https://github.com/glentner/dataphile
Data analytics library for Python and suite of open source, command line based data ops tools.
https://github.com/glentner/dataphile
data-analysis data-ops data-science python scientific-computing
Last synced: 9 months ago
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Data analytics library for Python and suite of open source, command line based data ops tools.
- Host: GitHub
- URL: https://github.com/glentner/dataphile
- Owner: glentner
- License: apache-2.0
- Created: 2018-03-12T17:46:20.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2022-12-08T03:41:11.000Z (about 3 years ago)
- Last Synced: 2025-05-07T23:07:13.308Z (9 months ago)
- Topics: data-analysis, data-ops, data-science, python, scientific-computing
- Language: Python
- Size: 351 KB
- Stars: 14
- Watchers: 2
- Forks: 3
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Dataphile
=========
Dataphile is a high-level python package for both data analysis and data processing. It started as
a central repository of common tasks and capabilities used by the author, but has now evolved into
something others might find useful. See [components](#Components) below.
[](https://www.apache.org/licenses/LICENSE-2.0)
[](https://pypi.org/project/dataphile/)
[](https://dataphile.readthedocs.io)
---
**Figure**: Demonstration of Dataphile's `AutoGUI` feature.
Installation
------------
To install Dataphile for general purposes use Pip:
```
pip install dataphile
```
If you are using Anaconda, install using the above call to pip _from inside your environment_.
There is not as of yet a separate conda package.
Documentation
-------------
Documentation will be available at [dataphile.readthedocs.io](https://dataphile.readthedocs.io).
Currently, development of additional features is a priority, but this is a great place for
contributing to the project.
Contributions
-------------
Contributions are welcome in the form of suggestions for additional features, pull requests with
new features or bug fixes, etc. If you find bugs or have questions, open an _Issue_ here. If and
when the project grows, a code of conduct will be provided along side a more comprehensive set of
guidelines for contributing; until then, just be nice.
Road Map
--------
- **additional command line tools**
Many additional command line tools are planned for future releases including tools that expose
database queries and filters. Generally, just a massive extension of the UNIX philosophy whereby
we can compose several functions together with pipes to make unique workflows.
- **data acquisition**
One of the motivations for this package was to provide an easy-to-use, high-level interface to
collecting scientific data from an externel device (e.g., over USB). This, along side a simple
live data visualization feature would go a long way for high school and university student
laboratory courses to both aquire and analyze their data using all open-source tools right inside
of a [Jupyter Notebook](https://jupyter.org).
- **documentation and package management**
A quickstart guide along with full documentation of all components needs to be built using Sphinx.