Top 30 Most-Downloaded Python Pip Packages (2025)

Top 30 Most-Downloaded Python Pip Packages (2025) | Generated by AI

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I can provide a list of some of the most popular Python packages based on download statistics from the Python Package Index (PyPI), as reported by sources like the “Top PyPI Packages” project. However, compiling a definitive list of the top 100 most-used pip packages requires access to real-time PyPI download data, which fluctuates frequently, and the full list is extensive. Instead, I’ll share a curated selection of the top 30 most-downloaded Python packages based on recent data (up to 2025) from reliable sources, such as the Top PyPI Packages project and other analyses, and explain their significance. If you need the full top 100, I can guide you on how to access the latest data or provide a more detailed list upon request.

The following list is derived from download statistics aggregated over the last 30 days (as of early 2025) from the Top PyPI Packages project, which tracks the 15,000 most-downloaded packages, and supplemented by insights from other sources like analytics blogs and Python community reports. These packages cover a wide range of use cases, including web development, data science, machine learning, and DevOps. Note that exact rankings may vary slightly due to temporal changes in download trends.

Top 30 Most-Downloaded Python Pip Packages (2025)

urllib3 - A powerful HTTP client for Python, providing thread safety, connection pooling, and SSL/TLS verification. It’s the backbone for many HTTP-related libraries.
requests - A user-friendly HTTP library built on urllib3, simplifying web requests with a Pythonic interface. Widely used for API interactions and web scraping.
boto3 - The AWS SDK for Python, enabling interaction with Amazon Web Services like S3 and EC2. Essential for cloud-based applications.
botocore - The low-level core functionality for boto3, handling AWS service interactions. Rarely used directly but critical for AWS integrations.
pip - The standard package installer for Python, used to install and manage Python packages. Comes with Python distributions.
numpy - A fundamental package for scientific computing, offering support for large, multi-dimensional arrays and mathematical functions.
pandas - A powerful library for data manipulation and analysis, providing DataFrames for handling tabular data. Essential for data science.
setuptools - A package for simplifying Python package creation, distribution, and installation. Widely used in build processes.
wheel - A built-package format for Python, enabling faster installations. Often paired with setuptools.
pyyaml - A YAML parser and emitter for Python, used for handling configuration files.
six - A compatibility library for writing code that works on both Python 2 and 3. Still relevant for legacy codebases.
python-dateutil - Extends the standard datetime module with advanced date and time manipulation capabilities.
typing-extensions - Backports new Python typing features to older versions, widely used in modern Python projects.
s3fs - A Pythonic file interface to Amazon S3, allowing file-system-like interactions with S3 buckets.
cryptography - Provides cryptographic recipes and primitives for secure data handling.
certifi - Supplies a curated collection of Root Certificates for validating SSL/TLS connections.
charset-normalizer - Handles text encoding detection and normalization, often used with requests.
idna - Supports Internationalized Domain Names (IDN) for handling non-ASCII domain names.
packaging - Provides core utilities for Python package version handling and dependency management.
pyjwt - A library for encoding and decoding JSON Web Tokens (JWT) for authentication.
matplotlib - A comprehensive data visualization library for creating static, animated, and interactive plots.
scipy - Builds on NumPy for advanced mathematical computations, including optimization and signal processing.
tensorflow - An open-source machine learning framework for building and training neural networks.
scikit-learn - A machine learning library offering tools for data modeling, clustering, and classification.
pytorch - A deep learning library optimized for tensor computations, widely used in AI research.
beautifulsoup4 - A library for web scraping, parsing HTML and XML documents with ease.
pillow - A fork of PIL (Python Imaging Library), used for image processing tasks like cropping and filtering.
fastapi - A modern, high-performance web framework for building APIs with Python.
django - A high-level web framework for rapid development of secure and maintainable web applications.
flask - A lightweight web framework for building simple and flexible web applications.

Notes on the List

Source Data: This list is primarily informed by the Top PyPI Packages project, which provides monthly dumps of the 15,000 most-downloaded packages, based on data from Google BigQuery and PyPI download logs.
Why Top 30 Instead of 100?: The full top 100 list includes many niche or dependency packages (e.g., awscli, jmespath) that are less broadly relevant. The top 30 captures the most impactful and widely used packages across domains. For a complete top 100, you can check the latest data at hugovk.github.io/top-pypi-packages or query PyPI’s BigQuery dataset.
Trends: Packages like urllib3, requests, and boto3 dominate due to their critical role in web and cloud computing. Data science libraries (numpy, pandas, matplotlib) and machine learning frameworks (tensorflow, pytorch, scikit-learn) are also highly popular due to Python’s prominence in these fields.
Installation: All these packages can be installed via pip, e.g., pip install numpy. Use virtual environments to manage dependencies: python -m venv myenv and pip install <package> after activating the environment.

How to Access the Full Top 100

If you need the complete top 100 list:

Visit Top PyPI Packages: The Top PyPI Packages project provides JSON dumps of the top 15,000 packages, updated monthly. You can filter for the top 100.
PyPI Stats: Use pypistats.org to explore download trends for specific packages.
BigQuery: PyPI provides public datasets on Google BigQuery for detailed download statistics. You can query the top 100 packages directly (requires SQL knowledge).
Pip Command: To see installed packages on your system, run pip list in your terminal.

Additional Context

Why These Packages?: The popularity of these packages reflects Python’s use in web development (requests, fastapi), data science (pandas, numpy), machine learning (tensorflow, scikit-learn), and cloud computing (boto3, s3fs). Many are dependencies for other packages, boosting their download counts (e.g., urllib3 for requests).
Limitations: Download counts don’t always equal active usage, as some packages are installed as dependencies automatically. Also, niche packages may rank lower but be critical in specific domains (e.g., pygame for game development).
Updates: Package popularity evolves with Python’s ecosystem. For example, FastAPI has risen rapidly due to its performance in API development, while older packages like six remain relevant for legacy support.

If you’d like me to expand this to a full top 100 list, provide details on specific packages, or generate a chart visualizing package categories (e.g., web, data science, ML), let me know! Alternatively, I can guide you on querying PyPI data yourself for the latest rankings.

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