Skip to main content

fastx-barber

DOI Release ID Release date
PyPI - Python Version PyPI - Status GitHub Actions Python package status
license Code size
Watch no. Stars no.

PyPi | docs

A Python3.8+ package to trim and extract flags from FASTA and FASTQ files.

Features (in short)

  • Works on both FASTA and FASTQ files.
  • Selects reads based on a pattern (regex).
  • Trims reads by pattern (regex), length, or single-base quality.
  • Extracts parts (flags) of reads based on a pattern and stores them in the read headers.
  • Generates BED file with the locations of a substring in FASTX records.
  • Regular expression support fuzzy matching (fuzzy matching might affect the barber's speed).
  • Parallelizes processing by splitting the fastx file in chunks.

For more available features, check out our docs!

Requirements

fastx-barber has been tested with Python 3.8 and 3.9. We recommend installing it using pipx (see below) to avoid dependency conflicts with other packages. The packages it depends on are listed in our dependency graph. We use poetry to handle our dependencies.

Install

We recommend installing fastx-barber using pipx. Check how to install pipx here if you don't have it yet!

Once you have pipx ready on your system, install the latest stable release of fastx-barber by running: pipx install fastx-barber. If you see the stars (✨ 🌟 ✨), then the installation went well!

Usage

Run:

  • fbarber to access the barber's services.
  • fbarber find_seq to extract the locations of a sequence (e.g., restriction site) in FASTX records.
  • fbarber flag to extract or manipulate read flags.
  • fbarber match to select reads based on a pattern (regular expression).
  • fbarber trim to trim your reads.

Add -h to see the full help page of a command!

Contributing

We welcome any contributions to fastx-barber. In short, we use black to standardize code format. Any code change also needs to pass mypy checks. For more details, please refer to our contribution guidelines if this is your first time contributing! Also, check out our code of conduct.

License

MIT License - Copyright (c) 2020-21 Gabriele Girelli

Metadata

Release files for fastx-barber 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fastx-barber 0.1.5
File Size Uploaded Provenance
fastx-barber-0.1.5.tar.gz 30.0 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for fastx-barber 0.1.5
File Interpreter ABI Platform
fastx_barber-0.1.5-py3-none-any.whl Python 3 none any Details

Total release size: 80.9 kB

Release files / fastx-barber-0.1.5.tar.gz

Download URL fastx-barber-0.1.5.tar.gz
Size 30.0 kB
Tags Source
SHA-256 checksum
How to use checksums
4b65e983e6e71ac99165f5f35c9c300b7c3de695ede7e74eca702d065504911d
BLAKE2b-256 checksum
How to use checksums
2c3111d64d853043b60c0d232b70521f55bea0dd39b895fc43f26fa78d2ff806
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.1.5 CPython/3.8.5 Linux/5.4.0-74-generic

Release files / fastx_barber-0.1.5-py3-none-any.whl

Download URL fastx_barber-0.1.5-py3-none-any.whl
Size 50.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
cebb25b76fc27cf89c328783d80981ace5cc32083459cc2414f2abc073f12e8c
BLAKE2b-256 checksum
How to use checksums
58a8acdc794e274da5f0b4b64c3cac1ced35191dfbe5a107e5fe8c4f7f12f283
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.1.5 CPython/3.8.5 Linux/5.4.0-74-generic

Security for fastx-barber 0.1.5

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page