Top Downloaded Python Packages on PyPI and Their Uses

Today I share the most downloaded Python packages on PyPI in the past year, explaining their purpose, relationships, and why they are popular.

1. urllib3: 893 million downloads

Urllib3 is an HTTP client for Python offering features not in the standard library, such as thread safety, connection pooling, SSL/TLS verification, multipart file upload, request retry, gzip/deflate support, and proxy handling.

Although named urllib3, it is not a successor to urllib2; for core functionality you may use urllib.request.

For end users, the requests library is recommended; urllib3 ranks first because about 1,200 packages depend on it.

2. six: 732 million downloads

Six provides compatibility utilities between Python 2 and Python 3, masking syntax differences (e.g., six.print_()). The name comes from 2×3=6. Similar libraries include future; for code conversion see 2to3.

Although popular, the author encourages dropping Python 2 support since it reached end‑of‑life on 2020‑01‑01.

3. botocore, boto3, s3transfer, awscli

These AWS‑related projects are listed together:

botocore – 660 million downloads (rank 3)

s3transfer – 584 million downloads (rank 7)

awscli – 394 million downloads (rank 17)

boto3 – 329 million downloads (rank 22)

Botocore is the low‑level AWS interface and the foundation for boto3 and the AWS CLI. s3transfer manages S3 transfers and is a dependency of many AWS libraries.

4. pip: 627 million downloads

Pip is the standard Python package installer. It can install packages from PyPI or other indexes, uninstall them, and handle requirement files. Combined with virtualenv it creates isolated environments.

5. python-dateutil: 617 million downloads

Dateutil extends the standard datetime module, enabling flexible parsing such as fuzzy date extraction from log lines.

<code>from dateutil.parser import parse

logline = "INFO 2020-01-01T00:00:01 Happy new year, human."
timestamp = parse(log_line, fuzzy=True)
print(timestamp)  # 2020-01-01 00:00:01</code>

6. requests: 611 million downloads

Requests builds on urllib3 to provide a simple API for HTTP requests.

<code>import requests

r = requests.get("https://api.github.com/user", auth=(user, pass))
print(r.status_code)   # 200
print(r.headers["content-type"])
print(r.text)
print(r.json())</code>

7. s3transfer

See entry 3 for details.

8. certifi: 552 million downloads

Certifi supplies a curated collection of root CA certificates, allowing Python to verify SSL/TLS connections similarly to browsers.

9. idna: 527 million downloads

Idna implements the Internationalised Domain Names in Applications (IDNA) protocol, providing encode/decode functions for non‑ASCII domain names.

<code>import idna
print(idna.encode("ドメイン.テスト"))  # b'xn--eckwd4c7c.xn--zckzah'
print(idna.decode("xn--eckwd4c7c.xn--zckzah"))  # ドメイン.テスト</code>

10. PyYAML: 525 million downloads

PyYAML parses and emits YAML, a human‑friendly data serialization format, supporting complex data types and nested structures.

11. pyasn1: 512 million downloads

pyasn1 provides a pure‑Python implementation of ASN.1 types and DER/BER/CER encoding, used in many security protocols such as TLS certificates.

12. docutils: 508 million downloads

Docutils converts reStructuredText documents to formats like HTML, XML, and LaTeX; it powers Python’s PEP documentation and tools like Sphinx.

13. chardet: 501 million downloads

Chardet detects the character encoding of byte streams, useful for processing unknown text data.

<code>chardetect somefile.txt
# output: somefile.txt: ascii with confidence 1.0</code>

14. rsa: 492 million downloads

RSA is a pure‑Python implementation of the RSA algorithm, supporting encryption, decryption, signing, and key generation.

<code>import rsa

(bob_pub, bob_priv) = rsa.newkeys(512)
crypto = rsa.encrypt("hello Bob!", bob_pub)
message = rsa.decrypt(crypto, bob_priv)
print(message.decode("utf8"))  # hello Bob!</code>

15. jmespath: 473 million downloads

JMESPath provides a declarative query language for extracting data from JSON structures in Python.

<code>import jmespath

d = {"foo": {"bar": "baz"}}
print(jmespath.search("foo.bar", d))  # baz
</code>

The article concludes with QR codes and links to free Python courses and additional reading.