Packages
Client library for the Firecrawl API that scrapes, crawls, and searches the web, returning clean Markdown or structured data; also indexes research papers from PubMed, bioRxiv, medRxiv, and arXiv.
Pydicom reads, modifies, and writes DICOM medical imaging files in pure Python, with optional NumPy support for pixel data as arrays.
Install it if you work with medical imaging data, DICOM files, or healthcare IT systems.
PubChemPy is a Python wrapper around the PubChem REST API that lets you search for chemical compounds by name, substructure, or similarity, retrieve their properties, and convert between chemical file formats.
Install it if you need programmatic access to PubChem data.
VTK is a 3D graphics, image processing, and visualization toolkit that provides algorithms for surface reconstruction, volume rendering, and advanced rendering techniques.
PyHMMER provides Python bindings to HMMER3, a biological sequence analysis tool that uses profile hidden Markov models to search for sequence homologs in protein or DNA databases.
A Python SDK for web scraping, crawling, searching, and extracting structured data from websites and research papers via the Firecrawl API, returning results as clean Markdown, HTML, or typed objects.
SimpleITK provides a simplified Python interface to the Insight Toolkit (ITK) for performing image segmentation, registration, and general filtering operations on 2D, 3D, and 4D images.
Parses HL7 version 2.x medical messages into Python objects for programmatic access to healthcare data fields and segments.
MONAI is a PyTorch-based framework for building deep learning models on medical imaging data, providing pre-processing, network architectures, loss functions, and evaluation metrics tailored to healthcare applications.
HDMF provides APIs for defining hierarchical data models, reading and writing data to storage backends like HDF5, and representing structured data as Python objects.
Install it if you need to define, validate, and serialize hierarchical scientific data with schema enforcement.
cwltool is the reference implementation of the Common Workflow Language standard, enabling you to write, validate, and execute portable scientific workflows defined in CWL format across different computing environments.
Install it if you need to execute portable workflows, validate CWL definitions, or integrate CWL workflows into Python applications.
Decodes and encodes JPEG, JPEG-LS, JPEG 2000, and RLE image formats, primarily for use with DICOM medical imaging data.
Install only if you also install at least one format-specific plugin; the base package alone cannot decode or encode.
PyNWB provides a high-level Python API for reading, writing, and working with neurophysiology data stored in the NWB (Neurodata Without Borders) format, a unified standard for cellular-based neural recordings.
Install it if you work with neurophysiology data and need interoperability with the NWB ecosystem or plan to share data with other labs.
Decodes JPEG and JPEG-LS images to NumPy arrays, with support for multiple DICOM transfer syntaxes and integration with pylibjpeg and pydicom.
Converts DICOM medical imaging files to NIfTI format, supporting anatomical CT/MR scans and vendor-specific 4D imaging (fMRI, DTI) with optional resampling and reorientation.
itk-core provides Python bindings to the Insight Toolkit's core image processing and analysis algorithms, enabling N-dimensional image segmentation, registration, and scientific image manipulation.
itk-filtering provides Python bindings for ITK's N-dimensional image filtering algorithms, enabling medical image processing operations like smoothing, edge detection, and morphological transformations.
Install it if you need ITK filtering operations in Python; the binary wheels reduce friction.
itk-numerics provides Python bindings for ITK's N-dimensional image processing, segmentation, and registration algorithms, focusing on the numerical computation core.
itk-io provides Python bindings for reading and writing medical and scientific image files in multiple formats as part of the Insight Toolkit ecosystem.
Decodes and encodes JPEG 2000 images to and from NumPy arrays, with built-in support for use as a pylibjpeg plugin for DICOM image decompression.
ITK provides N-dimensional scientific image processing, segmentation, and registration capabilities through a Python interface to a cross-platform C++ toolkit.
Install it if you need production-grade medical or scientific image processing with segmentation and registration.
Provides Python bindings for ITK's segmentation algorithms, enabling N-dimensional medical image segmentation and classification on cross-platform systems.
itk-registration provides Python bindings for ITK's image registration algorithms, enabling alignment and correspondence mapping between medical and scientific images.
Not recommended if you need only basic image alignment—evaluate whether ITK's scope matches your use case first.
pymzml parses mzML mass spectrometry data files in Python, providing fast random access to spectra and tools for spectrum comparison and visualization.
Install it if you work with mass spectrometry data in proteomics or metabolomics; the core library is lightweight and optional features are available if needed.
nnU-Net is a semantic segmentation framework that automatically configures U-Net variants based on dataset characteristics and provides end-to-end workflows for preprocessing, training, model selection, and inference on 2D and 3D images.
Pronto parses, browses, creates, and exports ontologies in OBO, OBO Graphs JSON, and OWL2 RDF/XML formats, providing a high-level Python interface to biomedical ontology data.
Install it if you need to work with biomedical ontologies in Python.
Reimplemented data augmentation transforms for deep learning, optimized for CPU performance and designed to work with torch and numpy on individual samples rather than batches.
However, verify that the currently implemented transforms cover your use case, since the package explicitly covers only a subset of the original batchgenerators.
Parses, loads, edits, and serializes OBO (Open Biomedical Ontology) format files via Python bindings to a Rust parser, supporting both plain and gzip-compressed files.
Pysylph provides Python bindings to sylph, enabling fast ANI (Average Nucleotide Identity) querying and taxonomic profiling of metagenomic samples against genome databases.
However, the 647-day gap since last release and dormant maintenance status mean you should verify that the current API meets your needs and be prepared to pin the…
Datamol provides a pythonic layer on top of RDKit for molecular manipulation, offering simplified APIs for converting between molecular formats, standardizing molecules, and performing common cheminformatics operations.
Install it if you work with molecular structures and want a more ergonomic API than raw RDKit; the Apache-2.0 license poses no barrier.
TorchIO reads, preprocesses, augments, and samples 3D medical images for deep learning with PyTorch, offering both standard computer vision transforms and domain-specific medical imaging operations like MRI artifact simulation.
Install it if you're building medical imaging models with PyTorch.
TorchXRayVision provides pre-trained deep learning models and unified dataset interfaces for chest X-ray analysis, enabling rapid classification and feature extraction on medical imaging data.