cbor
RFC 7049 - Concise Binary Object Representation
Decision gist · record as of 2026-08-14
No—unless you have a specific requirement to work with existing CBOR data or systems. The package is abandoned (last release 2016-02-09) with no active maintenance. High installation friction combined with zero active maintenance makes this a poor choice for new projects.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a C compiler and development headers to build the C extension during installation.
- Installation requires compilation of C extensions (high friction).
- The package is abandoned—last release was 2016-02-09, with no active maintenance or repository activity visible.
License · maintenance · safety
Apache (permissive) — Licensed under Apache (permissive), allowing commercial and private use with minimal restrictions. No notable licensing constraints for typical use.
last release 2016-02-09 (3839 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 818,221 downloads/mo, #4,982 on PyPI
Alternatives
Verify before relying
import cbor
data = {'key': 'value'}
encoded = cbor.dumps(data)
decoded = cbor.loads(encoded)- Whether the C implementation still provides claimed 3-5× speedup over modern JSON libraries
- Compatibility with Python versions beyond 3.5 (classifiers list only 2.7, 3.4, 3.5)
- Whether the pure-Python fallback works reliably if C compilation fails
- Active maintained alternatives and their relative performance
What it is and what it does
cbor is a Python implementation of RFC 7049, the CBOR binary serialization standard. It provides two main functions—cbor.loads() and cbor.dumps()—to convert Python objects to and from CBOR's compact binary format. The package includes both a C implementation and a pure Python implementation.
CBOR is designed as a binary alternative to JSON: it supports JSON's data types plus additional structures, serializes to smaller payloads, and parses faster. The package is useful when you need efficient binary interchange with systems that speak CBOR, or when payload size and parsing speed matter more than human readability.
Use it for
- Serialize structured data for transmission over bandwidth-constrained or latency-sensitive networks
- Implement CBOR support in applications that must interoperate with IoT or embedded systems using RFC 7049
- Store compact binary representations of Python objects in databases or files where size efficiency is important
- Build APIs or protocols that require binary encoding with JSON-like flexibility
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No—unless you have a specific requirement to work with existing CBOR data or systems.
The package is abandoned (last release 2016-02-09) with no active maintenance. High installation friction combined with zero active maintenance makes this a poor choice for new projects.
Install
cbor on PyPI
Before you install
Installation requires compilation of C extensions (high friction). The package is abandoned—last release was 2016-02-09, with no active maintenance or repository activity visible. Use only if you have specific compatibility needs with existing CBOR data.
Requires a C compiler and development headers to build the C extension during installation.
License in practice
Licensed under Apache (permissive), allowing commercial and private use with minimal restrictions. No notable licensing constraints for typical use.
Quickstart
import cbor
data = {'key': 'value'}
encoded = cbor.dumps(data)
decoded = cbor.loads(encoded)
Verify before relying
- Whether the C implementation still provides claimed 3-5× speedup over modern JSON libraries
- Compatibility with Python versions beyond 3.5 (classifiers list only 2.7, 3.4, 3.5)
- Whether the pure-Python fallback works reliably if C compilation fails
- Active maintained alternatives and their relative performance
Package facts
| License | Apache permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Abandoned 3,839 days since the last release |
| First released | |
| Downloads | 818,221 / month, #4,982 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: CProgramming Language :: Python :: 2.7Programming Language :: Python :: 3.4Programming Language :: Python :: 3.5Topic :: Software Development :: Libraries :: Python Modules |
Evidence: cbor-1.0.0.tar.gz
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “binary object representation”
- cborSerializes and deserializes data in CBOR (Concise Binary Object…
- borsh-constructImplements the Borsh binary serialization format for Python, enabling…
- cbor2Encodes and decodes CBOR (Concise Binary Object Representation) data…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also cbor2 · zcbor · prison · paradict · borsh-construct · pyiso8583 · rfc8785 · jcs · avro-python3 · rison