{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/4"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/12"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"},{"label":"Chemistry","url":"https://skillfed.io/packages/category/scientific-engineering-chemistry"}],"enrichment":{"capability":"alchemlyb parses molecular dynamics simulation output, extracts uncorrelated samples from timeseries data, and estimates free energies using MBAR, BAR, and thermodynamic integration methods.","skillfed_tags":["computational-chemistry","molecular-dynamics","free-energy"],"use_cases":["Extract and analyze free energy differences from GROMACS, AMBER, or NAMD simulations using MBAR or BAR estimators.","Detect equilibration in molecular dynamics trajectories and subsample to obtain independent, uncorrelated configurations for downstream analysis.","Compute free energies via thermodynamic integration from alchemical simulation data.","Parse and standardize output from multiple MD engines into a common pandas-based data structure for comparative analysis.","Automate post-processing of alchemical free energy perturbation (FEP) calculations in high-throughput workflows."],"what_it_does":"alchemlyb is a Python library for analyzing alchemical free energy calculations from molecular dynamics simulations. It sits atop the PyData stack (numpy, pandas, scipy, scikit-learn, matplotlib) and provides three main layers: parsers that extract raw data from output files of common MD engines (GROMACS, AMBER, NAMD, and others), subsamplers that extract uncorrelated and equilibrated samples from timeseries data using techniques like those in pymbar, and estimators that compute free energies directly using best-practices methods including multistate Bennett acceptance ratio (MBAR), BAR, and thermodynamic integration (TI).\n\nThe package is designed for computational chemists and molecular dynamics practitioners who need to post-process simulation output and extract thermodynamic quantities. It abstracts away the boilerplate of parsing heterogeneous file formats and handling statistical correlation in timeseries, letting users focus on the analysis and interpretation of results. The library is actively maintained, supports modern Python versions (3.11\u20133.14), and has no compiled dependencies.","worth_installing":"Yes. alchemlyb is actively maintained, has no known vulnerabilities, carries a permissive BSD-3-Clause license, and requires only standard PyData stack dependencies (low install friction). It is purpose-built for a specific, well-defined task\u2014free energy analysis from MD simulations\u2014and does it with established statistical methods. Install it if you work with alchemical free energy calculations; skip it if you do not."},"id":"alchemlyb","links":{"html":"https://skillfed.io/packages/alchemlyb","md":"https://skillfed.io/packages/alchemlyb.md","pypi":"https://pypi.org/project/alchemlyb/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-10-22","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"alchemlyb","python_support":"supports_current","summary":"the simple alchemistry library"},"popularity":{"monthly_downloads":392931,"position":7002,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.5.0"}