Metadata-Version: 2.1
Name: pyaml
Version: 23.7.0
Summary: PyYAML-based module to produce a bit more pretty and readable YAML-serialized data
Home-page: https://github.com/mk-fg/pretty-yaml
Author: Mike Kazantsev
Author-email: Mike Kazantsev <mk.fraggod@gmail.com>
License: WTFPL
Project-URL: Homepage, https://github.com/mk-fg/pretty-yaml
Keywords: yaml,serialization,pretty-print,formatter,human,readability
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: Public Domain
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
Provides-Extra: anchors
License-File: COPYING

pretty-yaml (or pyaml)
======================

PyYAML_-based python module to produce a bit more pretty and human-readable YAML-serialized data.

This module is for serialization only, see `ruamel.yaml`_ module for literate
YAML parsing (keeping track of comments, spacing, line/column numbers of values, etc).

(side-note: to dump stuff parsed by ruamel.yaml with this module, use only ``YAML(typ='safe')`` there)

It's a small module, and for projects that only need part of its functionality,
I'd recommend copy-pasting that in, instead of adding janky dependency.

.. _PyYAML: http://pyyaml.org/
.. _ruamel.yaml: https://bitbucket.org/ruamel/yaml/

.. contents::
  :backlinks: none

Repository URLs:

- https://github.com/mk-fg/pretty-yaml
- https://codeberg.org/mk-fg/pretty-yaml
- https://fraggod.net/code/git/pretty-yaml


Warning
-------

Prime goal of this module is to produce human-readable output that can be
easily diff'ed, manipulated and re-used, but maybe with occasional issues.

So please do not rely on the thing to produce output that can always be
deserialized exactly to what was exported, at least - use PyYAML directly
for that (but maybe with options from the next section).


What this module does and why
-----------------------------

YAML is generally nice and easy format to read *if* it was written by humans.

PyYAML can a do fairly decent job of making stuff readable, and the best
combination of parameters for such output that I've seen so far is probably this one::

  >>> m = [123, 45.67, {1: None, 2: False}, 'some text']
  >>> data = dict(a='asldnsa\nasldpáknsa\n', b='whatever text', ma=m, mb=m)
  >>> yaml.safe_dump(data, sys.stdout, allow_unicode=True, default_flow_style=False)
  a: 'asldnsa

    asldpáknsa

    '
  b: whatever text
  ma: &id001
  - 123
  - 45.67
  - 1: null
    2: false
  - some text
  mb: *id001

pyaml (this module) tries to improve on that a bit, with the following tweaks:

* Most human-friendly representation options in PyYAML (that I know of)
  are used as defaults.

* Dump "null" values as empty values, if possible, which have the same meaning
  but reduce visual clutter and are easier to edit.

* Dicts, sets, OrderedDicts, defaultdicts, namedtuples, enums, dataclasses, etc
  are represented as their safe YAML-compatible base (like int, list or mapping),
  with mappings key-sorted by default for more diff-friendly output.

* Use shorter and simplier yes/no for booleans.

* List items get indented, as they should be.

* Attempt is made to pick more readable string representation styles, depending
  on the value, e.g.::

    >>> yaml.safe_dump(cert, sys.stdout)
    cert: '-----BEGIN CERTIFICATE-----

      MIIH3jCCBcagAwIBAgIJAJi7AjQ4Z87OMA0GCSqGSIb3DQEBCwUAMIHBMRcwFQYD

      VQQKFA52YWxlcm9uLm5vX2lzcDEeMBwGA1UECxMVQ2VydGlmaWNhdGUgQXV0aG9y
    ...

    >>> pyaml.p(cert):
    cert: |
      -----BEGIN CERTIFICATE-----
      MIIH3jCCBcagAwIBAgIJAJi7AjQ4Z87OMA0GCSqGSIb3DQEBCwUAMIHBMRcwFQYD
      VQQKFA52YWxlcm9uLm5vX2lzcDEeMBwGA1UECxMVQ2VydGlmaWNhdGUgQXV0aG9y
    ...

* "force_embed" option (default=yes) to avoid having &id stuff scattered all
  over the output. Might be more useful to disable it in some specific cases though.

* "&id" anchors, if used, get labels from the keys they get attached to,
  not just meaningless enumerators.

* "string_val_style" option to only apply to strings that are values, not keys,
  i.e::

    >>> pyaml.p(data, string_val_style='"')
    key: "value\nasldpáknsa\n"
    >>> yaml.safe_dump(data, sys.stdout, allow_unicode=True, default_style='"')
    "key": "value\nasldpáknsa\n"

* Add vertical spacing (empty lines) between keys on different depths,
  to separate long YAML sections in the output visually, make it more seekable.

* Discard end-of-document "..." indicators for simple values.

Result for the (rather meaningless) example above::

  >>> pyaml.p(data, force_embed=False, vspacing=dict(split_lines=10))

  a: |
    asldnsa
    asldpáknsa

  b: whatever text

  ma: &ma
    - 123
    - 45.67
    - 1:
      2: no
    - some text

  mb: *ma

(force_embed=False enabled deduplication with ``&ma`` anchor,
vspacing is adjusted to split even this tiny output)

----------

Extended example::

  >>> pyaml.dump(data, vspacing=dict(split_lines=10))

  destination:

    encoding:
      xz:
        enabled: yes
        min_size: 5120
        options:
        path_filter:
          - \.(gz|bz2|t[gb]z2?|xz|lzma|7z|zip|rar)$
          - \.(rpm|deb|iso)$
          - \.(jpe?g|gif|png|mov|avi|ogg|mkv|webm|mp[34g]|flv|flac|ape|pdf|djvu)$
          - \.(sqlite3?|fossil|fsl)$
          - \.git/objects/[0-9a-f]+/[0-9a-f]+$

    result:
      append_to_file:
      append_to_lafs_dir:
      print_to_stdout: yes

    url: http://localhost:3456/uri

  filter:
    - /(CVS|RCS|SCCS|_darcs|\{arch\})/$
    - /\.(git|hg|bzr|svn|cvs)(/|ignore|attributes|tags)?$
    - /=(RELEASE-ID|meta-update|update)$

  http:
    ca_certs_files: /etc/ssl/certs/ca-certificates.crt
    debug_requests: no
    request_pool_options:
      cachedConnectionTimeout: 600
      maxPersistentPerHost: 10
      retryAutomatically: yes

  logging:

    formatters:
      basic:
        datefmt: '%Y-%m-%d %H:%M:%S'
        format: '%(asctime)s :: %(name)s :: %(levelname)s: %(message)s'

    handlers:
      console:
        class: logging.StreamHandler
        formatter: basic
        level: custom
        stream: ext://sys.stderr

    loggers:
      twisted:
        handlers:
          - console
        level: 0

    root:
      handlers:
        - console
      level: custom

Note that unless there are many moderately wide and deep trees of data,
which are expected to be read and edited by people, it might be preferrable
to directly use PyYAML regardless, as it won't introduce another
(rather pointless in that case) dependency and a point of failure.


Some Tricks
-----------

* Pretty-print any yaml or json (yaml subset) file from the shell::

    % python -m pyaml /path/to/some/file.yaml
    % curl -s https://www.githubstatus.com/api/v2/summary.json | python -m pyaml

* Process and replace json/yaml file in-place::

    % python -m pyaml -r file-with-json.data

* Easier "debug printf" for more complex data (all funcs below are aliases to same thing)::

    pyaml.p(stuff)
    pyaml.pprint(my_data)
    pyaml.pprint('----- HOW DOES THAT BREAKS!?!?', input_data, some_var, more_stuff)
    pyaml.print(data, file=sys.stderr) # needs "from __future__ import print_function"

* Force all string values to a certain style (see info on these in `PyYAML docs`_)::

    pyaml.dump(many_weird_strings, string_val_style='|')
    pyaml.dump(multiline_words, string_val_style='>')
    pyaml.dump(no_want_quotes, string_val_style='plain')

  Using ``pyaml.add_representer()`` (note \*p\*yaml) as suggested in
  `this SO thread`_ (or `github-issue-7`_) should also work.

* Control indent and width of the results::

    pyaml.dump(wide_and_deep, indent=4, width=120)

  These are actually keywords for PyYAML Emitter (passed to it from Dumper),
  see more info on these in `PyYAML docs`_.

* Dump multiple yaml documents into a file: ``pyaml.dump_all([data1, data2, data3], dst_file)``

  explicit_start=True is implied, unless explicit_start=False is passed.

.. _PyYAML docs: http://pyyaml.org/wiki/PyYAMLDocumentation#Scalars
.. _this SO thread: http://stackoverflow.com/a/7445560
.. _github-issue-7: https://github.com/mk-fg/pretty-yaml/issues/7


Installation
------------

It's a regular Python 3.8+ module/package, published on PyPI (as pyaml_).

Module uses PyYAML_ for processing of the actual YAML files
and should pull it in as a dependency.

Dependency on unidecode_ module is optional and should only be necessary
with force_embed=False keyword, and same-id objects or recursion is used
within serialized data.

Using pip_ is how you generally install it, usually coupled with venv_ usage
(which will also provide "pip" tool itself)::

  % pip install pyaml

Current-git version can be installed like this::

  % pip install git+https://github.com/mk-fg/pretty-yaml

pip will default to installing into currently-active venv, then user's home
directory (under ``~/.local/lib/python...``), and maybe system-wide when running
as root (only useful in specialized environments like docker containers).

There are many other python packaging tools - pipenv_, poetry_, pdm_, etc -
use whatever is most suitable for specific project/environment.

More general info on python packaging can be found at `packaging.python.org`_.

When changing code, unit tests can be run with ``python -m unittest discover``
from the local repository checkout.

.. _pyaml: https://pypi.org/project/pyaml/
.. _unidecode: https://pypi.python.org/pypi/Unidecode
.. _pip: https://pip.pypa.io/en/stable/
.. _venv: https://docs.python.org/3/library/venv.html
.. _poetry: https://python-poetry.org/
.. _pipenv: https://pipenv.pypa.io/
.. _pdm: https://pdm.fming.dev/
.. _packaging.python.org: https://packaging.python.org/installing/
