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Fastkit-Mobility

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Fastkit-Mobility (fastmob on PyPI) is a high-performance Python library for mobility analysis. It combines native Rust kernels with a Narwhals-based API, so the same code works unchanged against pandas, Polars, and other eager dataframe backends — no rewrites, no backend-specific branches.

Beyond individual/collective mobility measures, fastmob covers the full pipeline: raw position fixes → staypoints → triplegs → trips → tours, trajectory preprocessing (outlier filtering, simplification, segmentation, smoothing), mobility models (next-location prediction, gravity/radiation, synthetic diary generation), and network/social analysis (road/rail-matched distances, co-presence contact networks, mobility-law fitting).

Why fastmob

  • Backend-agnostic — pass a pandas, Polars, or any other Narwhals-compatible DataFrame; fastmob works without changes.
  • Rust-accelerated core — compute-heavy kernels run in parallel, zero-copy Rust instead of Python loops.
  • Full trajectory hierarchy — positionfixes, staypoints, triplegs, trips, tours, and locations, following the trackintel model.
  • Migration-friendly — API shapes mirror scikit-mobility where compatibility matters, with reproducible parity tests against it.
  • Measured, not claimed — correctness tests, coverage, and reproducible benchmarks back every performance and compatibility claim.

Install

pip install fastmob

Install optional capabilities only when needed:

pip install duckdb  # fetch road/rail networks from Overture
pip install statsmodels  # fit the Gravity Poisson-GLM
pip install "fastmob[vis]"  # visualization package

Quickstart

import pandas as pd
from fastmob import jump_lengths, radius_of_gyration

traj = pd.DataFrame(
    {
        "uid": ["alice", "alice", "alice"],
        "datetime": pd.date_range("2024-01-01", periods=3, freq="h"),
        "lat": [41.8902, 41.9028, 41.9109],
        "lng": [12.4922, 12.4964, 12.4818],
    }
)

print(jump_lengths(traj))
print(radius_of_gyration(traj))

Fastmob auto-detects common time, latitude, longitude, and user-ID column names. Pass explicit datetime_col, lat_col, lng_col, and uid_col arguments when your schema differs.

Documentation

Development

git clone https://github.com/gefgu/fastmob.git
cd fastmob
bash scripts/setup_env.sh
source .venv/bin/activate
pytest

To preview documentation locally:

uv sync --group docs
uv run --group docs zensical serve

See CONTRIBUTING.md for documentation conventions and the repository workflows.

Status and support

Fastmob is actively developed. Please include versions, dataframe backend, a minimal reproducible input, expected behavior, and the full error when opening an issue.

Project links

Data verified by PyPI on Sep 9, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Latest release

1 maintainer

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Avatar for gefgu from gravatar.com gefgu

Credits

Author: Gustavo Henrique Bruno dos Santos

GitHub Statistics

Data verified by PyPI on Sep 9, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

BSD-3-Clause
View SPDX License List

Requires

Python >=3.9

Provides Extra

geo vis

Classifiers

Report project as malware

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