree of directories and files on disk.
-   A Python string, returned to a client application (implemented as
    docutils.io.StringOutput).
-   No output; useful for programmatic applications where only a portion
    of the normal output is to be used (implemented as
    docutils.io.NullOutput).
-   A single tree-shaped data structure in memory.
-   Some other set of data structures in memory.

Docutils Package Structure

-   Package "docutils".
    -   Module "__init__.py" contains: class "Component", a base class
        for Docutils components; class "SettingsSpec", a base class for
        specifying runtime settings (used by docutils.frontend); and
        class "TransformSpec", a base class for specifying transforms.

    -   Module "docutils.core" contains facade class "Publisher" and
        convenience functions. See Publisher above.

    -   Module "docutils.frontend" provides runtime settings support,
        for programmatic use and front-end tools (including
        configuration file support, and command-line argument and option
        processing).

    -   Module "docutils.io" provides a uniform API for low-level input
        and output. See Input/Output above.

    -   Module "docutils.nodes" contains the Docutils document tree
        element class library plus tree-traversal Visitor pattern base
        classes. See Document Tree below.

    -   Module "docutils.statemachine" contains a finite state machine
        specialized for regular-expression-based text filters and
        parsers. The reStructuredText parser implementation is based on
        this module.

    -   Module "docutils.urischemes" contains a mapping of known URI
        schemes ("http", "ftp", "mail", etc.).

    -   Module "docutils.utils" contains utility functions and classes,
        including a logger class ("Reporter"; see Error Handling below).

    -   Package "docutils.parsers": markup parsers.

        -   Function "get_parser_class(parser_name)" returns a parser
            module by name. Class "Parser" is the base class of specific
            parsers. (docutils/parsers/__init__.py)
        -   Package "docutils.parsers.rst": the reStructuredText parser.
        -   Alternate markup parsers may be added.

        See Parsers above.

    -   Package "docutils.readers": context-aware input readers.

        -   Function "get_reader_class(reader_name)" returns a reader
            module by name or alias. Class "Reader" is the base class of
            specific readers. (docutils/readers/__init__.py)
        -   Module "docutils.readers.standalone" reads independent
            document files.
        -   Module "docutils.readers.pep" reads PEPs (Python Enhancement
            Proposals).
        -   Readers to be added for: Python source code (structure &
            docstrings), email, FAQ, and perhaps Wiki and others.

        See Readers above.

    -   Package "docutils.writers": output format writers.

        -   Function "get_writer_class(writer_name)" returns a writer
            module by name. Class "Writer" is the base class of specific
            writers. (docutils/writers/__init__.py)
        -   Module "docutils.writers.html4css1" is a simple HyperText
            Markup Language document tree writer for HTML 4.01 and CSS1.
        -   Module "docutils.writers.docutils_xml" writes the internal
            document tree in XML form.
        -   Module "docutils.writers.pseudoxml" is a simple internal
            document tree writer; it writes indented pseudo-XML.
        -   Writers to be added: HTML 3.2 or 4.01-loose, XML (various
            forms, such as DocBook), PDF, TeX, plaintext,
            reStructuredText, and perhaps others.

        See Writers above.

    -   Package "docutils.transforms": tree transform classes.

        -   Class "Transformer" stores transforms and applies them to
            document trees. (docutils/transforms/__init__.py)
        -   Class "Transform" is the base class of specific transforms.
            (docutils/transforms/__init__.py)
        -   Each module contains related transform classes.

        See Transforms above.

    -   Package "docutils.languages": Language modules contain
        language-dependent strings and mappings. They are named for
        their language identifier (as defined in Choice of Docstring
        Format below), converting dashes to underscores.

        -   Function "get_language(language_code)", returns matching
            language module. (docutils/languages/__init__.py)
        -   Modules: en.py (English), de.py (German), fr.py (French),
            it.py (Italian), sk.py (Slovak), sv.py (Swedish).
        -   Other languages to be added.
-   Third-party modules: "extras" directory. These modules are installed
    only if they're not already present in the Python installation.
    -   extras/optparse.py and extras/textwrap.py provide option parsing
        and command-line help; from Greg Ward's http://optik.sf.net/
        project, included for convenience.
    -   extras/roman.py contains Roman numeral conversion routines.

Front-End Tools

The tools/ directory contains several front ends for common Docutils
processing. See Docutils Front-End Tools for details.

Document Tree

A single intermediate data structure is used internally by Docutils, in
the interfaces between components; it is defined in the docutils.nodes
module. It is not required that this data structure be used internally
by any of the components, just between components as outlined in the
diagram in the Docutils Project Model above.

Custom node types are allowed, provided that either (a) a transform
converts them to standard Docutils nodes before they reach the Writer
proper, or (b) the custom node is explicitly supported by certain
Writers, and is wrapped in a filtered "pending" node. An example of
condition (a) is the Python Source Reader (see below), where a "stylist"
transform converts custom nodes. The HTML <meta> tag is an example of
condition (b); it is supported by the HTML Writer but not by others. The
reStructuredText "meta" directive creates a "pending" node, which
contains knowledge that the embedded "meta" node can only be handled by
HTML-compatible writers. The "pending" node is resolved by the
docutils.transforms.components.Filter transform, which checks that the
calling writer supports HTML; if it doesn't, the "pending" node (and
enclosed "meta" node) is removed from the document.

The document tree data structure is similar to a DOM tree, but with
specific node names (classes) instead of DOM's generic nodes. The schema
is documented in an XML DTD (eXtensible Markup Language Document Type
Definition), which comes in two parts:

-   the Docutils Generic DTD, docutils.dtd, and
-   the OASIS Exchange Table Model, soextbl.dtd.

The DTD defines a rich set of elements, suitable for many input and
output formats. The DTD retains all information necessary to reconstruct
the original input text, or a reasonable facsimile thereof.

See The Docutils Document Tree for details (incomplete).

Error Handling

When the parser encounters an error in markup, it inserts a system
message (DTD element "system_message"). There are five levels of system
messages:

-   Level-0, "DEBUG": an internal reporting issue. There is no effect on
    the processing. Level-0 system messages are handled separately from
    the others.
-   Level-1, "INFO": a minor issue that can be ignored. There is little
    or no effect on the processing. Typically level-1 system messages
    are not reported.
-   Level-2, "WARNING": an issue that should be addressed. If ignored,
    there may be minor problems with the output. Typically level-2
    system messages are reported but do not halt processing
-   Level-3, "ERROR": a major issue that should be addressed. If
    ignored, the output will contain unpredictable errors. Typically
    level-3 system messages are reported but do not halt processing
-   Level-4, "SEVERE": a critical error that must be addressed.
    Typically level-4 system messages are turned into exceptions which
    halt processing. If ignored, the output will contain severe errors.

Although the initial message levels were devised independently, they
have a strong correspondence to VMS error condition severity levels; the
names in quotes for levels 1 through 4 were borrowed from VMS. Error
handling has since been influenced by the log4j project.

Python Source Reader

The Python Source Reader ("PySource") is the Docutils component that
reads Python source files, extracts docstrings in context, then parses,
links, and assembles the docstrings into a cohesive whole. It is a major
and non-trivial component, currently under experimental development in
the Docutils sandbox. High-level design issues are presented here.

Processing Model

This model will evolve over time, incorporating experience and
discoveries.

1.  The PySource Reader uses an Input class to read in Python packages
    and modules, into a tree of strings.
2.  The Python modules are parsed, converting the tree of strings into a
    tree of abstract syntax trees with docstring nodes.
3.  The abstract syntax trees are converted into an internal
    representation of the packages/modules. Docstrings are extracted, as
    well as code structure details. See AST Mining below. Namespaces are
    constructed for lookup in step 6.
4.  One at a time, the docstrings are parsed, producing standard
    Docutils doctrees.
5.  PySource assembles all the individual docstrings' doctrees into a
    Python-specific custom Docutils tree paralleling the
    package/module/class structure; this is a custom Reader-specific
    internal representation (see the Docutils Python Source DTD).
    Namespaces must be merged: Python identifiers, hyperlink targets.
6.  Cross-references from docstrings (interpreted text) to Python
    identifiers are resolved according to the Python namespace lookup
    rules. See Identifier Cross-References below.
7.  A "Stylist" transform is applied to the custom doctree (by the
    Transformer), custom nodes are rendered using standard nodes as
    primitives, and a standard document tree is emitted. See Stylist
    Transforms below.
8.  Other transforms are applied to the standard doctree by the
    Transformer.
9.  The standard doctree is sent to a Writer, which translates the
    document into a concrete format (HTML, PDF, etc.).
10. The Writer uses an Output class to write the resulting data to its
    destination (disk file, directories and files, etc.).

AST Mining

Abstract Syntax Tree mining code will be written (or adapted) that scans
a parsed Python module, and returns an ordered tree containing the
names, docstrings (including attribute and additional docstrings; see
below), and additional info (in parentheses below) of all of the
following objects:

-   packages
-   modules
-   module attributes (+ initial values)
-   classes (+ inheritance)
-   class attributes (+ initial values)
-   instance attributes (+ initial values)
-   methods (+ parameters & defaults)
-   functions (+ parameters & defaults)

(Extract comments too? For example, comments at the start of a module
would be a good place for bibliographic field lists.)

In order to evaluate interpreted text cross-references, namespaces for
each of the above will also be required.

See the python-dev/docstring-develop thread "AST mining", started on
2001-08-14.

Docstring Extraction Rules

1.  What to examine:

    a)  If the "__all__" variable is present in the module being
        documented, only identifiers listed in "__all__" are examined
        for docstrings.
    b)  In the absence of "__all__", all identifiers are examined,
        except those whose names are private (names begin with "_" but
        don't begin and end with "__").
    c)  1a and 1b can be overridden by runtime settings.

2.  Where:

    Docstrings are string literal expressions, and are recognized in the
    following places within Python modules:

    a)  At the beginning of a module, function definition, class
        definition, or method definition, after any comments. This is
        the standard for Python __doc__ attributes.
    b)  Immediately following a simple assignment at the top level of a
        module, class definition, or __init__ method definition, after
        any comments. See Attribute Docstrings below.
    c)  Additional string literals found immediately after the
        docstrings in (a) and (b) will be recognized, extracted, and
        concatenated. See Additional Docstrings below.
    d)  @@@ 2.2-style "properties" with attribute docstrings? Wait for
        syntax?

3.  How:

    Whenever possible, Python modules should be parsed by Docutils, not
    imported. There are several reasons:

    -   Importing untrusted code is inherently insecure.
    -   Information from the source is lost when using introspection to
        examine an imported module, such as comments and the order of
        definitions.
    -   Docstrings are to be recognized in places where the byte-code
        compiler ignores string literal expressions (2b and 2c above),
        meaning importing the module will lose these docstrings.

    Of course, standard Python parsing tools such as the "parser"
    library module should be used.

    When the Python source code for a module is not available (i.e. only
    the .pyc file exists) or for C extension modules, to access
    docstrings the module can only be imported, and any limitations must
    be lived with.

Since attribute docstrings and additional docstrings are ignored by the
Python byte-code compiler, no namespace pollution or runtime bloat will
result from their use. They are not assigned to __doc__ or to any other
attribute. The initial parsing of a module may take a slight performance
hit.

Attribute Docstrings

(This is a simplified version of PEP 224.)

A string literal immediately following an assignment statement is
interpreted by the docstring extraction machinery as the docstring of
the target of the assignment statement, under the following conditions:

1.  The assignment must be in one of the following contexts:

    a)  At the top level of a module (i.e., not nested inside a compound
        statement such as a loop or conditional): a module attribute.
    b)  At the top level of a class definition: a class attribute.
    c)  At the top level of the "__init__" method definition of a class:
        an instance attribute. Instance attributes assigned in other
        methods are assumed to be implementation details. (@@@ __new__
        methods?)
    d)  A function attribute assignment at the top level of a module or
        class definition.

    Since each of the above contexts are at the top level (i.e., in the
    outermost suite of a definition), it may be necessary to place dummy
    assignments for attributes assigned conditionally or in a loop.

2.  The assignment must be to a single target, not to a list or a tuple
    of targets.

3.  The form of the target:

    a)  For contexts 1a and 1b above, the target must be a simple
        identifier (not a dotted identifier, a subscripted expression,
        or a sliced expression).
    b)  For context 1c above, the target must be of the form
        "self.attrib", where "self" matches the "__init__" method's
        first parameter (the instance parameter) and "attrib" is a
        simple identifier as in 3a.
    c)  For context 1d above, the target must be of the form
        "name.attrib", where "name" matches an already-defined function
        or method name and "attrib" is a simple identifier as in 3a.

Blank lines may be used after attribute docstrings to emphasize the
connection between the assignment and the docstring.

Examples:

    g = 'module attribute (module-global variable)'
    """This is g's docstring."""

    class AClass:

        c = 'class attribute'
        """This is AClass.c's docstring."""

        def __init__(self):
            """Method __init__'s docstring."""

            self.i = 'instance attribute'
            """This is self.i's docstring."""

    def f(x):
        """Function f's docstring."""
        return x**2

    f.a = 1
    """Function attribute f.a's docstring."""

Additional Docstrings

(This idea was adapted from PEP 216.)

Many programmers would like to make extensive use of docstrings for API
documentation. However, docstrings do take up space in the running
program, so some programmers are reluctant to "bloat up" their code.
Also, not all API documentation is applicable to interactive
environments, where __doc__ would be displayed.

Docutils' docstring extraction tools will concatenate all string literal
expressions which appear at the beginning of a definition or after a
simple assignment. Only the first strings in definitions will be
available as __doc__, and can be used for brief usage text suitable for
interactive sessions; subsequent string literals and all attribute
docstrings are ignored by the Python byte-code compiler and may contain
more extensive API information.

Example:

    def function(arg):
        """This is __doc__, function's docstring."""
        """
        This is an additional docstring, ignored by the byte-code
        compiler, but extracted by Docutils.
        """
        pass

Issue: from __future__ import

This would break "from __future__ import" statements introduced in
Python 2.1 for multiple module docstrings (main docstring plus
additional docstring(s)). The Python Reference Manual specifies:

  A future statement must appear near the top of the module. The only
  lines that can appear before a future statement are:

  -   the module docstring (if any),
  -   comments,
  -   blank lines, and
  -   other future statements.

Resolution?

1.  Should we search for docstrings after a __future__ statement? Very
    ugly.
2.  Redefine __future__ statements to allow multiple preceding string
    literals?
3.  Or should we not even worry about this? There probably shouldn't be
    __future__ statements in production code, after all. Perhaps modules
    with __future__ statements will simply have to put up with the
    single-docstring limitation.

Choice of Docstring Format

Rather than force everyone to use a single docstring format, multiple
input formats are allowed by the processing system. A special variable,
__docformat__, may appear at the top level of a module before any
function or class definitions. Over time or through decree, a standard
format or set of formats should emerge.

A module's __docformat__ variable only applies to the objects defined in
the module's file. In particular, the __docformat__ variable in a
package's __init__.py file does not apply to objects defined in
subpackages and submodules.

The __docformat__ variable is a string containing the name of the format
being used, a case-insensitive string matching the input parser's module
or package name (i.e., the same name as required to "import" the module
or package), or a registered alias. If no __docformat__ is specified,
the default format is "plaintext" for now; this may be changed to the
standard format if one is ever established.

The __docformat__ string may contain an optional second field, separated
from the format name (first field) by a single space: a case-insensitive
language identifier as defined in 1766. A typical language identifier
consists of a 2-letter language code from ISO 639 (3-letter codes used
only if no 2-letter code exists; 1766 is currently being revised to
allow 3-letter codes). If no language identifier is specified, the
default is "en" for English. The language identifier is passed to the
parser and can be used for language-dependent markup features.

Identifier Cross-References

In Python docstrings, interpreted text is used to classify and mark up
program identifiers, such as the names of variables, functions, classes,
and modules. If the identifier alone is given, its role is inferred
implicitly according to the Python namespace lookup rules. For functions
and methods (even when dynamically assigned), parentheses ('()') may be
included:

    This function uses `another()` to do its work.

For class, instance and module attributes, dotted identifiers are used
when necessary. For example (using reStructuredText markup):

    class Keeper(Storer):

        """
        Extend `Storer`.  Class attribute `instances` keeps track
        of the number of `Keeper` objects instantiated.
        """

        instances = 0
        """How many `Keeper` objects are there?"""

        def __init__(self):
            """
            Extend `Storer.__init__()` to keep track of instances.

            Keep count in `Keeper.instances`, data in `self.data`.
            """
            Storer.__init__(self)
            Keeper.instances += 1

            self.data = []
            """Store data in a list, most recent last."""

        def store_data(self, data):
            """
            Extend `Storer.store_data()`; append new `data` to a
            list (in `self.data`).
            """
            self.data = data

Each of the identifiers quoted with backquotes ("`") will become
references to the definitions of the identifiers themselves.

Stylist Transforms

Stylist transforms are specialized transforms specific to the PySource
Reader. The PySource Reader doesn't have to make any decisions as to
style; it just produces a logically constructed document tree, parsed
and linked, including custom node types. Stylist transforms understand
the custom nodes created by the Reader and convert them into standard
Docutils nodes.

Multiple Stylist transforms may be implemented and one can be chosen at
runtime (through a "--style" or "--stylist" command-line option). Each
Stylist transform implements a different layout or style; thus the name.
They decouple the context-understanding part of the Reader from the
layout-generating part of processing, resulting in a more flexible and
robust system. This also serves to "separate style from content", the
SGML/XML ideal.

By keeping the piece of code that does the styling small and modular, it
becomes much easier for people to roll their own styles. The "barrier to
entry" is too high with existing tools; extracting the stylist code will
lower the barrier considerably.

References and Footnotes

Project Web Site

A SourceForge project has been set up for this work at
http://docutils.sourceforge.net/.

Copyright

This document has been placed in the public domain.

Acknowledgements

This document borrows ideas from the archives of the Python Doc-SIG.
Thanks to all members past & present.



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