semvec/pypi-packages huggingface dataset:
metromobilite 0.2.1
Python library for metromobilite API
License: MIT

# Metromobilite
[![PyPI Version](https://img.shields.io/pypi/v/metromobilite.svg)](https://pypi.org/project/metromobilite/)

A Python client for interacting with [Metromobilite API](https://www.metromobilite.fr/pages/opendata/OpenDataApi.html) (Transport for Grenoble, TAG).

Installation
=====

```sh
pip install metromobilite
```


```sh
git clone git@github.com:PierreBerger/metromobilite.git
cd metromobilite
python setup.py install
```

Usage
=====
### Import and initialization:
```python
from metromobilite import Metromobilite
m = Metromobilite(origin='My Origin')
print (m.get_stoptimes('SEM:2216'))
```

All stops and routes are vailable here : [https://data.metromobilite.fr/api/routers/default/index/routes](https://data.metromobilite.fr/api/routers/default/index/routes)

See [Metromobilite API documentation](https://data.metromobilite.fr/donnees) for more informations.
universal-data-catalog 0.1.12
A abstraction layer for dataset IO that can be configured using yaml files.
License: MIT
Requires Python: >=3.7.1,<4.0
Keywords: yml,data-science,data-catalog

# universal-data-catalog


[![Documentation Status](https://readthedocs.org/projects/universal-data-catalog/badge/?version=latest)](https://universal-data-catalog.readthedocs.io/en/latest/?badge=latest)
![release workflow](https://github.com/AnH0ang/universal-data-catalog/actions/workflows/release.yml/badge.svg)
![test workflow](https://github.com/AnH0ang/universal-data-catalog/actions/workflows/test.yml/badge.svg)
[![codecov](https://codecov.io/gh/AnH0ang/universal-data-catalog/branch/master/graph/badge.svg?token=UKXBKOXDVQ)](https://codecov.io/gh/AnH0ang/universal-data-catalog)
[![PyPI version](https://badge.fury.io/py/universal-data-catalog.svg)](https://badge.fury.io/py/universal-data-catalog)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/AnH0ang/universal-data-catalog/blob/master/LICENCE)
[![Maintainability](https://api.codeclimate.com/v1/badges/b5bc602f4fb7c1132715/maintainability)](https://codeclimate.com/github/AnH0ang/universal-data-catalog/maintainability)
[![Python version](https://img.shields.io/badge/python-3.7|3.8|3.9-blue.svg)](https://pypi.org/project/kedro/)


## Introduction

The goal of `universal-data-catalog` is to act as an abstraction layer on top of the data IO.
Instead of hard-coding the data interface, the configuration is loaded from a configuration file that acts as a data catalog.
This concept is borrowed from the [kedro](https://github.com/quantumblacklabs/kedro) data catalog.


Full documentation can be found at [readthedocs.com](https://universal-data-catalog.readthedocs.io/en/latest/).


## Why use it ?

The advantages of `universal-data-catalog` are:
* **Abstraction**: Instead of hard-coding the data interface, you can use a configuration file
that separates the code from the configuration.
* **YAML configuration**: Since the configuration file is in YAML format, it can easily be used in
with Hydra and other YAML-based configuration and orchestration tools.
* **Customizability**: Link your own data provider to the data catalog.
* **Pluggability**: A number of providers are supported and many more will be added soon. These include:
    * `pandas`
    * `networkx`
    * `pickle`



## Installation

You can easily install this package with `pip`.

```
pip install universal-data-catalog
```

## Usage

Set the load configuration for your data in a separate `config.yaml` file.

```yaml
# catalog.yml

titanic:
  filepath: titanic.csv
  type: pandas.CSVDataSet
  load_args:
    sep: ","
```

Load the dataset from Python via the data catalog.

```python
# main.py

from universal_data_catalog.data_catalog import DataCatalog

catalog = DataCatalog("catalog.yml", conf)
titanic_df = catalog.load("titanic")
```

A complete example can be found in the [docs](https://universal-data-catalog.readthedocs.io/en/latest/logic/example.html).
grouping-list-tuple 1.0
Package for grouping array objects in list by some key
License: MIT
Requires Python: >=3.9

A function that implements grouping of objects by some key. For example, the string 'AAAABBBCAAB' is given. 
The result of the program should be:[('A', ['A', 'A', 'A', 'A']), ('B', ['B', 'B'¸'B']), ('C', ['C']), ('A', ['A', 'A']), ('B', ['B'])].
It is also possible to use the function to determine the key for grouping. For example, for a list of tuples: [('foo', 1), ('bar', 1), ('foobar', 2), ('baz', 3)],
when using the second element of the tuple as the key, the result should be [(1, [('foo', 1), ('bar', 1)]), (2, [('foobar', 2)]), (3, [('baz', 3)])].