https://github.com/arundo/adtk
A Python toolkit for rule-based/unsupervised anomaly detection in time series
Science Score: 13.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (18.6%) to scientific vocabulary
Keywords
Repository
A Python toolkit for rule-based/unsupervised anomaly detection in time series
Basic Info
- Host: GitHub
- Owner: arundo
- License: mpl-2.0
- Language: Python
- Default Branch: develop
- Homepage: https://adtk.readthedocs.io
- Size: 23.5 MB
Statistics
- Stars: 1,174
- Watchers: 24
- Forks: 160
- Open Issues: 51
- Releases: 12
Topics
Metadata Files
README.md
Anomaly Detection Toolkit (ADTK)
Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection.
As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model.
This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events.
See https://adtk.readthedocs.io for complete documentation.
Installation
Prerequisites: Python 3.5 or later.
It is recommended to install the most recent stable release of ADTK from PyPI.
shell
pip install adtk
Alternatively, you could install from source code. This will give you the latest, but unstable, version of ADTK.
shell
git clone https://github.com/arundo/adtk.git
cd adtk/
git checkout develop
pip install ./
Examples
Please see Quick Start for a simple example.
For more detailed examples of each module of ADTK, please refer to Examples section in the documentation or an interactive demo notebook.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update unit tests as appropriate.
Please see Contributing for more details.
License
ADTK is licensed under the Mozilla Public License 2.0 (MPL 2.0). See the LICENSE file for details.
Owner
- Name: Arundo Analytics
- Login: arundo
- Kind: organization
- Website: https://arundo.com
- Repositories: 34
- Profile: https://github.com/arundo
GitHub Events
Total
- Issues event: 1
- Watch event: 86
- Issue comment event: 7
- Fork event: 10
Last Year
- Issues event: 1
- Watch event: 86
- Issue comment event: 7
- Fork event: 10
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| tailaiw | 2****w | 48 |
| tailaiw | t****n@a****m | 5 |
| tailaiw-ghost | 6****t | 2 |
| Roy Keyes | r****g@g****m | 2 |
| tellezsanti | t****i@g****m | 1 |
| burakyilmaz321 | b****1@g****m | 1 |
| Yang Yu | 4****6 | 1 |
| Sam Zeitlin | s****n@g****m | 1 |
| Nathaniel Saul | n****t@r****m | 1 |
| Ajda | a****r | 1 |
| Jason Hu | j****u@a****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 68
- Total pull requests: 45
- Average time to close issues: about 1 month
- Average time to close pull requests: 1 day
- Total issue authors: 57
- Total pull request authors: 9
- Average comments per issue: 2.01
- Average comments per pull request: 0.22
- Merged pull requests: 34
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 4.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- tailaiw (7)
- engineeryashsaxena (2)
- ivanokeeffe (2)
- joriws (2)
- TonyEinstein (2)
- ajdapretnar (2)
- senemaktas (1)
- kusumy (1)
- f5-ansible (1)
- szeitlin (1)
- Anaisdg (1)
- nbrosse (1)
- numericOverflow (1)
- estcarisimo (1)
- tellezsanti (1)
Pull Request Authors
- tailaiw (32)
- tailaiw-ghost (4)
- earthgecko (3)
- tellezsanti (2)
- mazzma12 (1)
- csrgxtu (1)
- rbs392 (1)
- nabeelraza-7 (1)
- ajdapretnar (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 4
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Total downloads:
- pypi 276,339 last-month
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Total dependent packages: 2
(may contain duplicates) -
Total dependent repositories: 40
(may contain duplicates) - Total versions: 25
- Total maintainers: 2
pypi.org: adtk
A package for unsupervised time series anomaly detection
- Homepage: https://github.com/arundo/adtk
- Documentation: https://adtk.readthedocs.io/
- License: Mozilla Public License 2.0 (MPL 2.0)
-
Latest release: 0.6.2
published over 6 years ago
Rankings
proxy.golang.org: github.com/arundo/adtk
- Documentation: https://pkg.go.dev/github.com/arundo/adtk#section-documentation
- License: mpl-2.0
-
Latest release: v0.6.2
published over 6 years ago
Rankings
conda-forge.org: adtk
This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events.
- Homepage: https://github.com/arundo/adtk
- License: MPL-2.0
-
Latest release: 0.6.2
published over 6 years ago
Rankings
anaconda.org: adtk
This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events.
- Homepage: https://github.com/arundo/adtk
- License: MPL-2.0
-
Latest release: 0.6.2
published over 3 years ago
Rankings
Dependencies
- jupyter >=1
- nbsphinx >=0.4
- python-dateutil >=2.5
- sphinx >=2.0
- sphinx_rtd_theme <0.5
- actions/checkout v1 composite
- actions/setup-python v1 composite