Himena
himena is an infinitely extensible and reusable applications framework for data
science.
Motivation
There are many GUI applications for data science, and many of them use the "plugin system" to extend their functionality. Even though the plugin system is a good idea, there are plenty of duplicated works in the third-party plugins.
The reason is that plugins cannot extend other plugins. Imagine that you are a plugin developer and making a plugin that extract features from images as a table. To make your plugin more useful, you will need to implement not only the table widget, but filter/sort functions, plotting functions, and I/O functions as well. You will also be sad to find that these functions cannot readily be used in other plugins.
himena is designed so that plugins developers can cooperate with each other. The
table widgets you implemented in your plugin can be used by other plugins that return a
tabular data. The plotting functions you implemented in your plugin can be used from
any table widgets implemented in other plugins.
To join this plugin community, please check out the developer's guide.
Documentation
Tutorial, developer's guide, and API reference are available at the documentation site.
Installation
himena is available on PyPI.
pip install himena -U # minimal dependencies
pip install himena[recommended] -U # ready to use with recommended optional dependencies
Alternatively, you can install the latest version from GitHub.
git clone git+https://github.com/hanjinliu/himena
cd himena
pip install -e .
Start application
Command himena will be available after installation.
himena
Existing Plugins
You can customize himena for your needs by installing plugins. Here's some example plugins:
- himena-image: image processing and analysis
- himena-stats: statistical testing and modeling.
- himena-seaborn: seaborn plotting.
- himena-lmfit: Curve fitting and parameter optimization using lmfit.
- himena-bio: widgets and commands for basic bioinformatics analysis using biopython.
- himena-relion: A modern RELION GUI built on
himena. - napari-himena: Sending data between
napariandhimena.
Metadata
Release files for himena 0.2.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| himena-0.2.5.tar.gz | 477.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| himena-0.2.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / himena-0.2.5.tar.gz
| Download URL | himena-0.2.5.tar.gz |
|---|---|
| Size | 477.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ce916b8f950cbea5f0a7c78cecd704109e0a194bb3670d4777a5780788d3ba92
|
|
BLAKE2b-256 checksum How to use checksums |
8bc20384083b8a76a254000e795b52eeaa16c5b16a62fb17ae2dc2e15dfb9108
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.27.2
|
Release files / himena-0.2.5-py3-none-any.whl
| Download URL | himena-0.2.5-py3-none-any.whl |
|---|---|
| Size | 620.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
4988f7ab8df60d6cfc89482ddbd4f06900ab11ba51e163ce6292bfe6cf4e19fe
|
|
BLAKE2b-256 checksum How to use checksums |
dfa8ad33fd07759c90937f5ed0a21524d4025bfc8e561b89d5914f2175370efb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-httpx/0.27.2
|
Security for himena 0.2.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.