Packages
OSMnx downloads, models, and analyzes street networks and geospatial features from OpenStreetMap, letting you work with walking, driving, or biking networks, amenities, building footprints, and routing data.
Install it if you need to work with street networks, urban amenities, or geospatial features from OpenStreetMap.
Tests whether a graph is planar, computes planar embeddings, draws planar graphs as ASCII art, and isolates forbidden subgraphs using algorithms from the Edge Addition Planarity Suite.
pymatgen-core provides core data structures and I/O for materials science, including Element, Site, Molecule, and Structure classes with support for VASP, ABINIT, CIF, Gaussian, and other computational chemistry formats.
Meteostat provides access to historical weather and climate data from weather stations worldwide, allowing you to retrieve and analyze temperature, precipitation, and other meteorological measurements for specific locations and time periods.
Verify the actual license terms in the repository before use, since the package metadata does not formally declare them.
Detects knee (elbow) points in curves using the Kneedle algorithm, returning the point of maximum curvature for a given set of x and y values.
Vector provides 2D, 3D, and 4D space-time vector operations optimized for working with arrays of vectors rather than individual vectors in loops, with support for multiple coordinate systems and data backends.
Install it if you need to work with spatial vectors at scale or in high-energy physics contexts.
Validates VASP electronic structure calculation inputs and outputs against Materials Project standards, checking for parameter compliance, known bugs, and calculation discrepancies.
coffea provides columnar data analysis tools for high-energy physics (HEP) experiments, enabling efficient manipulation of ROOT file data and event structures using NumPy-like syntax with horizontal scaling support.
Downsamples large time series datasets to a smaller number of representative points for visualization, using Rust-based algorithms (MinMax, M4, LTTB, MinMaxLTTB) with optional multithreading.
Chalk is a Python SDK for building and deploying machine learning feature pipelines that compute features from multiple data sources and serve them for both online inference and offline training.
However, the license is unclear, so verify terms before production use.
Fetches historical and real-time Chinese stock market data and returns it as pandas DataFrames for analysis and export.
cdsapi is a Python client for the Copernicus Climate Data Store API, enabling programmatic retrieval of climate and weather datasets from ECMWF's CDS portal.
Install it if you need programmatic access to Copernicus CDS datasets; the main prerequisite is obtaining a CDS account and configuring your authentication token.
Python interface to the igraph graph library for network analysis and complex graph algorithms; this is a legacy package superseded by the igraph package.
Patito combines pydantic models with polars DataFrames to provide type-annotated schema validation, test data generation, and object-oriented row access for dataframe operations.
POT provides solvers for optimal transport problems, including Wasserstein distances, Gromov-Wasserstein distances, and related algorithms for signal processing, image processing, and machine learning applications.
Adds dynamic data aggregation to Plotly figures, enabling responsive visualization of large time-series datasets by resampling data in real time as users pan and zoom.
The main gotcha is that dynamic aggregation requires Jupyter or Dash—static HTML exports won't work—so confirm your deployment model first.
Automates machine learning model training and prediction on tabular data with minimal code, handling feature engineering, algorithm selection, and hyperparameter tuning internally.
Parses VASP calculation output from vasprun.xml files and generates plots, eigenvalue analyses, and material property calculations including band gaps, density of states, and band structures.
However, maintenance is dormant since early 2022—expect no updates for bugs or new VASP features.
AutoGluon Core provides the foundational infrastructure for automated machine learning, enabling training of high-accuracy models on tabular, time series, image, and text data with minimal code.
Vectorized backtesting engine that packs thousands of trading strategy configurations into NumPy arrays and runs them in parallel using Numba acceleration, turning grid searches into seconds instead of hours.
However, verify the fair-code Apache 2.0 + Commons Clause license terms before using in commercial or proprietary products—the license treatment is flagged as unclear…
Records and analyzes high-precision latency and performance distributions using HDR Histogram, a data structure optimized for capturing value ranges with controlled precision loss.
Install it if you need percentile-based performance analysis or are porting HDR Histogram code from Java or C.
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.
Automates feature engineering and preprocessing for machine learning pipelines, integrating with AutoGluon's broader ML automation framework to handle tabular, time series, and multimodal data preparation.
Visualizes missing data patterns in DataFrames through matrix, bar, heatmap, and dendrogram plots to quickly assess data completeness and nullity correlations.
dissect.target provides a unified API and command-line tools to parse and query data from disk images, file collections, and forensic evidence formats, abstracting away the complexity of multiple underlying Dissect modules.
Detects voiced versus unvoiced segments in audio by wrapping Google's WebRTC Voice Activity Detector with pre-built binary wheels for Windows, macOS, and Linux.
Install it if you need reliable voice activity detection in Python.
Lineax solves linear systems and least-squares problems in JAX, handling both explicit matrices and implicit linear operators without materializing them.
TinySegmenter is a compact Japanese tokenizer that breaks Japanese text into morphological tokens without requiring external dictionaries or machine learning models.
NumKong provides mixed-precision linear algebra and distance kernels with automatic accumulator widening, GIL-free batched operations, and low-precision dtype support (BFloat16, Float8, Float6, packed bits) across x86, ARM, RISC-V, and other architectures.
Provides a Python interface to Google's WebRTC Voice Activity Detector, classifying audio frames as voiced or unvoiced for speech recognition and telephony applications.
However, high install friction (compiled extension), dormancy since 2017-01-07, and uncertainty about modern Python compatibility mean you should verify it builds on…
Adds semantic functions to FabricDataFrame that automatically enrich data with historical weather information from meteostat based on detected latitude, longitude, and date columns.
Install only if you have Python 3.10 or later and meteostat data availability meets your geographic and temporal needs.
Provides Python bindings to CityHash, a fast non-cryptographic hashing algorithm, specifically tuned for ClickHouse protocol compatibility.
Install only if you specifically need ClickHouse protocol compatibility; for general-purpose hashing, use the original python-cityhash package instead.
YAKE extracts keywords from text documents using unsupervised statistical methods, requiring no training data, external corpus, or language-specific dictionaries.
The copyleft license requires careful review if you plan proprietary use.
Morphological analyzer and POS tagger for Russian and Ukrainian text that performs inflection analysis and lemmatization.
Provides Russian morphological dictionaries for pymorphy3, enabling morphological analysis and lemmatization of Russian text.
However, it is abandoned—no updates since 2022-01-08.
Hachoir parses and displays binary files as a tree of typed fields, letting you inspect and edit individual bits, bytes, and structures within any binary stream.
ipydagred3 is an ipywidgets library for rendering and interacting with directed acyclic graphs in JupyterLab, built on dagre-d3 for layout and visualization.
A Python wrapper for Censys APIs that lets you search internet-wide data on hosts, certificates, and services, manage attack surface assets, and run queries from the command line.
However, review the deprecation notice carefully: if you are starting a new project, evaluate censys-platform as your long-term choice.
Python wrapper for Google's CityHash and FarmHash non-cryptographic hash functions, offering 32-, 64-, and 128-bit implementations with support for hardware-independent fingerprints and fast hashing of buffer-protocol objects like NumPy arrays.
Dask-awkward integrates Awkward Array with Dask to enable distributed, lazy computation on complex, nested data structures across multiple cores or machines.
Install it if you work with Awkward Arrays at scale or need lazy evaluation of nested structures across multiple workers.