GPLv3+ and GPLv3+ with exceptions and GPLv2+ with exceptions and LGPLv2+ and BSD
LGPLv2+ and LGPLv2+ with exceptions and GPLv2+ and GPLv2+ with exceptions and BSD and Inner-Net-2.0 and ISC and Public Domain and GFDL-1.3-only
A fast multidimensional array facility for Python
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
acquired package info from repodata DB: repodata/f1f85c23079e7764ad00378a9fc5d660b89a03657290e75426caf7be5b7da462-primary.sqlite.bz2
FlatBuffers serialization format for Python
FlatBuffers is a serialization library for games and other memory constrained apps. FlatBuffers allows you to directly access serialized data without unpacking/parsing it first, while still having great forwards/backwards compatibility.
Easily build and distribute Python 3 packages
Setuptools is a collection of enhancements to the Python 3 distutils that allow you to more easily build and distribute Python 3 packages, especially ones that have dependencies on other packages. This package also contains the runtime components of setuptools, necessary to execute the software that requires pkg_resources.py.
An Open Source Machine Learning Framework for Everyone
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications. TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well. TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.
Abseil Python Common Libraries, see https://github.com/abseil/abseil-py.
This repository is a collection of Python library code for building Python applications. The code is collected from Google's own Python code base, and has been extensively tested and used in production. * Simple application startup * Distributed commandline flags system * Custom logging module with additional features * Testing utilities To install the package, simply run: ```bash pip install absl-py ``` Or install from source: ```bash python setup.py install ``` To run Abseil tests, you can clone the git repo and run [bazel](https://bazel.build/): ```bash git clone https://github.com/abseil/abseil-py.git cd abseil-py bazel test absl/... ``` Please refer to [smoke_tests/sample_app.py](https://github.com/abseil/abseil-py/blob/master/smoke_tests/sample_app.py) as an example to get started. See the [Abseil Python Developer Guide](https://abseil.io/docs/python/). The current repository includes an initial set of libraries for early adoption. More components and interoperability with Abseil C++ Common Libraries will come in future releases. The Abseil Python library is licensed under the terms of the Apache license. See [LICENSE](LICENSE) for more information.
A high- and low-level interface to the HDF5 library from Python
A high- and low-level interface to the HDF5 library from Python3
Keras is a high-level neural networks API for Python. Read the documentation at: https://keras.io/ Keras is compatible with Python 3.6+ and is distributed under the MIT license.
Backported and Experimental Type Hints for Python 3.5+
Typing Extensions -Backported and Experimental Type Hints for Python.
Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g., [`np.einsum`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.einsum.html), [`dask.array.einsum`](https://docs.dask.org/en/latest/array-api.html#dask.array.einsum), [`pytorch.einsum`](https://pytorch.org/docs/stable/torch.html#torch.einsum), [`tensorflow.einsum`](https://www.tensorflow.org/api_docs/python/tf/einsum), ) by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API. See the [**documentation**](http://optimized-einsum.readthedocs.io) for more information.
TensorBoard is a suite of web applications for inspecting and understanding your TensorFlow runs and graphs. Releases prior to 1.6.0 were published under the ``tensorflow-tensorboard`` name and may be found at https://pypi.python.org/pypi/tensorflow-tensorboard.
Python AST that abstracts the underlying Python version
A generic AST to represent Python2 and Python3's Abstract Syntax Tree(AST). GAST provides a compatibility layer between the AST of various Python versions, as produced by ``ast.parse`` from the standard ``ast`` module.
pasta is an AST-based Python refactoring library
Interpreter of the Python3 programming language
Python combines remarkable power with very clear syntax. It has modules, classes, exceptions, very high level dynamic data types, and dynamic typing. There are interfaces to many system calls and libraries, as well as to various windowing systems. New built-in modules are easily written in C or C++ (or other languages, depending on the chosen implementation). Python is also usable as an extension language for applications written in other languages that need easy-to-use scripting or automation interfaces. This package Provides python version 3.
ANSII Color formatting for output in terminal.
Reusable core utilities for various Python Packaging interoperability specifications. This library provides utilities that implement the interoperability specifications which have clearly one correct behaviour (eg: PEP 440) or benefit greatly from having a single shared implementation (eg: PEP 425). The packaging project includes the following: version handling, specifiers, markers, requirements, tags, utilities.
TensorFlow Estimator is a high-level API that encapsulates model training, evaluation, prediction, and exporting.
Module for decorators, wrappers and monkey patching.
This package contains GCC shared support library which is needed e.g. for exception handling support.
The GNU C Library project provides the core libraries for the GNU system and GNU/Linux systems, as well as many other systems that use Linux as the kernel. These libraries provide critical APIs including ISO C11, POSIX.1-2008, BSD, OS-specific APIs and more. These APIs include such foundational facilities as open, read, write, malloc, printf, getaddrinfo, dlopen, pthread_create, crypt, login, exit and more.
The libstdc++ package contains a rewritten standard compliant GCC Standard C++ Library.
Python 3 bindings for Google Protocol Buffers
This package contains Python 3 libraries for Google Protocol Buffers