Packages
Poetry is a dependency management and packaging tool that replaces setup.py, requirements.txt, and similar files with a single pyproject.toml configuration, handling project dependencies, virtual environments, and package builds.
Install it if you want deterministic dependency management and modern packaging practices.
poetry-core is a PEP 517 build backend that enables build frontends like pip to construct and install Poetry-managed projects without requiring Poetry itself or its dependencies.
A Poetry plugin that automatically loads environment variables from `.env` files before Poetry commands run, delegating to python-dotenv for variable expansion and interpolation.
However, note that maintenance is dormant (last release July 2023); if you need active support or compatibility with very recent Poetry versions, verify compatibility…
A Poetry plugin that automatically derives and injects version numbers from version control tags into your project during builds, using Dunamai to support multiple VCS systems.
Install it if you use Poetry 1.2.0+ and want to eliminate manual version management in your build workflow.
A Poetry plugin that enables building and type-checking projects with relative package includes, useful for monorepos where code is shared across multiple projects.
However, the aging maintenance status (last release 377 days ago) means you should verify compatibility with your current Poetry version before relying on it for…
Exports Poetry's locked dependency tree to requirements.txt, constraints.txt, or pylock.toml format for use with pip or other tools.
Install it if you use Poetry and need to export dependencies to pip-compatible formats for CI/CD, deployment, or interoperability with non-Poetry tools.
A Poetry plugin that launches a subshell with the project's virtual environment automatically activated, replacing Poetry's built-in shell command.
Pointpats provides statistical methods for analyzing planar point patterns, including clustering detection, distance-based tests, and spatial distribution metrics on Cartesian coordinates.
Install it if you need formal statistical tests on planar point patterns; skip it if your analysis is limited to simple distance or density calculations.
Python SDK for interacting with the Polar API, providing synchronous and asynchronous methods to manage organizations, benefits, checkouts, and other Polar resources, plus built-in webhook validation.
Install it if you're integrating with Polar's platform.
Provides a Python client for interacting with Polarion work-item management and test-management systems via SOAP API, allowing you to read, create, and modify workitems, test runs, plans, and documents.
However, the dormant maintenance status (no releases in 813 days) means you should verify compatibility with your Polarion version and be prepared to fork or patch if…
Polars is a DataFrame query engine written in Rust that executes analytical queries with multi-threaded, vectorized performance, supporting both lazy and eager evaluation modes.
Polars Cloud extends the Polars DataFrame library to run queries on distributed remote infrastructure, allowing you to scale computations beyond a single machine while using the same Polars API.
However, it is extremely new (0.10.0, released 11 days ago) with a 'Planning' development status, so treat it as early-stage software.
Polars-ds adds data science and machine learning operations to Polars dataframes, including linear regression, logistic regression, statistical tests, string and array distances, and feature engineering transforms.
Polars-hash adds cryptographic and non-cryptographic hashing functions to Polars DataFrames, including SHA256, FarmHash, CityHash, GxHash, geohashing, H3 spatial indexing, and time-window hashing.
However, verify the license terms before use in proprietary contexts, and confirm that the AES-instruction requirement for GxHash does not conflict with your…
polars-lts-cpu is a CPU-optimized DataFrame library that executes queries in Rust with lazy or eager evaluation, multi-threading, and SIMD support, handling datasets larger than RAM through streaming.
Polars OLS provides Rust-optimized linear regression models (OLS, WLS, Ridge, Elastic Net, non-negative least squares, recursive least squares) as Polars expressions, enabling efficient least-squares estimation within Polars workflows.
Polars-runtime-32 is a compiled runtime component for an analytical query engine that executes DataFrame queries with multi-threaded, vectorized performance and supports both lazy and eager evaluation modes.
A Rust-based analytical query engine for DataFrames that executes lazy and eager queries with multi-threaded, vectorized performance and can process datasets larger than available RAM through streaming.
Install it if you need fast analytical queries on large datasets or want performance-critical data transformation work.
Polars-runtime-compat provides binary wheels for Polars, a Rust-based analytical query engine for DataFrames, enabling fast vectorized execution with lazy and eager evaluation modes.
polib reads, writes, and manipulates gettext translation files (PO, POT, and MO formats), allowing you to load, iterate, modify entries, and create translation catalogs programmatically.
Install it if you need to work with gettext files programmatically.
Policy Sentry generates least-privilege AWS IAM policies from resource ARNs and access levels, automating the creation of security-scoped policies that would otherwise require manual AWS documentation review.
PolicyEngine Core provides a microsimulation engine and policy reform framework that powers country-specific tax and benefit models, enabling users to run policy scenarios and calculate outcomes across populations.
PolicyEngine US models the US federal and state tax and benefit system for household-level microsimulation calculations, computing tax liabilities, benefit eligibility, and distributional impacts.
However, note that direct microsimulation is deprecated in favor of the policyengine.py bundle for population-wide analysis.
Parses and analyzes AWS IAM and Resource Policies, extracts principals and conditions, detects internet accessibility, and expands or minifies policy wildcards.
However, note the dormant maintenance status—last release was 988 days ago—so verify compatibility with your AWS policy version and consider whether you need active…
Polling2 lets you wait for a function to return a desired condition without writing custom retry logic, handling timeouts and polling intervals automatically.
However, note that it is aging—last released in 2021 and not actively developed—so it is best suited for stable, simple polling tasks rather than projects requiring…
Constructs and serializes EIP-712 structured data for Ethereum signing, mapping Solidity-like types to Python objects with domain separation and message encoding.
Polyfactory generates mock data objects from type hints, supporting dataclasses, Pydantic models, typed-dicts, msgspec structs, and other typed structures for testing and development.
Identifies and maps the semantic and syntactic structure of files, including polyglots and embedded files, with a pure-Python libmagic implementation that can replace the `file` command and recursively extract embedded content.
However, the aging maintenance status (204 days since last release, minimal repository activity) and 14 runtime dependencies warrant caution for production use—verify…
Polyglot is a multilingual natural language processing pipeline that performs tokenization, language detection, named entity recognition, part-of-speech tagging, sentiment analysis, word embeddings, morphological analysis, and transliteration across many languages.
No—not for new projects.
Provides REST and WebSocket client libraries for accessing Massive financial market data APIs, including stock trades, quotes, aggregates, and options chains.
Polygraphy is a toolkit for running inference across multiple deep learning backends (TensorRT, ONNX-Runtime, etc.), comparing results, converting models to different formats, and debugging model behavior.
Install it if you need to prototype, compare, or debug deep learning inference across frameworks.
Polyleven computes Levenshtein distance between two strings using a fast C implementation, with optional threshold support to skip expensive comparisons.
Encodes and decodes geographic coordinate sequences using Google's Encoded Polyline Algorithm Format, converting between (lat, lon) tuples and compressed polyline strings.
Install it if your application requires polyline encoding/decoding; skip it if you don't work with this specific format.
A command-line tool that scaffolds and manages Polylith architecture workspaces in Python, automating the creation of components, bases, and projects within a structured codebase.
Official Python SDK for Polymarket that provides a unified interface to query public market data, manage authenticated accounts, execute trades, and handle wallet workflows on the Polymarket prediction market platform.
POML is a markup language and Python SDK for structuring, templating, and styling prompts for large language models, with support for embedding external data and managing presentation variations.
However, be aware that it is in early releases (0.0.8) with aging maintenance (354 days since last release), so expect the API to evolve and support to be slower.
Pond is an object-pooling library that manages reusable object instances with automatic lifecycle management, thread-safe borrowing and recycling, and memory-efficient frequency-based eviction.
However, maintenance is dormant (last release 2024-03-01, no recent commits), so adopt it only if you can tolerate a stable but unsupported dependency.
Pontos is a collection of Python utilities and tools for common development tasks, including CLI command support, version management, and data processing helpers maintained by Greenbone.
Pony is an object-relational mapper that lets you write database queries using Python generator expressions and lambdas, which it translates to SQL for SQLite, MySQL, PostgreSQL, and Oracle.
Pooch downloads files from HTTP, FTP, and data repositories (Zenodo, figshare), caches them locally, and verifies integrity via hash checking—eliminating manual file management and urllib boilerplate.
Install it if you need to download, cache, and verify data files in any Python project—it eliminates boilerplate and adds reproducibility with minimal overhead.