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"name": "py-json5",
"description": "A Python implementation of the JSON5 data format"
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{
"name": "py-jsonlines",
"description": "jsonlines is a Python library to simplify working with jsonlines and ndjson data."
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{
"name": "py-jsonpatch",
"description": "Apply JSON-Patches (RFC 6902)"
},
{
"name": "py-jsonpath-rw",
"description": "A robust and significantly extended implementation of JSONPath for Python, with a clear AST for metaprogramming."
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{
"name": "py-jsonpickle",
"description": "Python library for serializing any arbitrary object graph into JSON."
},
{
"name": "py-jsonpointer",
"description": "Identify specific nodes in a JSON document (RFC 6901)"
},
{
"name": "py-jsonschema",
"description": "An implementation of JSON Schema validation for Python."
},
{
"name": "py-jsonschema-specifications",
"description": "JSON support files from the JSON Schema Specifications"
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{
"name": "py-jubatus-client",
"description": "a Python client for jubatus, a highly distributed online machine learning system"
},
{
"name": "py-jug",
"description": "A Task Based Parallelization Framework"
},
{
"name": "py-julius",
"description": "Digital Signal Processing algorithms in PyTorch"
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{
"name": "py-junit-xml",
"description": "Creates JUnit XML test result documents that can be read by tools such as Jenkins"
},
{
"name": "py-jupyter",
"description": "Web application for interactive data science and scientific computing."
},
{
"name": "py-jupyter-lsp",
"description": "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server."
},
{
"name": "py-jupyter_client",
"description": "Jupyter protocol implementation and client libraries."
},
{
"name": "py-jupyter_console",
"description": "Jupyter terminal console."
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{
"name": "py-jupyter_core",
"description": "Jupyter core package."
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{
"name": "py-jupyter_events",
"description": "Jupyter Event System library."
},
{
"name": "py-jupyter_packaging",
"description": "Utilities for making Python packages with and without accompanying JavaScript packages."
},
{
"name": "py-jupyter_server",
"description": "The Jupyter Server provides the backend for Jupyter web applications."
},
{
"name": "py-jupyter_server_terminals",
"description": "A Jupyter Server Extension Providing Terminals."
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{
"name": "py-jupyter_sphinx",
"description": "Jupyter Sphinx Extensions"
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{
"name": "py-jupyterlab",
"description": "Next-generation web-based notebook environment for interactive computing."
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{
"name": "py-jupyterlab_pygments",
"description": "JupyterLab Pygments Theme"
},
{
"name": "py-jupyterlab_server",
"description": "This package is used to launch an application built using JupyterLab."
},
{
"name": "py-jupyterlab_widgets",
"description": "Jupyter interactive widgets for JupyterLab"
},
{
"name": "py-jupyterthemes",
"description": "Select and install a Jupyter notebook theme"
},
{
"name": "py-jupytext",
"description": "Jupyter Notebooks as Markdown Documents, Julia, Python or R Scripts"
},
{
"name": "py-jwt",
"description": "JSON Web Token implementation in Python"
},
{
"name": "py-kaitaistruct",
"description": "Kaitai Struct declarative parser generator for binary data runtime library for Python"
},
{
"name": "py-kaptan",
"description": "Configuration parser."
},
{
"name": "py-kapteyn",
"description": "The Kapteyn Package"
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{
"name": "py-kcs11",
"description": "PKCS11 wrapper for Python"
},
{
"name": "py-keep",
"description": "A Meta CLI toolkit"
},
{
"name": "py-keras",
"description": "Deep Learning library for Theano and TensorFlow"
},
{
"name": "py-keras2onnx",
"description": "Converts Machine Learning models to ONNX for use in Windows ML"
},
{
"name": "py-keras_applications",
"description": "Keras Applications is the applications module of the Keras deep learning library."
},
{
"name": "py-keras_preprocessing",
"description": "Keras Preprocessing is the data preprocessing and data augmentation module of the Keras deep learning library."
},
{
"name": "py-kerfi-vangasvipur",
"description": "Python tool to manipulate OS X system_profiler output."
},
{
"name": "py-keyring",
"description": "Python interface to access the system keyring service"
},
{
"name": "py-keyrings.alt",
"description": "Alternate keyring backend implementations for use with the keyring package"
},
{
"name": "py-keystoneauth1",
"description": "Tools for authenticating to an OpenStack-based cloud"
},
{
"name": "py-keystoneclient",
"description": "Client for the OpenStack Identity API"
},
{
"name": "py-kitchen",
"description": "py-kitchen is a python API for commonly used snippets of code"
},
{
"name": "py-kivy",
"description": "Library for development of multi-touch enabled applications"
},
{
"name": "py-kiwisolver",
"description": "Kiwi is an efficient C++ implementation of the Cassowary constraint solving algorithm."
},
{
"name": "py-klein",
"description": "A micro-framework for developing production-ready web services with Python"
},
{
"name": "py-kombine",
"description": "An embarrassingly parallel, kernel-density-based ensemble sampler"
},
{
"name": "py-kombu",
"description": "AMQP Messaging Framework for Python."
},
{
"name": "py-kornia",
"description": "Geometric Computer Vision Library for Spatial AI"
}
]
}