semvec/pypi-packages huggingface dataset:
python-ottawa-transit 0.2.0
Python interface for OCTranspo API
License: MIT
Requires Python: >=3.6,<4.0

# python-ottawa-transit

Python interface to the [OC Transpo](http://www.octranspo.com/developers/documentation) API and utilities for working with the returned data.

## Installation

The package is available on [PyPi](https://pypi.org/project/python-ottawa-transit)
```bash
pip install python-ottawa-transit
```

Alternativly it can be installed from source using [Poetry](https://github.com/sdispater/poetry)
```bash
git clone https://github.com/buckley-w-david/python-ottawa-transit.git
cd python-ottawa-transit
poetry install
```

## Usage

```python3
>>> from python_ottawa_transit import OCTransportApi
>>> api = OCTransportApi(app_id = 'APPLICATION_ID', app_key = 'APPLICATION_KEY')
>>> api.get_route_summary_for_stop(stop_no=8435)
{"GetRouteSummaryForStopResult":{"StopNo":"8435","StopDescription":"BANK \\/ COLLINS","Error":"","Routes":{"Route":{"RouteNo":6,"DirectionID":1,"Direction":"Northbound","RouteHeading":"Rockcliffe"}}}}
```
textalyzer 0.1.6
A text  analyzer for repeating and contraction characters
License: MIT
Keywords: python,replacers,words,repeat,characters

# Textalyzer
Textalyzer is a lightweight python module or library to help ease analyzing of text or words in a particular sentence and manipulating it.
Textalyzer analyze repeating words, contracted words or contractions and formatting them properly.

# Class Functions Involved in this module
  [-] ContractionReplacers <br>
  [-] RepeatingReplacers

# Usage
  -Place the file in a folder where you have either read or write and read permisson. Eg. /opinionmining/lib/Textalyzer.py<br/>
  -Import the module into your application.<br/>
   <hr/> 
    from opinionmining.lib.Textalyzer import "Function To Use" <br>
    sample = "I can't wait for the football match" <br>
    object = ContractionReplacers() <br>
    data = object.text_replacers(sample)<br>

# Sample
  ## Repeating words
  - Repeating words like helloooooooooooo - textalyzer help format this word by removing the o's to its normal word "hello"<br/>
  - Contractions like I'm - Textalyzer help format this word by converting it to it's normal word "I am"
# Dependencies
- wordnet 
- Install wordnet by installing nltk
# PyPI
- Textalyzer is available at python package index.
  ## Installation Guide
    - Download textalyzer using pip<br>
    - pip install textalyzer<br>
    - Import textalyzer into your project by using ```from textalyzer import Textalyzer``` depending on the   function you want to use.<br>
    - The use ``` replacer = Textalyzer.ContractionReplacers() and repeat = Textalyzer.RepeatingReplacers() ``` <br>
    -    ## Or
    - Simple do ```import textalyzer``` <br>
    - Then Use ``` data = textalyzer.Textalyzer ``` <br>
    -   ``` replacer  = data.ContractionReplacers() ``` <br>
    
  ## Alternatively
    - [x] You can download the tarball file from `pypi.python.org/pypi/textalyzer`
    - [x] Extract the tarball file
    - [x] Navigate into the extracted folder and install using `python setup.py install`
    
  **To Check Whether it's installed**
  - type  `pip freeze` to display the list of installed packages
# Why This
- Textalyzer is mostly used by python programmers who are more involved with Natural Language Processing , Machine Learning, Text Extraction and others.