semvec/pypi-packages huggingface dataset:
bd-metric 0.9.0
Bjontegaard metric calculation

# Bjontegaard_metric

Bjontegaard metric calculation. Include BD-PSNR and BD-rate.

See `demo.py` for usage.

References:
* [1] G. Bjontegaard, Calculation of average PSNR differences between
    RD-curves (VCEG-M33)
* [2] S. Pateux, J. Jung, An excel add-in for computing Bjontegaard metric and
    its evolution
energy-dashboard-library 0.48
Energy Dashboard Library

# Energy Dashboard Library (EDL)

This is a collection of common library functions used by the [Energy
Dashboard](https://github.com/energy-analytics-project/energy-dashboard), a
project of the [Energy Analytics
Project](https://github.com/energy-analytics-project).

## Overview

Common utility functions are used by:

* [energy-dashboard-cli](https://github.com/energy-analytics-project/energy-dashboard-client)
* [data feeds](https://github.com/energy-analytics-project/energy-dashboard/data)
* [feed generator](https://github.com/energy-analytics-project/data-source-template)

This is probably only interesting to project maintainers. Tool users will want
to look at
[energy-dashboard-cli](https://github.com/energy-analytics-project/energy-dashboard-client).

## Dependencies

* [conda](https://conda.io/en/latest/)
* [make](https://www.gnu.org/software/make/manual/html_node/Introduction.html)

## Getting Started

```bash
# only required the first time around, creates a conda environment named 'eap-dev'
make setup

# activate the created conda environment
conda activate eap-dev

# build
make build
```

## Publishing

* Ensure that you have a valid account and that your account has permissions to push to this project.
* Ensure that your `~/.pypirc` file is up to date. Note that I'm using auth tokens below:

```text
[distutils]
index-servers=
    pypi
    testpypi

[testpypi]
repository: https://test.pypi.org/legacy/
username: __token__
password: pypi-...elided...

[pypi]
username: __token__
password: pypi-...elided...
```

* Publish to test first

```bash
# publish
make test-publish
```

* If that worked, then publish to prod

```bash
# publish
make prod-publish
```

## Links

* https://geohackweek.github.io/Introductory/01-conda-tutorial/
* https://packaging.python.org/guides/migrating-to-pypi-org/
* https://packaging.python.org/guides/using-testpypi/
* https://packaging.python.org/tutorials/packaging-projects/

## Author
Todd Greenwood-Geer (Enviro Software Solutions, LLC)
hruid 0.0.3
Human Readable Unique Identifiers for Python
Requires Python: >=3.7,<4.0

<p  align="center">
  <strong>HRUID</strong>
  <br>
  <code>Human Readable Unique Identifier for Python</code>
  <br><br>
  <!-- <a href="https://badge.fury.io/py/conventional-commit"><img src="https://badge.fury.io/py/conventional-commit.svg" alt="PyPI version" height="18"></a>
  <a href="https://travis-ci.org/nebbles/gitcommit/branches"><img src="https://travis-ci.org/nebbles/gitcommit.svg?branch=master" alt="Travis CI build" height="18"></a> -->
</p>

## Usage

Install
```
???
```

Use
```python
import hruid

generator = hruid.Generator()
phrase = generator.random()
print(phrase)
```

## Overview

This Python package implements human readable ID generation based on the [Asanablog post by Greg
Slovacek](https://blog.asana.com/2011/09/6-sad-squid-snuggle-softly/).

In it, he describes how a unique phrase can be generated in lieu of a confusing and complex
alphanumeric ID.

> Imagine representing 32 bits of information (numbers up to 4 billion) as a sentence instead of a jumble of digits. Each sentence can have the same predictable structure, and the number will be used to choose words from a dictionary to fill in that structure—like Mad Libs.
> 
> One possible sentence structure can be: count + adjective + plural noun + verb + adverb, e.g. “6 sad squid snuggle softly.” We can divide the bit-space of the number like so:
> 
> - 5 bits for the count (2-33, so it is always plural)  
> - 7 bits for the adjective (one of 128 possibilities)  
> - 7 bits for the plural noun (one of 128 possibilities, which we made all animals just for fun)  
> - 7 bits for the verb (one of 128 possibilities)  
> - 6 bits for the adverb (one of 64 possibilities)  
>
> Now, given a dictionary containing words categorized in this way, we can generate 4 billion unique (and sometimes very memorable) sentences. In Asana, the ID used to generate the error phrase is random, so the same sentence is unlikely to occur twice.

## Develop

Install dependencies
```
poetry install
```

Run `example.py` which does some basic things with the package
```
poetry run python example.py
```

Run the package in CLI mode
```
poetry run python -m hruid
```

To run tests
```
poetry run tests
```

## License

[GNU GPLv3](./LICENSE)