- the main purpose of this class is to manage querying the order totals from the database and slice various kinds of time series out of the data - the class holds the former `aggregate_orders()` function as a method - modularize the corresponding tests - add `tests.config` with globals used when testing to provide a single source of truth for various settings |
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.github/workflows | ||
docs | ||
migrations | ||
research | ||
src/urban_meal_delivery | ||
tests | ||
.gitignore | ||
.gitmodules | ||
.pre-commit-config.yaml | ||
alembic.ini | ||
LICENSE.txt | ||
noxfile.py | ||
poetry.lock | ||
pyproject.toml | ||
README.md | ||
setup.cfg |
Urban Meal Delivery
This repository holds code analyzing the data of an undisclosed urban meal delivery platform (UDP) operating in France from January 2016 to January 2017. The goal is to optimize the platform's delivery process involving independent couriers.
Structure
The analysis is structured into the following stages that iteratively build on each other.
Data Cleaning
The UDP provided its raw data as a PostgreSQL dump.
This notebook
cleans the data extensively
and maps them onto the ORM models
defined in the urban-meal-delivery
package
that is developed in the src/ folder
and contains all source code to drive the analyses.
Due to a non-disclosure agreement with the UDP, neither the raw nor the cleaned data are published as of now. However, previews of the data can be seen throughout the research/ folder.
Real-time Demand Forecasting
Predictive Routing
Shift & Capacity Planning
Installation & Contribution
To play with the code developed for the analyses,
you can clone the project with git
and install the contained urban-meal-delivery
package
and all its dependencies
in a virtual environment
with poetry:
git clone https://github.com/webartifex/urban-meal-delivery.git
and
poetry install --extras research
The --extras
option is necessary as the non-develop dependencies
are structured in the pyproject.toml file
into dependencies related to only the urban-meal-delivery
source code package
and dependencies used to run the Jupyter environment
with the analyses.
Contributions are welcome. Use the issues tab. The project is licensed under the MIT license.