prseq 0.0.19

Python tools (backed by Rust) for sequence analysis

prseq (Python)

Python tools for sequence analysis, powered by Rust.

Overview

prseq provides Python bindings to a high-performance Rust library for FASTA and FASTQ parsing. It includes:

• Pythonic API: Full type hints and Python-native data structures
• CLI Tools: Ready-to-use command-line utilities
• Rust Performance: Fast parsing with automatic compression detection
• Memory Efficient: Streaming parsers for large files
• Universal Input: Files, compressed files, and stdin support

The core parsing is implemented in the Rust prseq library.

Installation

Using uv (recommended)

uv add prseq

Using pip

pip install prseq

From source (developers)

git clone https://github.com/VirologyCharite/prseq.git
cd prseq/python
pip install maturin
maturin develop

Quick Start

Command Line Tools

# Analyze a FASTA file
fasta-info sequences.fasta
fasta-stats sequences.fasta.gz  # Works with compressed files
fasta-filter 100 sequences.fasta  # Keep sequences ≥100bp

# Analyze a FASTQ file
fastq-info reads.fastq
fastq-stats reads.fastq.bz2
fastq-filter 50 reads.fastq  # Keep sequences ≥50bp

# All tools support stdin
cat sequences.fasta | fasta-stats
gunzip -c reads.fastq.gz | fastq-filter 75

Python API

import prseq

# FASTA files
records = prseq.read_fasta("sequences.fasta")
for record in records:
    print(f"{record.id}: {len(record.sequence)} bp")

# FASTQ files
records = prseq.read_fastq("reads.fastq")
for record in records:
    print(f"{record.id}: {len(record.sequence)} bp, quality: {len(record.quality)}")

# Streaming for large files
for record in prseq.FastaReader.from_file("large.fasta"):
    if len(record.sequence) > 1000:
        print(f"Long sequence: {record.id}")

# Works with stdin too
for record in prseq.FastqReader.from_stdin():
    print(f"Read: {record.id}")

Python API Reference

FASTA Support

from prseq import FastaRecord, FastaReader, read_fasta

# FastaRecord - represents a single sequence
record = FastaRecord(id="seq1", sequence="ATCG")
print(record.id)        # "seq1"
print(record.sequence)  # "ATCG"

# Read all records into memory
records = read_fasta("file.fasta")
records = read_fasta("file.fasta.gz")  # Auto-detects compression
records = read_fasta(None)  # Read from stdin

# Stream records (memory efficient)
reader = FastaReader.from_file("large.fasta")
reader = FastaReader.from_stdin()

for record in reader:
    # Process one record at a time
    print(f"{record.id}: {len(record.sequence)}")

# Performance tuning
reader = FastaReader.from_file("file.fasta", sequence_size_hint=50000)

FASTQ Support

from prseq import FastqRecord, FastqReader, read_fastq

# FastqRecord - represents a single read
record = FastqRecord(id="read1", sequence="ATCG", quality="IIII")
print(record.id)        # "read1"
print(record.sequence)  # "ATCG"
print(record.quality)   # "IIII"

# Read all records into memory
records = read_fastq("reads.fastq")
records = read_fastq("reads.fastq.bz2")  # Auto-detects compression
records = read_fastq(None)  # Read from stdin

# Stream records (memory efficient)
reader = FastqReader.from_file("large.fastq")
reader = FastqReader.from_stdin()

for record in reader:
    # Validate quality length matches sequence
    assert len(record.sequence) == len(record.quality)
    print(f"{record.id}: {len(record.sequence)} bp")

# Performance tuning for short/long reads
reader = FastqReader.from_file("reads.fastq", sequence_size_hint=150)  # Short reads
reader = FastqReader.from_file("nanopore.fastq", sequence_size_hint=10000)  # Long reads

Advanced Usage

import prseq

# Filter sequences by length
def filter_by_length(filename, min_length):
    for record in prseq.FastaReader.from_file(filename):
        if len(record.sequence) >= min_length:
            yield record

# Calculate GC content
def gc_content(sequence):
    gc_count = sequence.upper().count('G') + sequence.upper().count('C')
    return gc_count / len(sequence) if sequence else 0

# Process compressed files
records = prseq.read_fasta("sequences.fasta.gz")
avg_gc = sum(gc_content(r.sequence) for r in records) / len(records)

# Convert FASTQ to FASTA
def fastq_to_fasta(fastq_file, fasta_file):
    with open(fasta_file, 'w') as f:
        for record in prseq.FastqReader.from_file(fastq_file):
            f.write(f">{record.id}\n{record.sequence}\n")

CLI Tools

FASTA Tools

Command	Description	Example
fasta-info	Show basic file information	fasta-info sequences.fasta
fasta-stats	Calculate sequence statistics	fasta-stats sequences.fasta.gz
fasta-filter	Filter by minimum length	fasta-filter 100 sequences.fasta

FASTQ Tools

Command	Description	Example
fastq-info	Show basic file information	fastq-info reads.fastq
fastq-stats	Calculate sequence statistics	fastq-stats reads.fastq.bz2
fastq-filter	Filter by minimum length	fastq-filter 50 reads.fastq

CLI Examples

# Basic usage
fasta-info genome.fasta
fastq-stats reads.fastq

# With compressed files (auto-detected)
fasta-stats sequences.fasta.gz
fastq-info reads.fastq.bz2

# Using stdin (great for pipelines)
cat sequences.fasta | fasta-stats
gunzip -c reads.fastq.gz | fastq-filter 100

# Performance tuning for large sequences
fasta-stats --size-hint 50000 genome.fasta
fastq-filter --size-hint 10000 150 nanopore.fastq

Development

Prerequisites

• Python 3.8-3.12
• Rust 1.70+
• maturin for building Python extensions

Setup

cd python
pip install maturin
maturin develop

Testing

# Run all tests
python -m pytest tests/ -v

# Run integration tests
python -m pytest tests/ -v --integration

# Type checking with MyPy
mypy src/prseq

Building

# Development build
maturin develop

# Production wheel
maturin build --release

Publishing

cd python
maturin publish

Type Checking

The package includes full type hints and is configured for MyPy with Python 3.8+ compatibility. Type stubs are automatically generated for the Rust extension modules.

Rust Core

The Python package is built on top of the Rust prseq library, which provides the high-performance parsing implementation. If you need Rust-native parsing without Python, check out the Rust crate directly.

Links

• Main Project README - Project overview, features, and performance benchmarks
• Rust Library README - Rust API documentation
• PyPI
• GitHub Repository

License

This project is licensed under the MIT License - see the LICENSE file for details.