tsdat

v0.8.8

A data processing framework used to convert time series data into standardized format. For more information about how to use this package see README

Latest version published 1 month ago

License: **Time Series Data Utilities*…

PyPI

GitHub

Package Health Score

69 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Limited

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Popularity

Limited

GitHub Stars: 13
Forks: 8
Contributors: 9

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package tsdat, we found that it has been starred 13 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 19, 2024
Direct Vulnerabilities: 0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

**Time Series Data Utilities** Copyright © 2021, Battelle Memorial Institute Licensed under a Simplified BSD 2-Clause License; you may not use this software except in compliance with the License as specified below. 1. Battelle Memorial Institute (hereinafter Battelle) hereby grants permission to any person or entity lawfully obtaining a copy of this software and associated documentation files (hereinafter “the Software”) to redistribute and use the Software in source and binary forms, with or without modification. Such person or entity may use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and may permit others to do so, subject to the following conditions: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimers. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Other than as used herein, neither the name Battelle Memorial Institute or Battelle may be used in any form whatsoever without the express written consent of Battelle. 2. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL BATTELLE OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 4
Open PR: 2
Last Release: 1 month ago
Last Commit: 1 month ago

Further analysis of the maintenance status of tsdat based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that tsdat demonstrates a positive version release cadence with at least one new version released in the past 3 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 9
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.10

Age: 4 years
Latest Release: 1 month ago
Dependencies: 5 Direct
Versions: 56
Maintainers: 2
Wheels: OS Independent

Readme

About Tsdat

Tsdat is an open-source python framework for declaratively creating pipelines to read, standardize, and enhance time series datasets of any dimensionality for use in scalable applications and in building large data repositories.

This repository contains the core tsdat code. We invite you to explore this, especially for those willing to provide feedback or make contributions to the tsdat core (we enthusiastically welcome issues, PRs, discussions & new ideas, etc.).

> Most users should start with a template repository to generate boilerplate code and configurations needed to create a tsdat data pipeline. We recommend this template to start with, as it is the most flexible and well-supported template that we offer.

Development Environment

Instructions on setting up your development environment for working on the core tsdat code are included below:

Fork this repository to your github account and open it on your desktop in an IDE of your choice.

> We recommend using VS Code, as we've included extra settings that make it easy to start developing in a standard environment with no overhead configuration time.
Open an appropriate terminal shell from your computer
1. If you are on Linux or Mac, just open a regular terminal
2. If you are on Windows, start your Anaconda prompt if you installed Anaconda directly to Windows, OR open a WSL terminal if you installed Anaconda via WSL.
Run the following commands to create and activate your conda environment
```
conda env create
conda activate tsdat
pip install -e ".[dev]"
```

Community

Tsdat is an open-source repository and we highly-value community contributions and engagement via issues, pull requests, and discussions. Please let us know if you find bugs, want to request new features, or have specific questions about the framework!

Additional resources

Learn more about tsdat:
- GitHub:
- Documentation:
- Data standards:
- Preferred template:
- All templates:
- Docker Images:
Learn more about xarray:
- GitHub:
- Documentation:
Learn more about act-atmos:
- GitHub:
- Documentation:
Other useful tools:
- VS Code:
- Docker:
- pytest:
- black:
- matplotlib guide:

tsdat dependencies

cftime netcdf4 pint rich xarray

FAQs

What is tsdat?

A data processing framework used to convert time series data into standardized format. Visit Snyk Advisor to see a full health score report for tsdat, including popularity, security, maintenance & community analysis.

Is tsdat popular?

The python package tsdat receives a total of 535 weekly downloads. As such, tsdat popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is tsdat well maintained?

We found that tsdat demonstrated a healthy version release cadence and project activity. It has a community of 9 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is tsdat safe to use?

The python package tsdat was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 27 November-2024, at 04:04 (UTC).

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Readme

About Tsdat

Development Environment

Community

Additional resources

tsdat dependencies

FAQs

What is tsdat?

Is tsdat popular?

Is tsdat well maintained?

Is tsdat safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

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