Showing 981 open source projects for "python games code"

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  • 1
    pep484 stubs for Django

    pep484 stubs for Django

    PEP-484 stubs for Django

    This package contains type stubs and a custom mypy plugin to provide more precise static types and type inference for Django framework. Django uses some Python "magic" that makes having precise types for some code patterns problematic. This is why we need this project. The final goal is to be able to get precise types for the most common patterns. We are independent from Django at the moment. There's a proposal to merge our project into the Django itself. You can show your support by liking...
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  • 2
    django-money

    django-money

    Money fields for Django forms and models

    A little Django app that uses py-moneyed to add support for Money fields in your models and forms. The default currency code length is 3 but you can change it with the CURRENCY_CODE_MAX_LENGTH setting. Currencies are listed on moneyed, and these modules use this to provide a choice list on the admin, also for validation. Django-money leaves you to use any custom model managers you like for your models, but it needs to wrap some of the methods to allow searching for models with money values...
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  • 3
    dynaconf

    dynaconf

    Configuration Management for Python

    ... Vault and Redis as settings and secrets storage. Built-in extensions for Django and Flask web frameworks. CLI for common operations such as init, list, write, validate, export. On your own code you import and use settings object imported from your config.py file. Dynaconf prioritizes the use of environment variables and you can optionally store settings in Settings Files using any of toml|yaml|json|ini|py extension.
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  • 4
    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase mining...
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  • 5
    re2

    re2

    Alternative to backtracking regular expression engines

    RE2 is a fast, safe, thread-friendly alternative to backtracking regular expression engines like those used in PCRE, Perl, and Python. It is a C++ library. This is the source code repository for RE2, a regular expression library. There is a fair amount of documentation (including code snippets) in the re2.h header file. Unless otherwise noted, the RE2 source files are distributed under the BSD-style license found in the LICENSE file. In POSIX mode, RE2 accepts standard POSIX (egrep) syntax...
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  • 6
    Ruby

    Ruby

    Ruby programming language

    A dynamic, open source programming language with a focus on simplicity and productivity. It has an elegant syntax that is natural to read and easy to write. Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming. He has often said that he is “trying to make Ruby natural, not simple,” in a way that...
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  • 7
    QuantumOptics.jl

    QuantumOptics.jl

    Library for the numerical simulation of closed as well as open quantum

    QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics...
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  • 8
    k3s in docker

    k3s in docker

    Little helper to run CNCF's k3s in Docker

    k3d is a lightweight wrapper to run k3s (Rancher Lab’s minimal Kubernetes distribution) in docker. k3d makes it very easy to create single- and multi-node k3s clusters in docker, e.g. for local development on Kubernetes. Note: k3d is a community-driven project but it’s not an official Rancher (SUSE) product. Sponsoring: To spend any significant amount of time improving k3d, we rely on sponsorships. k3d creates containerized k3s clusters. This means, that you can spin up a multi-node k3s...
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  • 9
    git-delete-merged-branches

    git-delete-merged-branches

    Command-line tool to delete merged Git branches

    ... Git hosting. Takes safety seriously. Deletion is a sharp knife that requires care. While git reflog would have your back in most cases, git-delete-merged-branches takes safety seriously. git push is used with --force-with-lease so if the server and you have a different understanding of that branch, it is not deleted. There is no use of os.system or shell code to go wrong.
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  • 10
    Qiling

    Qiling

    Qiling Advanced Binary Emulation Framework

    Cross-platform and multi-arch ultra lightweight emulator. Supported OS: Linux, MacOS, Windows, FreeBSD, DOS and UEFI. Support Arch: x86(16/32/64), ARM(64) MIPS, EVM and WASM. It also support Linux Kernel Module(.ko) , Windows Driver(.sys) and MacOS Kernel(.kext) via Demigod. Binary instrumentation and API are Qiling Framework's main focus and priority. It is designed for reverse engineers - thus there is no need to rebuild another sand boxing tool. Using Qiling Framework saves you time. The...
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  • 11
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 12
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads...
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  • 13
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    ... graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour).
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  • 14
    SageMaker Hugging Face Inference Toolkit

    SageMaker Hugging Face Inference Toolkit

    Library for serving Transformers models on Amazon SageMaker

    SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging...
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  • 15
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime...
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  • 16
    CapRover

    CapRover

    Scalable PaaS (automated Docker+nginx), aka Heroku on Steroids

    CapRover is an extremely easy-to-use app/database deployment & web server manager for your NodeJS, Python, PHP, ASP.NET, Ruby, MySQL, MongoDB, Postgres, WordPress (and etc...) applications! It's blazingly fast and very robust as it uses Docker, Nginx, LetsEncrypt and NetData under the hood behind its simple-to-use interface. For a developer who does not like spending hours and days setting up a server, building tools, sending code to the server, building it, getting an SSL certificate...
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  • 17
    Ansible Molecule

    Ansible Molecule

    Molecule aids in the development and testing of Ansible roles

    ....x, we will also test our code with 2.8.x. Depending on the driver chosen, you may need to install additional OS packages. See INSTALL.rst, which is created when initializing a new scenario. Ansible is not listed as a direct dependency of molecule package because we only call it as a command-line tool. You may want to install it using your distribution package installer. It is your responsibility to assure that soft dependencies of Ansible are available on your controller or host machines.
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  • 18
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    ... are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU).
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  • 19
    Werkzeug

    Werkzeug

    The comprehensive WSGI web application library

    Werkzeug is a comprehensive WSGI web application library. It began as a simple collection of various utilities for WSGI applications and has become one of the most advanced WSGI utility libraries. Werkzeug doesn’t enforce any dependencies. It is up to the developer to choose a template engine, database adapter, and even how to handle requests. Includes an interactive debugger that allows inspecting stack traces and source code in the browser with an interactive interpreter for any frame...
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  • 20
    AWX

    AWX

    A web-based user interface built on top of Ansible

    AWX provides a web-based user interface, REST API, and task engine built on top of Ansible. It is one of the upstream projects for Red Hat Ansible Automation Platform. Starting in version 18.0, the AWX Operator is the preferred way to install AWX. AWX can also alternatively be installed and run in Docker, but this install path is only recommended for development/test-oriented deployments, and has no official published release. Uses naming and structure consistent with the AWX HTTP API....
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  • 21
    OpenAI Cookbook

    OpenAI Cookbook

    Examples and guides for using the OpenAI API

    openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. The repository is kept up to date and often expanded...
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  • 22
    glbinding

    glbinding

    A C++ binding for the OpenGL API, generated using the gl.xml specifica

    ... as tools and examples for quick-starting your projects. Based on the OpenGL API specification (gl.xml) glbinding is generated using Python scripts and templates that can be easily adapted to fit custom needs.
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  • 23
    Nerves

    Nerves

    Craft and deploy bulletproof embedded software in Elixir

    Nerves is the open-source platform and infrastructure you need to build, deploy, and securely manage your fleet of IoT devices at speed and scale. Nerves is written in Elixir, but you don’t have to rewrite everything in Elixir to get the advantages of Nerves, simply bring your own code (like C, C++, Python, Rust, and more) and scale up. Nerves use the Erlang runtime system, known for being distributed, fault-tolerant, soft real-time, and highly available. Nerves has the tools you need to manage...
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  • 24
    DevDocs

    DevDocs

    API Documentation Browser

    The devdocs repository powers the DevDocs web application, a fast, offline-friendly documentation browser for many programming languages, libraries, and APIs. It aggregates documentation from multiple sources (e.g., MDN, Python, Ruby, Git, etc.), converts them into a uniform format, and indexes them for instant text searching. The codebase includes a backend that handles ingestion, parsing, and transformation of documentation sources into a static site structure, as well as the client side UI...
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  • 25
    TraceRoot

    TraceRoot

    Find the Root Cause in Your Code's Trace

    ... and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context.
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