Current File : //proc/self/root/opt/imunify360/venv/lib/python3.11/site-packages/PyYAML-6.0.1.dist-info/METADATA
Metadata-Version: 2.1
Name: PyYAML
Version: 6.0.1
Summary: YAML parser and emitter for Python
Home-page: https://pyyaml.org/
Download-URL: https://pypi.org/project/PyYAML/
Author: Kirill Simonov
Author-email: xi@resolvent.net
License: MIT
Project-URL: Bug Tracker, https://github.com/yaml/pyyaml/issues
Project-URL: CI, https://github.com/yaml/pyyaml/actions
Project-URL: Documentation, https://pyyaml.org/wiki/PyYAMLDocumentation
Project-URL: Mailing lists, http://lists.sourceforge.net/lists/listinfo/yaml-core
Project-URL: Source Code, https://github.com/yaml/pyyaml
Platform: Any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Text Processing :: Markup
Requires-Python: >=3.6
License-File: LICENSE
YAML is a data serialization format designed for human readability
and interaction with scripting languages. PyYAML is a YAML parser
and emitter for Python.
PyYAML features a complete YAML 1.1 parser, Unicode support, pickle
support, capable extension API, and sensible error messages. PyYAML
supports standard YAML tags and provides Python-specific tags that
allow to represent an arbitrary Python object.
PyYAML is applicable for a broad range of tasks from complex
configuration files to object serialization and persistence.
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