Top 15 Most Downloaded Python Packages on PyPI and Their Uses
This article reviews the fifteen Python packages with the highest download counts on PyPI over the past year, explaining each library's purpose, key features, typical use‑cases, and providing code examples to illustrate how they simplify tasks such as HTTP requests, compatibility, cloud interaction, configuration, security, and data handling.
Today we share the Python packages that have received the most downloads on PyPI in the last year, describing their functions, relationships, and reasons for popularity.
1. urllib3 – 893 million downloads
urllib3 is an advanced HTTP client offering thread‑safety, connection pooling, SSL/TLS verification, multipart file upload, request retry, gzip/deflate support, and proxy handling. It is not a successor to the built‑in urllib; for core functionality you may use urllib.request . Most projects depend on it, so requests (listed later) is often preferred by end users.
2. six – 732 million downloads
six provides utilities to write code compatible with both Python 2 and Python 3, masking syntax differences (e.g., six.print_() works on both versions). The name comes from 2 × 3 = 6. Alternatives include future and the 2to3 conversion tool.
3. botocore, boto3, s3transfer, awscli
These AWS‑related packages rank high: botocore (660 million), s3transfer (584 million), awscli (394 million), boto3 (329 million). botocore is the low‑level core for boto3, which accesses S3, EC2, etc., and also powers the AWS CLI. s3transfer manages S3 transfers and is a dependency of boto3 and the CLI.
4. pip – 627 million downloads
pip is the standard Python package installer, allowing simple commands like pip install package and pip uninstall package . It works with requirements.txt and virtual environments to create isolated environments.
5. python-dateutil – 617 million downloads
Extends the standard datetime module with powerful parsing capabilities. Example:
<code>from dateutil.parser import parse
logline = "INFO 2020-01-01T00:00:01 Happy new year, human."
timestamp = parse(logline, fuzzy=True)
print(timestamp) # 2020-01-01 00:00:01</code>6. requests – 611 million downloads
Built on urllib3, requests makes HTTP calls extremely easy. Example:
<code>import requests
r = requests.get("https://api.github.com/user", auth=(user, pass))
print(r.status_code) # 200
print(r.headers["content-type"]) # application/json; charset=utf8
print(r.text)
print(r.json())</code>7. s3transfer – 552 million downloads
Manages S3 transfers; its API may change between minor versions, so pinning a version is recommended.
8. certifi – 552 million downloads
Provides a curated bundle of root SSL certificates, allowing Python code to verify HTTPS connections just like browsers do.
9. idna – 527 million downloads
Implements the IDNA protocol for internationalized domain names. Example:
<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
YAML parser and emitter for Python, enabling easy read/write of YAML files and automatic type conversion, unlike the limited ConfigParser . <code>config["section"]["my_int"]</code>
11. pyasn1 – 512 million downloads
Pure‑Python implementation of ASN.1 and DER/BER/CER encoding, used in many security protocols (TLS, SNMP, LDAP, etc.).
12. docutils – 508 million downloads
Converts plain text (reStructuredText) to formats like HTML, XML, LaTeX. It powers PEP documentation and Sphinx, which many projects use for documentation.
13. chardet – 501 million downloads
Detects character encoding of byte streams. Command‑line usage:
<code>chardetect somefile.txt
# somefile.txt: ascii with confidence 1.0</code>14. rsa – 492 million downloads
Pure‑Python RSA implementation supporting encryption, decryption, signing, and PKCS#1 v1.5 key generation. Example:
<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
Provides a declarative way to query JSON‑like data structures. Example:
<code>import jmespath
d = {"foo": {"bar": "baz"}}
print(jmespath.search('foo.bar', d)) # baz
</code>These packages illustrate the diverse needs of Python developers, from HTTP communication and cloud services to data parsing, configuration, security, and documentation.
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