Showing 7 open source projects for "python code"

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  • 1
    Faker for Python

    Faker for Python

    Python package that generates fake data for you

    Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating...
    Downloads: 1 This Week
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  • 2
    attrs

    attrs

    Python Classes Without Boilerplate

    attrs is a Python package that lets you write classes without all the usual drudgery. Its ultimate goal is to help you write concise and correct software without slowing down your code. attrs provides a class decorator and a means to declaratively define the attributes on that class. This results in a concise and explicit overview of the class's attributes, a human-readable __repr__, a complete set of comparison methods and more, all without having to repetitively write dull boilerplate code and without negatively affecting your runtime performance. ...
    Downloads: 3 This Week
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  • 3
    pipx

    pipx

    Install and run Python applications in isolated environments

    pipx is a tool to help you install and run end-user applications written in Python. It's roughly similar to macOS's brew, JavaScript's npx, and Linux's apt. It's closely related to pip. In fact, it uses pip, but is focused on installing and managing Python packages that can be run from the command line directly as applications. pip is a general-purpose package installer for both libraries and apps with no environment isolation. pipx is made specifically for application installation, as it...
    Downloads: 5 This Week
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  • 4
    Conda

    Conda

    OS-agnostic, system-level binary package manager

    Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a...
    Downloads: 33 This Week
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  • 5
    FuseSoC

    FuseSoC

    Package manager and build abstraction tool for FPGA/ASIC development

    FuseSoC is a package manager and build abstraction tool for hardware description language (HDL) code, aimed at simplifying the development and reuse of IP cores. It provides a standardized way to describe, manage, and build hardware projects, facilitating collaboration and reducing duplication of effort in FPGA and ASIC development. ​
    Downloads: 0 This Week
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  • 6
    Alphafold

    Alphafold

    Open source code for AlphaFold

    This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper. Please also refer to the Supplementary Information for a detailed description of the method. You can use...
    Downloads: 4 This Week
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  • 7
    Import from github_com

    Import from github_com

    Python module finder/loader from github, like in golang

    import_from_github_com is a playful yet practical experiment that lets you import Python modules directly from GitHub using an import-like mechanism. The idea is to remove the friction of “clone → install → import” when you just want to try out a single file or small repo. It hooks into Python’s import machinery so that when you reference a GitHub path, it fetches the code, stores it locally (often with caching), and makes it importable in the current environment.
    Downloads: 0 This Week
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