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17 रिपॉजिटरी

Awesome GitHub RepositoriesC-Extensions

Tools and patterns for compiling Python code into C for increased execution speed and memory efficiency.

Distinct from Python Compilers: Distinct from general Python compilers: specifically focuses on the Cython-style translation to C source for performance optimization.

Explore 17 awesome GitHub repositories matching programming languages & runtimes · C-Extensions. Refine with filters or upvote what's useful.

Awesome C-Extensions GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • gto76/python-cheatsheetgto76 का अवतार

    gto76/python-cheatsheet

    38,499GitHub पर देखें↗

    This project is a comprehensive technical reference and programming cheatsheet for the Python language. It serves as a curated catalog of language features, syntax patterns, and standard library functions designed to help developers identify and apply correct coding patterns. The documentation covers a broad range of functional areas, including language fundamentals such as object-oriented structuring, functional logic, and list comprehensions. It also provides guidance on utilizing the standard library for data analysis, file management, networking, and concurrent execution. The reference e

    Documents how to use Cython to compile Python-like code into C for high-performance execution.

    Pythoncheatsheetpythonpython-cheatsheet
    GitHub पर देखें↗38,499
  • explosion/spacyexplosion का अवतार

    explosion/spaCy

    33,688GitHub पर देखें↗

    spaCy is a Python natural language processing framework designed for industrial-scale text processing. It converts raw text into structured data for machine learning pipelines through a combination of statistical language model trainers, transformer-based text processors, and syntactic dependency parsers. The project enables the integration of pretrained transformer architectures to perform complex linguistic analysis and multi-task learning. It also provides a specialized system for neural named entity recognition to identify and categorize key entities within text. The framework covers a b

    Uses Cython C-extensions to provide high-performance memory management and tensor operations within Python.

    Pythonaiartificial-intelligencecython
    GitHub पर देखें↗33,688
  • python/mypypython का अवतार

    python/mypy

    20,489GitHub पर देखें↗

    mypy is a static type checker for Python that analyzes source code to detect type errors and inconsistencies without executing the program. It functions as a static analysis tool and type inference engine, providing a gradual typing system that allows type hints to be added to a codebase incrementally while maintaining compatibility with dynamic typing. The project distinguishes itself through a combination of performance and precision features. It utilizes a daemon-based incremental checking system and multi-process parallel analysis to manage large codebases, supported by binary cache persi

    Transforms Python modules into C extensions using type hints to increase execution performance.

    Pythonlinterpythontypechecker
    GitHub पर देखें↗20,489
  • phalcon/cphalconphalcon का अवतार

    phalcon/cphalcon

    10,829GitHub पर देखें↗

    Phalcon is a full-stack PHP web framework implemented as a compiled C extension that loads directly into the PHP interpreter. Rather than executing PHP scripts at runtime, the framework runs as a native C module, bundling routing, ORM, templating, and caching into immutable structures compiled at build time. This architecture hooks directly into PHP's internal Zend Engine API to bypass userland function call overhead, processes HTTP requests through a C-level event pipeline, and passes data between layers using pointer references instead of duplicating memory buffers. The framework manages ob

    Provides a full-stack PHP web framework implemented as a compiled C extension for maximum performance.

    PHPext-phalconextensionframework
    GitHub पर देखें↗10,829
  • cython/cythoncython का अवतार

    cython/cython

    10,767GitHub पर देखें↗

    Cython is a compiler that translates Python code into C or C++ to create high-performance extension modules. It functions as a static typing optimizer and a C extension generator, allowing developers to declare C types within Python code to reduce interpreter overhead and increase execution speed. The project enables the wrapping of external C libraries to provide high-level interfaces to low-level system capabilities. It also serves as a native binary packager, capable of freezing scripts and their dependencies into standalone executable binaries for distribution. The system covers a broad

    Provides tools for compiling Python code into C extensions to increase execution speed and memory efficiency.

    Cythonbig-dataccpp
    GitHub पर देखें↗10,767
  • falconry/falconfalconry का अवतार

    falconry/falcon

    9,794GitHub पर देखें↗

    Falcon is a minimalist Python web API framework and high-performance microservices framework. It serves as a resource-oriented API toolkit designed for building RESTful APIs and data plane services that prioritize low overhead, reliability, and scale. The framework implements an ASGI web server interface to handle both synchronous and asynchronous HTTP requests and WebSockets. It features a dedicated HTTP middleware system for intercepting network traffic and executing shared processing logic across multiple API endpoints. Its capability surface covers resource-based routing, HTTP specificat

    Uses compiled C extensions to optimize critical paths and increase request throughput.

    Pythonapiapi-restasgi
    GitHub पर देखें↗9,794
  • librosa/librosalibrosa का अवतार

    librosa/librosa

    8,200GitHub पर देखें↗

    Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature extraction suite and music information retrieval tool designed to analyze the structural and sonic characteristics of audio signals. The library provides specialized capabilities for music analysis, including dynamic tempo tracking to identify rhythmic pulses and spectral feature extraction to compute harmonic spectra, chroma variants, and onset points. It also serves as a time-series audio processor for synchronizing audio streams. The system covers a broad range of audio processing

    Implements C-extensions to accelerate computationally expensive signal processing loops for near-native execution speed.

    Pythonaudiodsplibrosa
    GitHub पर देखें↗8,200
  • lijin-thu/notes-pythonlijin-THU का अवतार

    lijin-THU/notes-python

    7,132GitHub पर देखें↗

    This project is a collection of educational notes and tutorials focused on Python programming, scientific computing, and data analysis. It serves as a reference for learning language basics, advanced techniques, and object-oriented design. The materials include implementation guides for building linear, logistic, and convolutional neural networks using symbolic graph frameworks. It also provides instruction on manipulating and visualizing structured data frames and performing complex mathematical operations through numerical libraries. The repository includes a system for converting interact

    Provides instructional notes on creating C-extensions to improve Python execution speed for computationally intensive tasks.

    Jupyter Notebookanacondamatplotlibnumpy
    GitHub पर देखें↗7,132
  • pufferai/pufferlibPufferAI का अवतार

    PufferAI/PufferLib

    6,039GitHub पर देखें↗

    PufferLib is a reinforcement learning framework built around high-speed environment simulation and automatic hyperparameter optimization. It is designed to accelerate the entire RL training pipeline by running simulations at near-native speed and enabling the training of tiny models to super-human performance within seconds. The framework achieves its speed through a single-process training loop that eliminates inter-process communication overhead, vectorized batched simulation for parallel environment execution, and compiled C extensions that offload performance-critical computations. It als

    Offloads performance-critical RL simulation loops to compiled C extensions for near-native speed.

    Creinforcement-learning
    GitHub पर देखें↗6,039
  • wendesi/lihang_book_algorithmWenDesi का अवतार

    WenDesi/lihang_book_algorithm

    5,827GitHub पर देखें↗

    This is an educational Python implementation of every algorithm from Li Hang's textbook on statistical learning methods. The project provides a comprehensive collection of supervised learning algorithms covering classification, regression, and sequence modeling techniques, implemented from scratch for learning and reference purposes. The repository covers a broad range of foundational machine learning methods, including decision trees built using the ID3 algorithm with information gain, ensemble boosting through AdaBoost that combines threshold-based weak learners, and probabilistic sequence

    Accelerates model training by implementing the computationally intensive threshold classifier in C++ as a shared library.

    Python
    GitHub पर देखें↗5,827
  • pypa/sampleprojectpypa का अवतार

    pypa/sampleproject

    5,245GitHub पर देखें↗

    This project is a reference implementation and tutorial designed to demonstrate the end-to-end workflow of building, versioning, and uploading Python distributions. It serves as a concrete project template and example for configuring metadata and build artifacts for package indices. The repository illustrates how to package software by defining project metadata and dependencies in static configuration files. It covers the process of transforming source trees into versioned archives and platform-specific binary distributions, specifically showing how to build binary wheels and source distribut

    Demonstrates the process of compiling C source code into importable Python modules.

    Python
    GitHub पर देखें↗5,245
  • laruence/yaflaruence का अवतार

    laruence/yaf

    4,516GitHub पर देखें↗

    Yaf एक MVC वेब फ्रेमवर्क है जिसे C में एक कंपाइल किए गए PHP एक्सटेंशन के रूप में लागू किया गया है। यह मानक user-land PHP में लिखे गए फ्रेमवर्क की तुलना में ओवरहेड को कम करने और रिक्वेस्ट प्रोसेसिंग की गति बढ़ाने के लिए डिज़ाइन किया गया एक प्रदर्शन एक्सटेंशन है। यह फ्रेमवर्क इनकमिंग नेटवर्क रिक्वेस्ट को कंट्रोलर्स तक भेजने की प्रक्रिया को तेज़ करने के लिए रिक्वेस्ट राउटिंग सहित कोर लॉजिक को एक कंपाइल किए गए बाइनरी लेयर में ले जाता है। यह मानकीकृत प्रोजेक्ट स्कैफोल्डिंग और बॉयलरप्लेट डायरेक्टरी संरचनाएं उत्पन्न करने के लिए एक कमांड-लाइन उपयोगिता प्रदान करता है। यह सिस्टम एनवायरनमेंट स्टेट को इनिशियलाइज़ करने के लिए एप्लिकेशन बूटस्ट्रैपिंग, सिस्टम सेटिंग्स के लिए कॉन्फ़िगरेशन प्रबंधन, और HTML आउटपुट उत्पन्न करने के लिए टेम्प्लेट रेंडरिंग को कवर करता है।

    Optimizes core framework tasks by implementing them as a compiled C extension.

    Ccphpphp-framework
    GitHub पर देखें↗4,516
  • toblerity/shapelyToblerity का अवतार

    Toblerity/Shapely

    4,457GitHub पर देखें↗

    Shapely समतलीय ज्यामितीय वस्तुओं (planar geometric objects) के हेरफेर और विश्लेषण के लिए एक ज्यामितीय विश्लेषण लाइब्रेरी है। यह एक कम्प्यूटेशनल ज्यामिति टूलकिट, टोपोलॉजिकल संबंधों का मूल्यांकन करने के लिए एक स्थानिक प्रेडिकेट इंजन और एक वेक्टराइज्ड ज्यामिति प्रोसेसर के रूप में कार्य करता है। यह लाइब्रेरी एक वेक्टराइज्ड ज्यामिति प्रोसेसर के माध्यम से खुद को अलग करती है जो मल्टी-थ्रेडेड समानांतर प्रोसेसिंग के साथ समन्वय सरणियों (coordinate arrays) में संचालन करने में सक्षम है। यह बार-बार होने वाले कंटेनमेंट और इंटरसेक्शन टेस्ट को तेज करने के लिए तैयार ज्यामिति ऑप्टिमाइज़ेशन का उपयोग करती है और कुशल निकटतम-पड़ोसी और इंटरसेक्टिंग ज्यामिति रिट्रीवल के लिए R-tree स्थानिक इंडेक्सिंग को लागू करती है। टूलकिट सेट-सैद्धांतिक संचालन, एफिन ट्रांसफॉर्मेशन और वोरोनोई आरेख (Voronoi diagrams) व डेलॉने ट्राइएंगुलेशन जैसी जटिल संरचनाओं के निर्माण सहित क्षमताओं की एक विस्तृत श्रृंखला को कवर करती है। यह क्षेत्र और लंबाई जैसे आंतरिक मेट्रिक्स की गणना करने के लिए टूल्स, साथ ही टोपोलॉजिकल सत्यापन और ज्यामिति मरम्मत के लिए उपयोगिताएँ प्रदान करती है। Shapely GeoJSON, Well-Known Text और Well-Known Binary प्रारूपों के बीच ज्यामितीय डेटा को पार्स और सीरियलाइज़ करके भू-स्थानिक डेटा इंटरऑपरेबिलिटी सुनिश्चित करती है।

    Releases the Global Interpreter Lock during native C++ GEOS calls to enable multi-threaded geometric processing.

    Python
    GitHub पर देखें↗4,457
  • shapely/shapelyshapely का अवतार

    shapely/shapely

    4,455GitHub पर देखें↗

    Shapely समतलीय ज्यामितीय वस्तुओं के हेरफेर और विश्लेषण के लिए एक लाइब्रेरी है, जो GEOS C++ इंजन के लिए एक Python रैपर के रूप में कार्य करती है। यह ज्यामितीय गुणों की गणना करने, स्थानिक संबंधों का मूल्यांकन करने और कार्टेशियन प्लेन के भीतर टोपोलॉजिकल प्रेडिकेट्स करने के लिए एक फ्रेमवर्क प्रदान करती है। यह प्रोजेक्ट एक वेक्टराइज्ड ज्यामिति प्रोसेसर के माध्यम से खुद को अलग करता है जो थ्रूपुट बढ़ाने के लिए आकृतियों की बड़ी सरणियों में स्थानिक संचालन करने में सक्षम है। इसमें इंटरसेक्टिंग ज्यामिति और निकटतम पड़ोसियों की रिट्रीवल को तेज करने के लिए R-trees पर आधारित एक स्थानिक इंडेक्सिंग सिस्टम भी शामिल है। लाइब्रेरी क्षमताओं की एक विस्तृत श्रृंखला को कवर करती है, जिसमें यूनियनों और इंटरसेक्शन की गणना के लिए ज्यामितीय सेट संचालन, GeoJSON और Well-Known Text जैसे प्रारूपों के बीच स्थानिक डेटा सीरियलाइजेशन, और ज्यामिति टोपोलॉजी को सत्यापित करने और मरम्मत करने के लिए टूल्स शामिल हैं। यह ज्यामितीय ट्रांसफॉर्मेशन, बफरिंग और कॉन्वेक्स हल्स या वोरोनोई आरेख के निर्माण का भी समर्थन करती है।

    Releases the global interpreter lock during heavy geometric computations to enable true multi-threaded execution.

    Python
    GitHub पर देखें↗4,455
  • thunlp/openkethunlp का अवतार

    thunlp/OpenKE

    4,041GitHub पर देखें↗

    OpenKE is a knowledge graph embedding framework designed to transform structured knowledge graphs into low-dimensional vector representations. It functions as a library for representation learning and a toolset for converting entities and relations into numerical embeddings. The project includes a link prediction engine to evaluate the likelihood of relationships between entities and identify missing facts in large-scale graphs. It provides a dedicated preprocessing tool to map raw entity and relation strings into numerical identifiers for machine learning training. The framework's capabilit

    Implements a native C++ layer to accelerate computationally intensive training loops for knowledge graph embeddings.

    Pythonknowledge-embedding
    GitHub पर देखें↗4,041
  • pypa/setuptoolspypa का अवतार

    pypa/setuptools

    2,809GitHub पर देखें↗

    Setuptools is a Python package build tool and distribution framework used to bundle code into distributable archives. It functions as a project metadata manager, allowing for the declarative definition of project identity, versioning, and dependencies. The toolkit distinguishes itself by providing an extension compiler for C and C++ source files and a plugin architecture that uses entry points to enable runtime discovery of functionality. It also supports development environment tooling, such as editable installs that link source code directly to the environment to allow immediate changes wit

    Compiles C and C++ source files into binary modules to improve execution speed within Python environments.

    Python
    GitHub पर देखें↗2,809
  • webassembly/wasi-sdkWebAssembly का अवतार

    WebAssembly/wasi-sdk

    1,504GitHub पर देखें↗

    The WASI SDK is a comprehensive compiler toolchain designed to transform C and C++ source code into portable, sandboxed binary modules. It provides the necessary utilities to target the WebAssembly System Interface, enabling native code to execute across diverse hardware and operating system environments through a standardized interface. The toolkit distinguishes itself by providing a complete, sysroot-isolated environment that ensures build consistency regardless of the host operating system. By bundling compilers, system headers, and libraries into unified, portable archives, it facilitates

    Compiles C and C++ source code into portable binary modules by resolving target paths and system dependencies.

    CMakellvmsysrootwasi-libc
    GitHub पर देखें↗1,504
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  4. C-Extensions

सब-टैग एक्सप्लोर करें

  • Compilation BridgesInterfaces that connect high-level build tools to system-level native compilers. **Distinct from C-Extensions:** Distinct from C-Extensions by focusing on the bridge/interface to the compiler rather than the resulting module pattern.
  • GIL ManagementStrategies for releasing the Global Interpreter Lock during native CPU-intensive operations. **Distinct from C-Extensions:** Focuses specifically on the GIL release mechanism for concurrency, whereas the parent focuses on general compilation/extension patterns.
  • Native Module CompilationThe process of compiling C source code into importable Python modules using setup scripts. **Distinct from C-Extensions:** Distinct from C-Extensions: specifically focuses on the compilation workflow and toolchain rather than the translation of Python to C.
  • PHP C-Extension FrameworksFull-stack PHP frameworks implemented as compiled C extensions that load directly into the PHP interpreter. **Distinct from C-Extensions:** Distinct from general C-Extensions: focuses on complete web frameworks compiled as C extensions, not individual Python-to-C translation tools.
  • RL Simulation AcceleratorsCompiled C extensions that offload performance-critical loops like environment stepping and reward computation for near-native speed. **Distinct from C-Extensions:** Distinct from general C-Extensions: specifically targets RL simulation acceleration, not general Python-to-C translation.
  • Training Acceleration ExtensionsC++ shared libraries that accelerate computationally intensive training loops by implementing core logic in native code. **Distinct from C-Extensions:** Distinct from C-Extensions: specifically targets machine learning training acceleration rather than general Python-to-C compilation.