https://github.com/r13i/cheapest-phone-call

Small challenge to find the best phone operator to use based on call price
https://github.com/r13i/cheapest-phone-call

big-data big-data-analytics cheapest data-analysis data-cruncher pandas phone-number pricelist

Last synced: 17 days ago
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Small challenge to find the best phone operator to use based on call price

• Host: GitHub
• URL: https://github.com/r13i/cheapest-phone-call
• Owner: r13i
• License: mit
• Created: 2018-11-15T19:56:39.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-11-16T13:24:44.000Z (over 6 years ago)
• Last Synced: 2024-12-07T05:12:32.564Z (2 months ago)
• Topics: big-data, big-data-analytics, cheapest, data-analysis, data-cruncher, pandas, phone-number, pricelist
• Language: Jupyter Notebook
• Size: 13.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# cheapest-phone-call

Small challenge to find the best phone operator to use based on call price

### Methodology

- We'll be using Python as programing language as it is pretty straightforward to build a fast prototype of the solution, and also as it offers many libraries aimed at making large datasets manipulation easier (`pandas`, `numpy`, ...)

- We'll be using a Jupyter notebook in order to have a maximum of ergonomy and a beautiful visual presentation. Also, there will be no need to download or re-run the code as the results is already displayed in the notebook.

- Unit Testing will be done within the same notebook, in separated cells to show directly that everything runs as expected.

- In case we want to have a production-ready prototype that deals with larger datasets, one of the best choices I propose is to use `Apache Spark` with the `Scala API`, as it is especially aimed for Big Data, and because it runs on the JVM.

### How To

- `$ git clone https://github.com/redouane-dev/cheapest-phone-call.git`

- `$ cd cheapest-phone-call`

- Create a virtual environment to avoid dealing with dependency issues and conflicts : `$ virtualenv -p python3 venv`

- `$ source ./venv/bin/activate`. You'll start seeing a `(venv)` before the shell prompt.

- `(venv) $ pip install -r requirements.txt` in order to install all the requirements.

Now you should be all set to run the notebook

- `(venv) $ jupyter notebook prototyping.ipynb`