semvec/pypi-packages huggingface dataset:
tacq 0.0.3
A framework for learning compact representations of constraint networks.
Requires Python: >=3.10

# TAcq - Framework for Learning Compact Representations of Constraint Networks
A framework for learning compact representations of constraint networks.
This project is based on the paper “Learning Compact Representations of Constraint Networks” to be published.

The code is organized in the following way:
- `src/`: Contains the code for the experiments and the models.
- `data/`: Contains data used for some experiments.

You need to have the following dependencies installed:
- "languageFreeAcq~=0.0.7"
- "typing_extensions~=4.12.2"
- "ortools~=9.11.4210"

You can install them using pip:
```bash
pip install ortools
pip install tqdm
pip install languageFreeAcq
```

## Use the TAcq framework in your code
You can install the TAcq framework using pip:
```bash
pip install tacq
```

Then, you can use it in your code as follows:
```python
from tacq import TemplateAcquisition

ta = TemplateAcquisition()
ta.learn_from_file("examtimetabling_2.csv", 300, 1000)
print(ta.get_network())
print(ta.get_template())
```

## Running using CLI
To run an experiment using CLI, you may use the following command:
```bash
python src/main.py <nb_examples> <examples_file> <timeout_solver> <verbose> <max_cpu>
```
Where `<nb_examples>` is the number of examples to use as training set, `<examples_file>` is the file containing 
the examples (some are provided in the `data/` directory), `<max_cpu>` is the maximum number of CPU cores,
`<timeout_solver>` is the timeout for each call to the solver in seconds, `<verbose>` is a flag to enable verbose
mode (1 for true, 0 for false),
synth-spectra 0.1.0
A package to generate synthetic spectra for testing purposes.
Requires Python: >=3.8

# Synthetic Spectra Generator

This is a simple tool for generating synthetic astronomical spectra. You can use it to create test data with multiple Gaussian components and control the amount of noise.

### How It's Organized

* `config.py`: Contains all the default spectra properties you might want to tweak, like the spectral range and noise levels.
* `spectrum_utils.py`: The core library with functions that do the actual work of building a spectrum.
* `plotting.py`: The main script you execute to see an example plot.

### Getting Started

1.  **Clone the repo:**
    ```bash
    git clone https://github.com/ashleyrbemis/synth_spectra.git
    cd synth_spectra
    ```

2.  **Set up the environment:**
    This project uses Conda. Make sure your `codeastro` environment is active and has the necessary packages.
    ```bash
    conda activate codeastro
    conda install numpy scipy matplotlib
    ```

3.  **Installation:**
    ```bash
    pip install -e .
    ```

4.  **Run the code:**
    ```python
    import synth_spectra
    import matplotlib.pyplot as plt
    spec   = synth_spectra.generate_synthetic_spectrum()
    fig,ax = synth_spectra.plot_spectrum(spec)
    plt.show()
    ```
    This will generate a sample spectrum and show you a plot.
esi-utils-rupture 1.0.8
USGS Earthquake Impact Utilities for Ruptures
Requires Python: >=3.11

# esi-utils-rupture

## Introduction

Utility package with some helper functions for representing ruptures and computing
rupture distances used by USGS earthquake hazard products such as ShakeMap and gmprocess.

See tests directory for usage examples.

## Installation

Isolating installations with virtual environments to prevent dependency conflicts is recommended.  You can use the Python3 [`venv`](https://docs.python.org/3/library/venv.html) module or [`conda`](https://docs.conda.io/en/latest/miniconda.html), which is shown below.

Create and activate the virtual environment, checking that the chosen Python version is compatible with package requirements

```bash
conda create --name rupture python=3.10
conda activate rupture
```

### From PyPi

The easiest way to install the package is via PyPi. For users interested in a more hands on development environment, instructions for a source installation with optional additional dependencies for development and testing further down.

```bash
pip install esi-utils-rupture
```

### From Source

First clone the repostory locally

```bash
git clone https://code.usgs.gov/ghsc/esi/esi-utils-rupture.git
cd esi-utils-rupture
```

Next, install the code with pip

```bash
pip install .
```

Note that this will install the minimum requirements to run the code.
There are additional optional packages that can be installed that support running the unit tests (`test`), code development (`dev`), and building wheels (`build`).
To install these, you need to add the relevant option in brackets:

```bash
pip install .[test,dev,build]
```

For developers, it is also convenient to install the code in "editable" mode by adding the `-e` option:

```bash
pip install -e .[test,dev,build]
```

## Tests

If you are installing from soruce and included the optional `test` dependencies in the install step, then you can run the unit tests in the root directory of the repository:

```bash
pytest .
```
icplot 0.2.4
Utilities for generating plots and graphics for technical reports.
Requires Python: >=3.10
Keywords: Publishing, Technical Reports, Graphics

# icplot

This is a library used at [The Irish Centre for High End Computing (ICHEC)](https://www.ichec.ie) for generating plots and graphics for technical documents.

# Features #

The project has support for:

* Coverting image formats between pdf, svg and png
* Building pdf and png output from tex files, including tikz.
* Generating plots based on a serializable data model to support reproducible research
* Generating mermaid plots

To covert between image formats you can do:

``` shell
icplot convert --source my_image.svg --target my_image.png
```

To render a Tex tikz image as pdf and png you can do:

``` shell
icplot convert --source my_tikz.tex
```

To render a Mermaid plot as png you can do:

``` shell
icplot convert --source my_mermaid.mmd
```

To generate a plot or collection of plots from a yaml description you can do:

``` shell
icplot plot --config my_plot.yml
```

# Installation #

The package is available on PyPI. For a minimal installation you can do:

``` shell
pip install icplot
```

For full functionality, particularly conversion of image formats, `imagemagick` and `cairo` are required. On Mac you can install them with:

``` shell
brew install imagemagick cairo
```

# Copyright #

Copyright 2024 Irish Centre for High End Computing

The software in this repository can be used under the conditions of the GPLv3+ license, which is available for reading in the accompanying LICENSE file.
sentiment-package 0.1.1
Package to analyse Motorcycle EV swap related issues
Requires Python: >=3.11

# Motoevsentiment 
A package for analysing swap related messages.

## wsentiment subpackage
This subpackage analyses WhatsApp related messages for sentiment.

## Using wsentiment

import by using
```
from motoevsentiment.wsentiment import wsentiment_score
```
wsentiment_score takes only string inputs.

- example

```
wsentiment_score('kofi has lights out')
>> -2
```

## wdataframe
This subpackage changes WhatsApp text export file *(.txt)* into a dataframe

## Using wdataframe

import using
```
from motoevsentiment.wsentiment import wdataframe
```

- example
```
# Suppose you have a text file with data
test_file = "sample.txt"

# Read the text file into a Pandas DataFrame
df = read_text_to_df(test_file)

# Display the DataFrame
print(df)

              datetime       sender     message
0  2023-09-29 07:49:00    John Doe          ok
1  2023-09-29 08:15:00    Jane Doe  swapped battery
```