semvec/pypi-packages huggingface dataset:
hieralog3 0.1.0
Hierarchical logging library with enhanced printing functions.
Requires Python: >=3.6

# Hieralog

**Hieralog** is a hierarchical logging library for Python that provides enhanced logging and printing functions. It supports multiple levels, color coding, framed and plain output, and integrates seamlessly with progress bars.

## Features

- **Hierarchical Logging:** Auto-detect log levels with a "[x]" prefix.
- **Color-Coded Output:** Different colors for each log level.
- **Enhanced Print Functions:** 
  - **hprint()**: Hierarchical (framed) logging output.
  - **pprint()**: Plain print with hierarchical indentation.
  - **fprint()**: Framed print with hierarchical indentation.
  - **progress_write()**: Writes progress messages with the proper indent.
- **Automatic Completion Message:** A final completion log is printed automatically when the program ends.

## Installation

Install via pip:

```bash
pip install hieralog1
icomo 1.0.3
This toolbox aims to simplify the construction of compartmental models and the inference of their parameters
Requires Python: >=3.10

<div align="center">
<img src="https://raw.githubusercontent.com/Priesemann-Group/icomo/main/docs/images/icomo_logo250px.png" width="550" alt="logo"></img>
</div>


# Inference of Compartmental Models toolbox

## Leverage the power of JAX libraries for PyMC models

This toolbox aims to simplify the construction of compartmental models and the inference of their parameters.

The aim isn't to provide a complete package that will build models from A to Z, but rather
provide different helper functions examples and guidelines to help leverage modern python
packages like [JAX](https://jax.readthedocs.io/en/latest/),
[Diffrax](https://docs.kidger.site/diffrax/) and
[PyMC](https://www.pymc.io/welcome.html) to build, automatically differentiate and fit
compartmental models.

A central part of the toolbox is the possibility to wrap JAX functions to be
used in PyMC models (see [here](https://icomo.readthedocs.
io/en/stable/api/jax2pytensor.html)), which
is used tro wrap the [Diffrax ODE solvers](https://docs.kidger.site/diffrax/api/diffeqsolve/), but might be also useful for other
projects.

* Documentation: https://icomo.readthedocs.io.

### Features

* Facilitate the construction of compartmental models by only defining flow between compartments, and
  automatically generating the corresponding ODEs.
* Plot the graph of the compartmental model to verify the correctness of the model.
* Integrate the ODEs using diffrax, automatically generating the Jacobian of the parameters of the ODE
* Fit the parameters using minimization algorithms or build a Bayesian model using PyMC.

### Credits

Logo by [Fabian Mikulasch](https://scholar.google.com/citations?user=ZWWBIoUAAAAJ&hl=en)
git-presets 0.1.0
The CLI tool to use multiple git config presets easily.
Requires Python: >=3.9

# git-presets

The CLI tool to use multiple git config presets easily.

## Usage

### `set` and `use`

Making the `work` preset and use it

```sh
git-presets set work user.name a4rcvv
git-presets set work user.email "a4rcvv@example.tld"
git-presets use work

# git-presets runs these commands internally:
# git config user.name a4rcvv
# git config user.email "a4rcvv@example.tld"
```

### `show`

Show defined presets

```sh
git-presets show  # show all presets
git-presets show work # show the `work` preset
```

### `unset`

Unset an attribute from the preset

```sh
git-presets unset work user.name
```

### `remove`

Remove the `work` preset

```sh
git-presets remove work
```

### Show help

Use `-h` option to show more help.

```sh
git-presets -h
```