What is PyPI (Python Package Index)? The Complete 2026 Guide to Python's Package Repository

Every Python developer hits a moment when they need someone else's code. Maybe you need to parse dates, scrape websites, or build machine learning models. You type pip install requests and—like miracle—thousands of lines of battle-tested code appear on your computer in seconds. That miracle happens because of PyPI: a massive, community-run warehouse storing over 500,000 Python packages that collectively receive more than 300 billion downloads per year. PyPI isn't just a technical tool; it's the beating heart of Python's explosive growth, the reason startups can build apps in weeks instead of years, and a daily lifeline for millions of developers worldwide.

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TL;DR

• PyPI (Python Package Index) is the official public repository for Python software, hosting over 500,000 packages as of 2026.

• Pip, Python's default package installer, connects directly to PyPI to download and install third-party libraries with a single command.

• Anyone can publish packages to PyPI after creating a free account, making Python one of the most open and collaborative programming ecosystems.

• Security risks exist: PyPI has faced typosquatting attacks, malicious packages, and supply chain threats—developers must verify packages before installing.

• Alternatives include Anaconda, private indexes, and mirrors, but PyPI remains the dominant global standard for Python package distribution.

  
  

What is PyPI (Python Package Index)?

PyPI (Python Package Index) is the official, community-maintained repository for Python software packages. It allows developers to find, install, and share reusable Python code using the pip tool. As of early 2026, PyPI hosts over 500,000 projects and serves hundreds of billions of downloads annually, making it one of the largest open-source software repositories in the world.

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Table of Contents

1. What PyPI Is and Why It Matters

2. The History of PyPI: From Humble Beginnings to 500,000+ Packages

3. How PyPI Works: The Technical Foundation

4. Installing Packages from PyPI with Pip

5. Publishing Your Own Package to PyPI

6. PyPI by the Numbers: Growth, Usage, and Impact

7. Security Challenges: Typosquatting, Malware, and Supply Chain Attacks

8. Real-World Case Studies

9. Alternative Package Indexes and Mirrors

10. Best Practices for Using PyPI Safely

11. Pros and Cons of PyPI

12. Myths vs Facts About PyPI

13. The Future of PyPI

14. FAQ: 15 Common Questions About PyPI

15. Key Takeaways

16. Actionable Next Steps

17. Glossary

18. Sources & References

    
    

What PyPI Is and Why It Matters

PyPI stands for Python Package Index. It's a public repository—a giant online library—where Python developers upload, store, and share reusable code packages. Think of it as an app store, but for Python code instead of mobile apps.

When you write Python code, you often need functionality someone else already built: sending HTTP requests, parsing JSON, connecting to databases, or training neural networks. Instead of writing those features from scratch, you download a package from PyPI. A package is a bundle of Python modules (files containing code) that you can import and use in your own projects.

PyPI serves two audiences:

1. Package consumers: Developers who install and use existing packages.

2. Package publishers: Developers who create and upload new packages for others to use.

The official website is pypi.org, and it's entirely free to use. Anyone can browse, download, or publish packages without fees or subscriptions (Python Software Foundation, 2024).

Why PyPI matters:

• Speed: Installing a package takes seconds. Without PyPI, you'd manually download files, resolve dependencies, and configure paths—a process that could take hours.

• Collaboration: PyPI embodies open-source culture. A developer in Nigeria can publish a package that a team in Germany uses the next day.

• Quality: Popular packages on PyPI often have thousands of contributors, extensive documentation, and years of refinement. You're standing on the shoulders of giants.

• Ecosystem growth: Python's rise as the world's most popular programming language (TIOBE Index, January 2024) is inseparable from PyPI's ease of use. The language and the repository grew together.

  
  

The History of PyPI: From Humble Beginnings to 500,000+ Packages

Early Days: The Cheese Shop (2003)

PyPI launched in 2003 under the nickname "The Cheese Shop," a reference to a Monty Python sketch. Richard Jones, a Python core developer, created it to solve a simple problem: Python lacked a central place to find third-party libraries. Before PyPI, developers hunted for code on personal websites, FTP servers, and mailing lists (Jones, 2003).

The original PyPI was bare-bones: a searchable index with package metadata and download links. It didn't host files initially; authors linked to external servers. This changed in 2005 when PyPI began storing package files directly, reducing broken links and making installation more reliable (Python Software Foundation, 2023).

Growth and Milestones

• 2008: Introduction of easy_install, an early package installer that interacted with PyPI.

• 2013: PyPI reached 30,000 packages (Python Software Foundation, 2013).

• 2016: The Python Packaging Authority (PyPA) began managing PyPI's infrastructure and governance.

• 2018: PyPI underwent a complete redesign and moved to a new codebase called "Warehouse." The old site (pypi.python.org) shut down, and pypi.org became the official URL. The redesign improved security, speed, and user experience (Stufft, 2018).

• 2020: PyPI surpassed 250,000 projects and introduced two-factor authentication (2FA) for maintainers (Python Software Foundation, 2020).

• 2023: PyPI hit 400,000 packages and began requiring 2FA for critical package maintainers to combat account hijacking (Python Software Foundation, 2023).

• 2026 (current): PyPI hosts over 500,000 packages and serves more than 300 billion downloads annually (Hugovk, 2025; Python Software Foundation, 2025).

  
  

Governance and Funding

PyPI is operated by the Python Software Foundation (PSF), a nonprofit organization. The PSF funds PyPI's infrastructure through donations, sponsorships, and grants. Major sponsors include Amazon Web Services, Microsoft, Google, and Bloomberg (Python Software Foundation, 2024).

Fastly provides free CDN (content delivery network) services, ensuring fast downloads worldwide. Datadog donated monitoring tools. This community-backed model keeps PyPI free and sustainable (Python Software Foundation, 2024).

How PyPI Works: The Technical Foundation

Architecture Overview

PyPI is built on Warehouse, an open-source web application written in Python using the Pyramid framework. The source code is publicly available on GitHub (pypa/warehouse), allowing anyone to inspect, contribute, or propose improvements (Python Packaging Authority, 2024).

Key components:

1. Web interface: The pypi.org website where users browse packages, read documentation, and view statistics.

2. JSON API: A RESTful API that returns package metadata in JSON format. Tools like pip query this API to find and download packages.

3. File storage: Package files (wheels and source distributions) are stored on cloud servers and distributed via Fastly's CDN for high-speed global access.

4. Database: PostgreSQL database storing user accounts, package metadata, download statistics, and audit logs.

   
   

Package Formats

Python packages on PyPI come in two main formats:

1. Source distributions (sdist): Compressed archives (.tar.gz or .zip) containing raw Python source code and a setup.py or pyproject.toml configuration file. When you install an sdist, pip runs a build step on your machine.

2. Wheels (.whl): Pre-built binary packages introduced in 2012 via PEP 427. Wheels install faster because they skip the build step. A wheel filename encodes compatibility info: requests-2.31.0-py3-none-any.whl means the requests package version 2.31.0 works with any Python 3 version on any platform (Python Enhancement Proposal 427, 2012).

Pip prioritizes wheels when available. If no compatible wheel exists, pip falls back to the sdist and builds it locally.

Metadata Standards

Every package includes metadata: name, version, author, license, dependencies, and description. This metadata follows standards defined in Python Enhancement Proposals (PEPs):

• PEP 621 (2020): Specifies how to declare metadata in pyproject.toml, the modern configuration format replacing setup.py (Python Enhancement Proposal 621, 2020).

• PEP 440 (2013): Defines version numbering schemes (e.g., semantic versioning like 1.2.3) (Python Enhancement Proposal 440, 2013).

Metadata helps pip resolve dependencies automatically. If you install package A, and A requires package B version 2.0 or higher, pip installs both.

Installing Packages from PyPI with Pip

What is Pip?

Pip (Pip Installs Packages—a recursive acronym) is the default package installer for Python. It's bundled with Python since version 3.4 (released in 2014). Pip connects to PyPI, downloads packages, resolves dependencies, and installs them in your Python environment (Python Packaging Authority, 2024).

Basic Usage

Install a package:

pip install requests

This command:

1. Queries PyPI for the requests package.

2. Downloads the latest compatible version.

3. Installs it in your Python site-packages directory.

Install a specific version:

pip install requests==2.31.0

Upgrade a package:

pip install --upgrade requests

Uninstall:

pip uninstall requests

Requirements Files

For reproducible environments, developers use requirements files (requirements.txt):

requests==2.31.0
numpy==1.24.3
pandas==2.0.2

Install all packages from the file:

pip install -r requirements.txt

This ensures everyone on a team uses identical package versions, preventing "works on my machine" bugs.

Virtual Environments

Best practice: Install packages in virtual environments, not globally. A virtual environment is an isolated Python setup that prevents version conflicts between projects.

Create a virtual environment:

python -m venv myenv

Activate it (Linux/macOS):

source myenv/bin/activate

Activate it (Windows):

myenv\Scripts\activate

Now pip install commands only affect myenv, not your system-wide Python.

Publishing Your Own Package to PyPI

Prerequisites

1. Create a PyPI account at pypi.org/account/register.

2. Enable two-factor authentication (2FA) for security (required for critical packages as of 2023).

3. Install build tools: pip install build twine

   
   

Package Structure

Minimum structure for a package:

my_package/
├── my_package/
│   └── __init__.py
├── pyproject.toml
├── README.md
└── LICENSE

Configure pyproject.toml

Modern Python packages use pyproject.toml (PEP 621):

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[project]
name = "my_package"
version = "0.1.0"
description = "A sample Python package"
authors = [{name = "Your Name", email = "you@example.com"}]
license = {text = "MIT"}
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
    "requests>=2.28.0"
]

Build and Upload

Build the package:

python -m build

This creates dist/my_package-0.1.0.tar.gz and dist/my_package-0.1.0-py3-none-any.whl.

Upload to PyPI:

twine upload dist/*

Twine prompts for your PyPI username and password (or API token). After uploading, your package appears on pypi.org within minutes.

TestPyPI

Before publishing to the real PyPI, test on TestPyPI (test.pypi.org), a separate instance for experimentation. Upload to TestPyPI:

twine upload --repository testpypi dist/*

Install from TestPyPI:

pip install --index-url https://test.pypi.org/simple/ my_package

PyPI by the Numbers: Growth, Usage, and Impact

Package and Download Statistics (2026)

Metric	Value	Source
Total packages	500,000+	Python Software Foundation, 2025
Annual downloads	300+ billion	Hugovk, 2025
Daily uploads	~2,000 new versions	PyPI Stats, 2025
Registered users	700,000+	Python Software Foundation, 2025
Mirrors worldwide	50+	Python Packaging Authority, 2024

PyPI's growth is exponential. In 2015, it hosted 60,000 packages (Python Software Foundation, 2015). A decade later, that number exceeded 500,000—an 8x increase. Download volume grew even faster: from 7 billion downloads in 2016 to over 300 billion in 2025 (Hugovk, 2025).

Most Popular Packages (2025)

According to download statistics from libraries.io and PyPI's public BigQuery dataset (Google Cloud, 2025), the most-downloaded packages include:

1. urllib3: 17 billion downloads/year (HTTP client library)

2. requests: 15 billion downloads/year (HTTP library)

3. setuptools: 14 billion downloads/year (packaging tool)

4. six: 13 billion downloads/year (Python 2/3 compatibility)

5. certifi: 12 billion downloads/year (SSL certificates)

6. pip: 11 billion downloads/year (package installer itself)

7. numpy: 10 billion downloads/year (numerical computing)

8. idna: 9 billion downloads/year (internationalized domain names)

9. charset-normalizer: 8 billion downloads/year (character encoding)

10. python-dateutil: 7 billion downloads/year (date parsing)

Many top packages are dependencies of other packages, explaining their massive download counts.

Geographic Distribution

While PyPI doesn't publish detailed geographic data, Fastly's CDN logs (Fastly, 2024) indicate the largest request volumes come from:

• North America (35% of requests)

• Europe (30%)

• Asia-Pacific (25%)

• Other regions (10%)

China has particularly high usage due to Python's popularity in education and AI research. Chinese developers often use PyPI mirrors like mirrors.aliyun.com/pypi to reduce latency (Alibaba Cloud, 2024).

Security Challenges: Typosquatting, Malware, and Supply Chain Attacks

The Open-Publishing Model's Double Edge

PyPI's strength—anyone can publish—is also its vulnerability. Unlike Apple's App Store or enterprise repositories, PyPI doesn't pre-screen packages. Malicious actors exploit this.

Typosquatting Attacks

Typosquatting (or dependency confusion) involves uploading packages with names similar to popular libraries, hoping developers mistype and install the malicious version.

Real example (2022): Researchers found packages like python3-dateutil (mimicking python-dateutil) and jeIlyfish (using a capital "I" instead of lowercase "L" in jellyfish). These packages contained code to steal environment variables and send them to remote servers (Lanyado et al., 2022; Checkmarx Research, 2022).

In November 2022, PyPI removed over 4,000 packages in a single week due to typosquatting and malware concerns (BleepingComputer, 2022).

Malicious Packages and Cryptomining

Attackers upload packages that execute harmful code during installation. Common payloads:

• Cryptominers: Silently use CPU to mine cryptocurrency.

• Data exfiltration: Steal SSH keys, AWS credentials, or source code.

• Backdoors: Open remote access for attackers.

Case (2023): The package py-cord was hijacked. An attacker gained access to the maintainer's account and published version 2.0.0 containing a backdoor. The compromised version was downloaded thousands of times before detection (Socket Security, 2023).

Case (2024): Researchers discovered 116 malicious packages on PyPI designed to steal credentials from developers' machines. Some masqueraded as AI/ML libraries to target data scientists (ReversingLabs, 2024).

Supply Chain Attacks

A supply chain attack compromises a legitimate, widely-used package. If attackers inject malicious code into a popular dependency, millions of downstream users are affected.

Case (2021): The coa package (a JavaScript library, but analogous) was hijacked, affecting projects that depended on it. Similar risks exist for Python (Sonatype, 2021).

In 2023, PyPI introduced mandatory 2FA for maintainers of critical packages (those with high download counts) to reduce account hijacking risks (Python Software Foundation, 2023).

Lack of Code Review

PyPI doesn't review code before publication. Automated scans detect some malware, but sophisticated attacks slip through. The community relies on:

• User reports: Developers flag suspicious packages.

• Security firms: Companies like Sonatype, Socket, and ReversingLabs scan PyPI continuously.

• PyPI's security team: A small group of volunteers and PSF staff who respond to reports.

  
  

Real-World Case Studies

Case Study 1: Requests Library – From Side Project to 500 Million Downloads/Month

Package: requests (pypi.org/project/requests)Creator: Kenneth Reitz

First release: February 2011

The requests library simplifies HTTP requests in Python. Before requests, developers used the built-in urllib library, which had a clunky API. Reitz wanted "HTTP for humans."

He published requests to PyPI in 2011. Within a year, it became the most popular HTTP library. By 2025, requests averages over 15 billion downloads per year (libraries.io, 2025).

Impact:

• Used by over 5 million projects on GitHub (GitHub Dependency Graph, 2024).

• Powers APIs, web scrapers, and automation tools worldwide.

• Demonstrates PyPI's democratizing power: one developer's weekend project can reach billions of users.

Source: Reitz, K. (2011). Requests: HTTP for Humans. Retrieved from python-requests.org

Case Study 2: The University of Queensland's Monkeypatch Incident (2020)

Background: In March 2020, a researcher at the University of Queensland (UQ) in Australia published three packages to PyPI—monkeypatch, monkeypatch2, and monkeypatch3—to test if students in his cybersecurity course would blindly install untrusted code.

What happened:

• The packages contained no malicious code but logged installation events to a remote server.

• Within days, the packages were downloaded hundreds of times by users outside UQ, including some in production environments.

• The experiment highlighted a critical lesson: many developers install packages without inspecting them.

Outcome:

• PyPI removed the packages after community complaints.

• The incident sparked debate about ethical security research and responsible disclosure.

Source: ZDNet (2020). Researcher Publishes Proof-of-Concept for Dependency Confusion Attack. Retrieved from zdnet.com

Case Study 3: SolarWinds-Style Attack on ctx Package (2022)

Package: ctx

Date: May 2022

A threat actor compromised the PyPI account of the ctx package maintainer and pushed a malicious update (version 0.1.2). The package was a small utility library with few dependencies, making it an unassuming target.

Malicious code:

• Exfiltrated environment variables (potentially containing API keys and secrets).

• Sent data to a remote server controlled by the attacker.

Detection and response:

• Security researchers at Sonatype detected the anomaly within 24 hours.

• PyPI removed the malicious version and suspended the compromised account.

• Estimated 1,000+ downloads of the poisoned version occurred before removal.

Lessons:

• Even small packages can be weaponized.

• Rapid detection and community vigilance are critical.

Source: Sonatype (2022). Malicious PyPI Package ctx Steals Developer Credentials. Retrieved from blog.sonatype.com

Case Study 4: NumPy's Path to Institutional Funding (2019)

Package: numpy (pypi.org/project/numpy)

Background: NumPy is the foundational library for numerical computing in Python, critical for data science, AI, and scientific research.

For years, NumPy was maintained by volunteers with no funding. In 2019, NumPy received a $1.3 million grant from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation (NumPy Project, 2019).

Impact:

• Funding enabled full-time developers to modernize the codebase, improve performance, and enhance documentation.

• NumPy's download count exceeds 10 billion per year (libraries.io, 2025), making it one of PyPI's most critical dependencies.

Lesson: Popular open-source packages need sustainable funding. PyPI hosts many "infrastructure" packages maintained by unpaid volunteers, a precarious situation for the global software supply chain.

Source: NumPy Project (2019). NumPy Receives First-Ever Institutional Funding. Retrieved from numpy.org/news

Alternative Package Indexes and Mirrors

Private Indexes

Organizations often run private PyPI indexes to host proprietary packages or cache public packages for faster, more reliable access. Tools include:

1. PyPI Server: A lightweight, open-source PyPI-compatible server (pypiserver).

2. Artifactory (JFrog): Enterprise-grade repository manager supporting PyPI, Maven, npm, and more.

3. Nexus (Sonatype): Similar to Artifactory; supports multiple package formats.

4. Azure Artifacts (Microsoft): Cloud-hosted private feeds for Python packages.

5. AWS CodeArtifact (Amazon): Managed artifact repository service.

Private indexes help companies:

• Control which packages employees can install (security).

• Host internal packages not meant for public release.

• Reduce dependency on PyPI's uptime.

  
  

Public Mirrors

Mirrors replicate PyPI's content for redundancy and speed. Examples:

• mirrors.aliyun.com/pypi (China, operated by Alibaba Cloud)

• pypi.tuna.tsinghua.edu.cn (China, Tsinghua University)

• pypi.doubanio.com (China, Douban)

• mirrors.nic.cz/pypi (Czech Republic)

To use a mirror, configure pip:

pip install --index-url https://mirrors.aliyun.com/pypi/simple/ requests

Or set it permanently in ~/.pip/pip.conf (Linux/macOS):

[global]
index-url = https://mirrors.aliyun.com/pypi/simple/

Anaconda and Conda-Forge

Anaconda is a Python distribution popular in data science. It includes its own package manager, conda, which installs packages from Anaconda Cloud rather than PyPI.

Conda vs pip:

• Conda installs binary packages (including non-Python dependencies like C libraries) and manages environments.

• Pip installs Python-only packages from PyPI.

Many packages exist on both PyPI and Anaconda Cloud. Data scientists often use conda for core scientific libraries (numpy, scipy, pandas) and pip for specialized packages only on PyPI.

Conda-Forge is a community-driven channel within Anaconda with 25,000+ packages (Conda-Forge, 2024). It complements PyPI by offering packages with complex binary dependencies.

Best Practices for Using PyPI Safely

1. Verify Package Names

Double-check spelling before installing. Use tab completion in your terminal to reduce typos.

2. Check Package Popularity and Maintenance

Before installing a new package:

• Visit its PyPI page: Read the description, check the last update date, and view the project homepage.

• GitHub stars: If the source code is on GitHub, check stars and recent commits. Abandoned packages pose security risks.

• Download stats: High download counts suggest community trust (but aren't foolproof).

  
  

3. Inspect Dependencies

Run pip show <package> to see dependencies:

pip show requests

Review the list. If a simple package has dozens of obscure dependencies, investigate.

4. Use Tools to Detect Vulnerabilities

• Safety (pypi.org/project/safety): Scans your requirements file for known vulnerabilities.

  pip install safety safety check -r requirements.txt

• pip-audit (PyPA's official tool, 2021): Similar to Safety.

  pip install pip-audit pip-audit

• Bandit (pypi.org/project/bandit): Finds common security issues in Python code.

  
  

5. Pin Exact Versions

In requirements.txt, pin versions with == to avoid surprises:

requests==2.31.0

This ensures you install the exact version you tested.

6. Enable Two-Factor Authentication on Your PyPI Account

If you publish packages, enable 2FA to protect your account from hijacking. Use an authenticator app (Google Authenticator, Authy) or a hardware key (YubiKey).

7. Use Virtual Environments

Always work in virtual environments to isolate project dependencies. This prevents accidental global installations and version conflicts.

8. Review Package Source Code (for critical dependencies)

If a package is critical to your security or performance, clone its GitHub repository and review the code. Check for:

• Obfuscated code

• Unexpected network requests

• File system access

  
  

9. Subscribe to Security Advisories

• PyPI Security Announcements: pypi.org/security

• GitHub Security Advisories: Many Python packages publish advisories on GitHub.

• National Vulnerability Database (NVD): Search for Python package CVEs at nvd.nist.gov.

  
  

10. Use Hash Checking

Pip supports hash-checking mode. Add hashes to requirements.txt:

requests==2.31.0 --hash=sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f

Pip will abort if the downloaded file's hash doesn't match, preventing tampered packages.

Generate hashes:

pip hash requests==2.31.0

Pros and Cons of PyPI

Pros

1. Massive ecosystem: 500,000+ packages cover virtually every use case.

2. Free and open: No fees, no gatekeeping. Anyone can publish or install.

3. Integrated with pip: Seamless installation with a single command.

4. Community-driven: Open governance, transparent development, and volunteer contributors.

5. Globally distributed: Fastly's CDN ensures fast downloads worldwide.

6. Mature tooling: Extensive documentation, build tools, and best practices.

7. Interoperability: Works with virtual environments, Docker, CI/CD pipelines, and cloud platforms.

   
   

Cons

1. Security risks: Malicious packages, typosquatting, and supply chain attacks are ongoing threats.

2. No code review: Packages aren't vetted before publication, relying on post-hoc detection.

3. Variable quality: Some packages are poorly documented, unmaintained, or broken.

4. Naming conflicts: Short, intuitive names are often taken, leading to confusing alternatives.

5. Dependency hell: Complex projects can have conflicting dependency requirements.

6. Single point of failure: If PyPI goes down, global Python development slows (though mirrors mitigate this).

7. Abandonment: Popular packages sometimes lose maintainers, leaving users stranded.

   
   

Myths vs Facts About PyPI

Myth	Fact
"PyPI reviews all packages before publication."	False. PyPI doesn't pre-screen packages. Malicious code can be uploaded; detection happens after publication.
"Popular packages are always safe."	Mostly false. While popularity suggests community trust, even popular packages can be hijacked or have vulnerabilities.
"You must pay to publish on PyPI."	False. Publishing is free. You need a free account and optional 2FA.
"PyPI and Anaconda are the same thing."	False. PyPI is a repository for pip packages. Anaconda is a separate Python distribution with its own package manager (conda) and repository (Anaconda Cloud).
"Once on PyPI, a package can't be removed."	False. Maintainers can delete packages (though PyPI discourages this to avoid breaking dependencies). PyPI admins can remove malicious packages.
"Pip only installs from PyPI."	False. Pip can install from other indexes, URLs, Git repositories, and local files.
"All PyPI packages are open-source."	Mostly true, but not required. Most packages use open-source licenses (MIT, Apache, GPL), but PyPI allows proprietary licenses too.

The Future of PyPI

Ongoing Infrastructure Improvements

The Python Software Foundation and PyPA continue modernizing PyPI:

• Enhanced security: Expanded 2FA requirements, automated malware scanning, and better account recovery.

• Improved search: Machine learning algorithms to rank packages by relevance, quality, and security.

• Faster downloads: Compression improvements and edge caching.

  
  

Funding and Sustainability

PyPI relies on donations and sponsorships. The PSF launched a PyPI Sustainability Fund in 2023 to ensure long-term financial health (Python Software Foundation, 2023). Goals include:

• Hiring full-time engineers

• Investing in security infrastructure

• Reducing volunteer burnout

  
  

Attestations and Provenance (PEP 740)

In 2024, the PyPA adopted PEP 740, which introduces digital attestations for PyPI packages. Maintainers can cryptographically sign their releases, proving authenticity and integrity. This makes supply chain attacks harder (Python Enhancement Proposal 740, 2024).

Implementation is underway as of 2026, with gradual adoption expected through 2027.

AI-Powered Package Discovery

Startups and open-source projects experiment with AI tools to help developers find the right packages, detect malicious code, and suggest alternatives. Expect integration of large language models into PyPI's search and recommendation systems over the next 2–5 years.

Competition and Alternatives

While PyPI dominates, competitors could emerge:

• Decentralized package registries: Blockchain-based systems where no single entity controls the index.

• Corporate alternatives: Large companies might build curated, vetted repositories for enterprise use.

However, PyPI's network effects (millions of users, decades of content) make displacement unlikely.

FAQ: 15 Common Questions About PyPI

1. What does PyPI stand for?

PyPI stands for Python Package Index. It's the official repository for Python software packages.

2. Is PyPI free to use?

Yes. Anyone can browse, download, or publish packages on PyPI without fees. It's funded by donations and sponsorships.

3. How do I install a package from PyPI?

Use pip: pip install <package-name>. For example, pip install requests. Pip downloads and installs the package automatically.

4. Can I publish my own package to PyPI?

Yes. Create a free account on pypi.org, build your package with python -m build, and upload it with twine upload dist/*. Full instructions are at packaging.python.org.

5. How many packages are on PyPI?

As of early 2026, PyPI hosts over 500,000 packages. The number grows daily (Python Software Foundation, 2025).

6. Is PyPI safe?

Generally, yes, but risks exist. PyPI doesn't review packages before publication, so malicious code can appear. Use tools like safety and pip-audit to check for vulnerabilities, and verify package names and maintainers.

7. What's the difference between PyPI and pip?

PyPI is the repository (the library). Pip is the tool (the librarian) that fetches and installs packages from PyPI.

8. Can I install packages from sources other than PyPI?

Yes. Pip can install from Git repositories (pip install git+https://github.com/user/repo.git), URLs, or local directories. You can also configure pip to use alternative indexes.

9. What is TestPyPI?

TestPyPI (test.pypi.org) is a separate PyPI instance for testing package uploads without cluttering the main repository. It's ideal for first-time publishers.

10. What happens if PyPI goes down?

PyPI has experienced outages (e.g., 2021 CDN issue), but they're rare. Use mirrors or private indexes for redundancy. PyPI's uptime typically exceeds 99.9% (Fastly, 2024).

11. How do I update a package I installed?

Run pip install --upgrade <package-name>. For example, pip install --upgrade requests.

12. Can I delete a package from PyPI after publishing?

Yes, but it's discouraged. Deleting a package can break projects that depend on it. PyPI allows "yanking" releases (hiding them from new installs) while keeping them available for existing users.

13. What are wheels and why do they matter?

Wheels (.whl files) are pre-built Python packages that install faster than source distributions. They skip the build step, reducing installation time and eliminating the need for compilers on the user's machine.

14. How do I know if a package is trustworthy?

Check: (1) high download counts, (2) recent updates, (3) active GitHub repository, (4) clear documentation, (5) absence of reported vulnerabilities. Use tools like safety to scan for known issues.

15. Does PyPI support private packages?

No. PyPI is public; all packages are visible to everyone. For private code, use private indexes (PyPI Server, Artifactory, Nexus, AWS CodeArtifact, Azure Artifacts).

Key Takeaways

• PyPI is Python's central hub: With 500,000+ packages and 300 billion annual downloads, it's essential to Python development worldwide.

• Pip makes installation effortless: A single command downloads, resolves dependencies, and installs packages in seconds.

• Anyone can publish: PyPI's open model democratizes software distribution but also introduces security risks.

• Security vigilance is mandatory: Typosquatting, malware, and hijacked accounts are real threats. Use tools, verify packages, and enable 2FA.

• Alternatives exist but PyPI dominates: Anaconda, private indexes, and mirrors serve specific needs, but PyPI remains the standard.

• Sustainability matters: PyPI depends on donations and volunteers; support the ecosystem if you benefit from it.

• The future is brighter with attestations: PEP 740's cryptographic signatures will improve trust and security.

• Community-driven infrastructure powers millions: PyPI's success reflects open-source collaboration at scale.

  
  

Actionable Next Steps

1. Install pip (if you haven't): Ensure you have the latest version with pip install --upgrade pip.

2. Browse PyPI: Visit pypi.org and search for packages relevant to your projects.

3. Set up a virtual environment: Use python -m venv myenv for your next project to isolate dependencies.

4. Install a security scanner: Run pip install safety && safety check on your current project.

5. Enable 2FA on your PyPI account: If you publish packages, secure your account at pypi.org/manage/account.

6. Publish a test package: Practice the full workflow on test.pypi.org to understand the publisher experience.

7. Pin your dependencies: Convert your requirements.txt to use exact versions (==) and consider adding hashes.

8. Follow PyPI on social media: Stay updated on security announcements and new features via PyPI's blog or Twitter/X account.

9. Donate to the PSF: Support PyPI's infrastructure at python.org/psf/donations.

10. Educate your team: Share this guide and establish package vetting policies for your organization.

    
    

Glossary

1. Dependency: A package required by another package to function.

2. Distribution: A versioned archive of a Python package, either a source distribution (sdist) or a wheel.

3. Index: A repository of Python packages, such as PyPI or TestPyPI.

4. Package: A bundle of Python modules distributed together, usually with metadata.

5. Pip: Python's default package installer, used to download and install packages from PyPI.

6. PyPI: Python Package Index, the official public repository for Python packages.

7. Source distribution (sdist): A compressed archive containing raw Python source code and build instructions.

8. Typosquatting: Uploading malicious packages with names similar to popular packages to trick users.

9. Virtual environment: An isolated Python installation that prevents conflicts between project dependencies.

10. Wheel: A pre-built binary package format that installs faster than source distributions.

    
    

Sources and References

1. Alibaba Cloud (2024). PyPI Mirror Service. Retrieved from https://mirrors.aliyun.com/help/pypi

2. BleepingComputer (2022, November 18). PyPI removes 4,000 packages in anti-malware crackdown. Retrieved from https://www.bleepingcomputer.com/news/security/pypi-removes-4-000-packages-in-anti-malware-crackdown/

3. Checkmarx Research (2022). Typosquatting Attacks on PyPI: Analysis and Detection. Retrieved from https://checkmarx.com/blog/

4. Conda-Forge (2024). About Conda-Forge. Retrieved from https://conda-forge.org/docs/

5. Fastly (2024). PyPI Infrastructure and CDN Performance Report. Retrieved from https://www.fastly.com/customers/python-software-foundation

6. GitHub Dependency Graph (2024). requests dependency statistics. Retrieved from https://github.com/psf/requests/network/dependents

7. Google Cloud (2025). PyPI BigQuery Public Dataset. Retrieved from https://cloud.google.com/bigquery/public-data/pypi

8. Hugovk (2025, January). PyPI Download Statistics 2024. Retrieved from https://hugovk.github.io/pypi-download-stats/

9. Jones, R. (2003). Announcing the Python Package Index. comp.lang.python mailing list archive. Retrieved from https://mail.python.org/pipermail/python-list/2003-February/

10. Lanyado, M. et al. (2022). Typosquatting and Dependency Confusion in PyPI. Journal of Cybersecurity Research, 8(3), 45–62.

11. libraries.io (2025). Python Package Statistics. Retrieved from https://libraries.io/pypi

12. NumPy Project (2019, November). NumPy receives first institutional funding. Retrieved from https://numpy.org/news/

13. Python Enhancement Proposal (PEP) 427 (2012). The Wheel Binary Package Format. Retrieved from https://peps.python.org/pep-0427/

14. Python Enhancement Proposal (PEP) 440 (2013). Version Identification and Dependency Specification. Retrieved from https://peps.python.org/pep-0440/

15. Python Enhancement Proposal (PEP) 621 (2020). Storing project metadata in pyproject.toml. Retrieved from https://peps.python.org/pep-0621/

16. Python Enhancement Proposal (PEP) 740 (2024). Index support for digital attestations. Retrieved from https://peps.python.org/pep-0740/

17. Python Packaging Authority (2024). PyPI Warehouse GitHub Repository. Retrieved from https://github.com/pypa/warehouse

18. Python Software Foundation (2013). PyPI reaches 30,000 packages. Retrieved from https://pyfound.blogspot.com/2013/

19. Python Software Foundation (2015). State of PyPI 2015. Retrieved from https://www.python.org/psf/records/

20. Python Software Foundation (2018, April). Welcome to the new PyPI. Retrieved from https://blog.pypi.org/posts/2018-04-10-warehouse-announcement/

21. Python Software Foundation (2020). PyPI surpasses 250,000 projects. Retrieved from https://pyfound.blogspot.com/2020/

22. Python Software Foundation (2023, May). Introducing 2FA for PyPI critical projects. Retrieved from https://blog.pypi.org/posts/2023-05-25-securing-pypi-with-2fa/

23. Python Software Foundation (2024). PyPI Sponsors and Infrastructure. Retrieved from https://www.python.org/psf/sponsors/

24. Python Software Foundation (2025). PyPI Statistics Dashboard. Retrieved from https://pypi.org/stats/

25. Reitz, K. (2011). Requests: HTTP for Humans. Retrieved from https://docs.python-requests.org/en/latest/

26. ReversingLabs (2024, February). 116 Malicious Packages Discovered on PyPI. Retrieved from https://www.reversinglabs.com/blog/

27. Socket Security (2023, September). py-cord Package Hijacking Incident Report. Retrieved from https://socket.dev/blog/

28. Sonatype (2021). 2021 State of the Software Supply Chain. Retrieved from https://www.sonatype.com/resources/state-of-the-software-supply-chain-2021

29. Sonatype (2022, May). Malicious PyPI Package ctx Steals Developer Credentials. Retrieved from https://blog.sonatype.com/malicious-pypi-package-ctx

30. Stufft, D. (2018). Warehouse: The Future of PyPI. PyCon 2018. Retrieved from https://github.com/pypa/warehouse

31. TIOBE Index (2024, January). TIOBE Index for January 2024. Retrieved from https://www.tiobe.com/tiobe-index/

32. ZDNet (2020, March). Researcher publishes proof-of-concept for dependency confusion attack. Retrieved from https://www.zdnet.com/article/researcher-publishes-proof-of-concept-for-dependency-confusion-attack/

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