easyfasta 1.1.63

A lightweight Python library for efficient FASTA file parsing and DNA sequence manipulation.

Easy Fasta

A lightweight functional Python library for efficient FASTA file parsing and DNA sequence manipulation. No OOP bloat, only data.

Features

• Memory-efficient parsing: Stream through large FASTA files without loading everything into memory
• Random access: Jump directly to specific sequences with position tracking
• FAI indexing: Build and query standard .fai index files for fast random access
• Sequence extraction: Filter sequences by identifiers
• DNA manipulation: Complete IUPAC-compliant complement and reverse complement operations
• Formatting: Convert sequences to multi-line FASTA format
• Does not validate input: users are responsible to provide correctly formatted files.

Installation

python 3.8+

> pip install easyfasta

or simply copy the module to your project

Quick Start

from easyfasta import *

# Parse FASTA file sequence by sequence (memory efficient)
with open('sequences.fasta') as f:
    for header, sequence in fasta_iter(f):
        print(f">{header}")
        print(sequence[:50])  # First 50 bases

# Load entire FASTA into dictionary
sequences = load_fasta('sequences.fasta')
print(sequences['sequence_id'])

# Extract specific sequences
target_ids = ['seq1', 'seq2', 'seq3']
found = get_sequence_id('sequences.fasta', target_ids)
for header, seq in found:
    print(f"Found: {header}")

# Extract specific sequences using a dictionary index
index = build_dico_index('sequences.fasta')
# using pickle you can save and load the index
#import pickle
#pickle.dump(index, "save_index_file.pkl")
#index = pickle.load("save_index_file.pkl")
target_ids = ['seq1', 'seq2', 'seq3']
found = get_sequence_dico_index('sequences.fasta', target_ids, index, ignore_unfound=True)
for header, seq in found:
    print(f"Found: {header}")

# FAI index for fast random access
build_index('sequences.fasta')  # creates sequences.fasta.fai
index = load_index('sequences.fasta')  # load into memory for repeated queries
seq = query('sequences.fasta', 'seq1', 0, 100, strand='+', dico_index=index)

# DNA manipulation
dna = "ATCGGTAA"
print(complement(dna))           # TAGCCATT
print(reverse_complement(dna))   # TTACCGAT

API Reference

Parsing Functions

fasta_iter(open_file: TextIO) -> Generator[tuple[str, str], None, None]

Memory-efficient iterator over FASTA sequences.

with open('large_file.fasta') as f:
    for header, sequence in fasta_iter(f):
        # Process one sequence at a time
        process_sequence(header, sequence)

load_fasta(fasta_path: str|Path) -> dict[str, str]

Load entire FASTA file into a dictionary mapping sequence IDs to sequences.

sequences = load_fasta('sequences.fasta')
my_sequence = sequences['sequence_id']

get_sequence_id(fasta_file: str|Path, identifiers: Iterable[str], identifier_only: bool = True) -> list[tuple[str, str]]

Extract sequences matching specific identifiers.

• identifier_only: If True, match only the first part of headers (before whitespace)

wanted = ['seq1', 'seq2']
results = get_sequence_id('sequences.fasta', wanted)

Dictionary Index Functions

build_dico_index(fasta_file: str|Path) -> dict[str, int]

Build an in-memory index as a dictionary mapping sequence identifiers to their byte position in the file.

index = build_dico_index('sequences.fasta')

get_sequence_dico_index(fasta_file: str|Path, identifiers: Iterable[str], index_dict: dict[str, int], ignore_unfound: bool = True) -> list[tuple[str, str]]

Use a dictionary index to retrieve sequences faster than parsing through the file.

index = build_dico_index('sequences.fasta')
wanted = ['seq1', 'seq2']
results = get_sequence_dico_index('sequences.fasta', wanted, index)

FAI Index Functions

build_index(fasta: str|Path) -> None

Build a standard .fai index file next to the fasta file. Required before using load_index or query.

build_index('sequences.fasta')  # creates sequences.fasta.fai

load_index(fasta: str|Path) -> dict[str, list]

Load a .fai index file into memory for repeated queries.

index = load_index('sequences.fasta')

query(fasta: str|Path, name: str, start: int, end: int, strand: str = "+", dico_index: dict = None) -> str

Query a fasta file for a sequence by name and coordinates using the FAI index. Returns the reverse complement if strand is "-".

build_index('sequences.fasta')
index = load_index('sequences.fasta')
seq = query('sequences.fasta', 'chr1', 1000, 2000, strand='+', dico_index=index)

Sequence Manipulation

complement(seq: str) -> str

Return the complement of a DNA sequence (A↔T, C↔G, supports all IUPAC codes).

reverse(seq: str) -> str

Return the reverse of a sequence.

reverse_complement(seq: str) -> str

Return the reverse complement of a DNA sequence.

wrap_sequence(sequence: str, chunk_size: int = 80) -> str

Format sequence with line breaks every chunk_size characters (standard multiline FASTA format).

formatted = wrap_sequence("ATCGATCGATCG" * 10, 60)
print(formatted)  # 60 characters per line
# write to a file
with open(out_file, 'w') as fo:
   fo.write(">{}\n{}\n".format('seq_id', wrap_sequence("ATCGATCGATCG" * 10, 80)))

Migration Guide: 1.0.14 → 1.1.0

Version 1.1.0 introduces FAI index support and contains breaking changes.

Breaking Changes

1.0.14	1.1.0	Notes
build_index()	build_dico_index()	build_index() now builds a .fai file, not a dictionary
get_sequence_index()	get_sequence_dico_index()	straight rename

New in 1.1.0

• build_index() — builds a standard .fai index file
• load_index() — loads a .fai index into memory
• query() — fast random access to any sequence region by coordinates

What you need to change

# 1.0.14
index = build_index('sequences.fasta')
results = get_sequence_index('sequences.fasta', ids, index)

# 1.1.0
index = build_dico_index('sequences.fasta')
results = get_sequence_dico_index('sequences.fasta', ids, index)

⚠️ Important: build_index() no longer returns a dictionary. Calling it expecting a dictionary index will silently produce wrong results. Use build_dico_index() instead.

Design Philosophy

This library prioritizes:

• Memory efficiency: Built for large genomic files that don't fit in RAM
• Simplicity: Clean, predictable API with minimal dependencies. Not OOP bloat, only data.
• Performance: Stream-based processing with O(1) memory usage for parsing
• Standards compliance: Full IUPAC nucleotide code support

Use Cases

• Processing large fasta files (metagenome)
• Common DNA sequence manipulation
• Common operations on fasta including parsing, indexing and sequence retrieval
• Bioinformatics workflows requiring memory efficiency

Requirements

• Python 3.8+
• No external dependencies

License

MIT

Contributing

Feel free to ask for new features. I published it as lightweight because those are the features I use the most and wanted to start with a solid foundation.

I used this library for years, and it has been extensively tested. As such I will only address issues that come with a minimal reproducible problem.