Packages
Provides CMA-ES (Covariance Matrix Adaptation Evolution Strategy) optimization in an ask-and-tell interface, supporting continuous, integer, and categorical variable optimization with variants for mixed-variable and multi-objective problems.
Distributes CMake 4.4.2 as a Python package, making the cmake, ccmake, cpack, and ctest executables available on PATH for cross-platform build automation.
Install it if your project needs CMake as a build-time dependency or if you want to avoid separate CMake installation complexity.
Formats, lints, and annotates CMake listfiles, and converts ctest output to structured formats like JSON or XML.
No, not recommended for new projects.
Provides command-line tools to format, lint, and annotate CMake listfiles, plus a utility to parse and convert ctest output to JSON or XML.
However, do not adopt it for new projects or if you rely on recent CMake features—the abandonment since August 2020 means no bug fixes or feature updates will arrive.
cmakelint parses CMake files and reports style violations across syntax, whitespace, readability, and naming conventions.
cmap provides a collection of scientific colormaps (from matplotlib, cmocean, colorbrewer, crameri, seaborn, and others) that work with only numpy as a dependency, without requiring matplotlib.
Install it if you work with visualization libraries that support cmap exports or if you need colormaps in a lightweight, numpy-only environment.
Converts CommonMark and GitHub-flavored markdown to HTML using Python bindings to GitHub's fork of cmark.
The aging maintenance status (296 days since last release) is not a blocker for a mature, focused library; however, if you need active development or rapid bug fixes,…
Provides perceptually uniform colormaps by Fabio Crameri for matplotlib, enabling scientific visualizations designed to be readable across different media and accessible to colorblind viewers.
cmd2 is a Python framework for building interactive command-line applications with built-in tab completion, help text generation, scripting, and automation features.
CmdStanPy provides a pure-Python interface to the Stan probabilistic programming language, enabling you to compile Stan models and run Bayesian inference algorithms without direct C++ interaction.
Install it if you need to run Stan models from Python for Bayesian inference, statistical modeling, or probabilistic programming.
cmeel is a PEP 517 build backend that packages CMake projects as Python wheels for distribution on PyPI.
Provides a Python-packaged distribution of Assimp built via CMeel, enabling 3D model import in Python applications.
Provides pre-built Boost 1.90.0 C++ libraries packaged for Python environments via cmeel, enabling Python projects to link against Boost without compiling from source.
However, verify that the license treatment ('unclear') aligns with your use case, and confirm which Boost components are included match your actual needs.
Provides a Python distribution of console-bridge, a ROS-independent logging package that routes messages into rosconsole/rosout for ROS-dependent packages.
However, verify first whether your use case requires ROS integration or if you need console-bridge's logging outside a ROS context.
Provides Python bindings to OctoMap, a 3D probabilistic mapping framework that represents spatial environments as octrees for efficient storage and querying of occupancy data.
Provides precompiled qhull binaries (convex hull, Delaunay triangulation, Voronoi diagrams, halfspace intersection) as a Python package via the cmeel distribution system.
However, install only after clarifying the upstream license terms—the package metadata does not declare them, creating legal ambiguity for proprietary or…
Provides a Python-packaged distribution of TinyXML, a C++ XML parser library, via the cmeel build system for cross-platform use.
No—install only if you have an explicit dependency from another package or legacy codebase.
Provides a Python-packaged distribution of TinyXML-2, a lightweight C++ XML parser, via the cmeel build system for cross-platform use.
Parses URDF (U-Robot Description Format) XML files into Python data structures, supporting versions 1.0, 1.1, and 1.2 with features like quaternion orientation, capsule geometry, and extended joint limits.
Provides zlib 1.3.2 as a pre-built wheel for use within cmeel-based Python packages, enabling compression and decompression without requiring system zlib installation.
Provides perceptually uniform colormaps designed for oceanographic data visualization, integrating with matplotlib for scientific plots.
However, verify the license terms before use, as the license is currently unclear in the metadata.
Provides a Python logging handler that sends log records directly to Elasticsearch, integrating with the standard logging library to store structured logs in Elasticsearch indices.
Queries and manages device information from CMSIS PACKs, providing processor type, flash algorithm, and memory layout data through Python API or command-line interface.
Provides Python access to the CMU Pronouncing Dictionary data files (phonetic transcriptions, phone inventories, and related linguistic data) with minimal processing and NLTK compatibility.
cmweather provides a collection of colormaps optimized for weather and climate visualization, including color vision deficiency friendly options, built on numpy and matplotlib.
The dormant maintenance status is acceptable for a specialized, feature-complete library; however, do not expect active development or rapid bug fixes.
Converts between Chinese numerals and Arabic numerals in multiple modes, supporting integers, decimals, negatives, and sentence-level transformations including dates, fractions, and percentages.
CnOCR recognizes text in images—Chinese (simplified and traditional), English, and digits—using pre-trained deep learning models, with built-in text detection and support for both scene photos and document scans.
Detects text and mathematical formulas in images using pre-trained deep learning models, supporting Chinese, English, and multiple languages with both PyTorch and ONNX backends.
Coal is a collision detection and distance computation library that provides efficient GJK and EPA algorithm implementations for detecting collisions and computing distances between 3D geometric objects.
Coal provides collision detection, distance computation, and contact analysis for 3D geometric objects, with Python bindings for prototyping and integration into robotics frameworks.
Cobble is a Python library for creating data classes with automatic implementations of common methods like `__eq__` and `__repr__`, and for building visitor patterns over object hierarchies.
However, if you are on Python 3.7+ and do not need the visitor pattern, the standard library's dataclasses module or attrs may be more actively maintained alternatives.
COBRApy is a constraint-based modeling package for genome-scale metabolic network analysis, providing flux balance analysis, flux variability analysis, gene deletion analysis, and access to mathematical solvers.
Encodes and decodes data using Consistent Overhead Byte Stuffing (COBS), a method that eliminates zero bytes from encoded packets to enable reliable packet framing in communication protocols.
Install it if you need reliable packet framing in serial/network protocols or must eliminate zero bytes from binary data.
CocoIndex maintains a live, incrementally-updated index of codebases, documents, and other sources for AI agents and LLM applications, recomputing only the changed portions rather than re-processing everything.
cocotb is a Python framework for writing testbenches that simulate and verify VHDL and Verilog hardware designs through coroutine-based cosimulation.
cocotb-bus provides pre-built testbenching tools and reusable bus interface models for cocotb, a Python-based hardware verification framework.
Adds constrained randomization and functional coverage capabilities to cocotb, enabling SystemVerilog-style verification methodologies in Python for hardware testbenches.
cocotb-test wraps cocotb hardware simulations in pytest, letting you write and run HDL testbenches as standard Python unit tests without Makefiles.
Parses and summarizes code annotations (originally for PII detection) across codebases using configurable, extensible rules.
However, its Alpha status suggests it may be best suited for teams already in the Open edX ecosystem or those willing to invest in customization via its plugin system.
Code Puppy is an AI-powered code generation agent that understands programming tasks, generates code, and explains its reasoning by integrating with multiple LLM providers and executing code through shell and file tools.