{"categories":[{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"cyvcf2 is a Cython wrapper around htslib that parses VCF and BCF genomic variant files at speed, including region-based queries, and returns numpy arrays for immediate downstream analysis.","skillfed_tags":["bioinformatics","genomics","vcf-parsing"],"use_cases":["Filter variants by allele frequency or quality thresholds extracted from INFO fields and genotype depths.","Extract genotype matrices or depth arrays from large VCF files for population genetics or association studies.","Query specific genomic regions in indexed VCF/BCF files without loading the entire file into memory.","Convert VCF records to numpy arrays for downstream machine learning or statistical analysis pipelines.","Rapidly scan VCF files from the command line to inspect headers, sample counts, or variant statistics."],"what_it_does":"cyvcf2 is a high-performance Python interface to VCF and BCF genomic variant files, built as a Cython wrapper around the C library htslib. It parses variant records and returns their attributes\u2014chromosome, position, reference and alternate alleles, genotypes, depths, and custom INFO/FORMAT fields\u2014as numpy arrays ready for immediate analysis. The package supports region-based queries on indexed files and works with Python 3.9 and later.\n\nTypical use involves iterating over variants in a file, extracting genotype or depth information as numpy arrays, and filtering or aggregating them downstream. A key design detail is that numpy arrays returned by attributes like `gt_ref_depths` are backed by the underlying C data structure, so they become invalid once the variant object goes out of scope; users must explicitly copy arrays they wish to persist. The package includes a command-line tool for basic VCF inspection and filtering.","worth_installing":"Yes. cyvcf2 is actively maintained, widely used in bioinformatics, has no known vulnerabilities, and offers permissive licensing. Binary wheels make installation frictionless for most users. Install it if you need to parse VCF or BCF files in Python and want speed and direct numpy integration; avoid it only if you cannot tolerate the C compiler requirement for source builds or the array-lifetime gotcha."},"id":"cyvcf2","links":{"html":"https://skillfed.io/packages/cyvcf2","md":"https://skillfed.io/packages/cyvcf2.md","pypi":"https://pypi.org/project/cyvcf2/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-25","license_spdx":null,"license_treatment":"permissive","name":"cyvcf2","python_support":"supports_current","summary":"fast vcf parsing with cython + htslib"},"popularity":{"monthly_downloads":217227,"position":9361,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.34.0"}