fraunhoferportugal / tsfel
Time Series Feature Extraction Library (TSFEL): 60+ statistical, temporal, spectral and fractal features for time series classification, regression and signal processing in Python
Why this job: works in the areas we cover, but does not say which job it does
What it does
- Intuitive, fast deployment, and reproducible. Easily configure your feature extraction pipeline and store the
- Computational complexity evaluation. Estimate the computational time required for feature extraction in advance.
- Comprehensive documentation. Each feature extraction method is accompanied by a detailed explanation.
- Unit tested. We provide an extensive suite of unit tests for each feature to ensure accurate and reliable feature
- Easily extended. Adding new features is straightforward, and we encourage contributions of custom features to the
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 58 days ago
- Stars
- 1,114
- +2 this week
- Licence
- BSD-3-Clause
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.2.0
- Released 14 months ago
- Built with
- Python
- 99% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- 92% closed
- 7 still open
- Pull requests
- 74 merged
- 9 waiting
- Releases
- 12
- 0 in the last year
- No contributing guide
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 99%
- Shell 1%
Topics
- audio
- biosignal-processing
- ecg
- eeg
- emg
- explainable-ai
- feature-engineerig
- feature-extractor
- fractal-analysis
- human-activity-recognition
- machine-learning
- python
Project record
- JobOther AI tools
- StatusListed
- Commits445
- Forks161
- Watching18
- Stars in 28 days+8
- CreatedJan 9, 2019
- First seen by usNov 7, 2026
- CheckedNov 12, 2026