# kbandla/dpkt

fast, simple packet creation / parsing, with definitions for the basic TCP/IP protocols

Repository: https://github.com/kbandla/dpkt
Canonical: https://ross.abutalabs.com/products/dpkt
Language: Python
License: NOASSERTION
License Family: other
Last push: 2024-07-26T04:11:43+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5201, "days_push": 768, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1159, forks 273 (observed 2026-08-28T04:03:48.644940+00:00)

## What it is
dpkt is a Python library for fast, simple network packet creation and parsing, with definitions for basic TCP/IP protocols. It is commonly used to decode pcap files and raw packet captures for network analysis and security research.

## Use cases
- parse pcap files in python
- decode tcp/ip packets from a capture
- build custom network packets programmatically
- analyze network traffic for security research
- extract http or dns requests from packet captures

## When to choose
- you need fast, low-level packet parsing in pure Python
- you want to decode pcap captures without external tools
- you need to construct or dissect TCP/IP protocol headers

## When to avoid
- you need live packet capture or injection (use scapy instead)
- you need high-level protocol analysis or GUI tooling
- you need actively developed features or frequent updates

## Facets
- artifact type: library
- maturity: maintenance
- function: parser, networking, serialization
- domain: networking, security, developer-tools
- platform: python, cross-platform
- tags: packet-parsing, pcap, tcp-ip, network-forensics, protocol-decoding

## Member repositories
- kbandla/dpkt (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.644940+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:31:54.177583+00:00, confidence not recorded.
  - readme: https://github.com/kbandla/dpkt (fetched 2026-08-28T04:03:48.644940+00:00, sha a3febf53be7c)
  - registry_pypi: https://pypi.org/pypi/dpkt/json (fetched 2026-08-29T12:36:34.481247+00:00, sha b82e8e9740d9)
- Data as of 2026-08-30T08:39:29.467469+00:00.