Optimizing an urban meal delivery platform
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Alexander Hess c7989e0040
Add a code linting tool chain
- use flake8 as the main and pylint as the auxiliary linter
- install flake8 with the following plug-ins:
  + flake8-annotations => enforce type annotations for functions/classes
  + flake8-black => ensure black would not make any changes
  + flake8-expression-complexity
  + wemake-python-styleguide, which packages the following:
    * darglint         * flake8-bandit         * flake8-broken-line
    * flake8-bugbear   * flake8-commas         * flake8-comprehensions
    * flake8-debugger  * flake8-docstrings     * flake8-eradicate
    * flake8-isort     * flake8-rst-docstrings * flake8-string-format
    * flake8-quotes    * pep8-naming
- configure flake8 & friends in a rather explicit and strict way
- isort needed to be downgraded to ^4.3.21 due to a conflict with
  pylint and wemake-python-styleguide:
  + provide TODO's to remove the parts that "fix" isort
- use mypy for static type checking
- add a nox session "lint" that runs flake8, mypy, and pylint
- lint all source files
2020-08-03 23:12:12 +02:00
src/urban_meal_delivery Initial commit 2020-08-03 20:19:42 +02:00
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LICENSE.txt Initial commit 2020-08-03 20:19:42 +02:00
noxfile.py Add a code linting tool chain 2020-08-03 23:12:12 +02:00
poetry.lock Add a code linting tool chain 2020-08-03 23:12:12 +02:00
pyproject.toml Add a code linting tool chain 2020-08-03 23:12:12 +02:00
README.md Initial commit 2020-08-03 20:19:42 +02:00
setup.cfg Add a code linting tool chain 2020-08-03 23:12:12 +02:00

Urban Meal Delivery

This repository holds code analyzing the data of an undisclosed urban meal delivery platform operating in France from January 2016 to January 2017. The goal is to optimize the platform's delivery process involving independent couriers.

The analysis is structured into three aspects that iteratively build on each other.

Real-time Demand Forecasting

Predictive Routing

Shift & Capacity Planning