This project was designed to give a basic set of analytics tools for historical data relating to the Ethiopian Coffee Exchange. The initial scope is to provide a proof-of-concept market price prediction API alongside a set of visualisations tool for understanding market characteristics in the past 7 years.
This repo is python based, so you should use whichever environment manager you prefer to install the relevant packages found in the requirements.txt file.
You should also download the relevant dataset from Kaggle Datasets here https://www.kaggle.com/khalidsultan/cdatasets . Either run the make_data_directory.sh file or create a data directory in the home directory with the following structure:
- data
- bronze
- silver
- gold
- feature_store
Extract the excel files into the bronze directory and delete the original .zip file.
The project has three core functionalities:
- Data Processor
- Price Predictor
- Visualisation
To run the data processing step, use the data_processor_main.py script found within the respective layer of the ecx_analytics package. This will populate the data directory with the appropriate data. This data model mimics the delta lake pattern https://databricks.com/blog/2019/08/14/productionizing-machine-learning-with-delta-lake.html in a lightweight manner.
The price prediction functionality uses a swagger-based endpoint, this can be running by issuing the command python -m swagger_server whilst in the home directory. This will spawn a local server which can be accessed via the browser. There is also a Dockerfile which can be used to spawn a server.
The application path is {server}/ecx-analytics . The swagger UI can be found at {server}/ecx-analytics/ui
Once the server is running, you can issue REST API calls to the server endpoints. Specifying the coffee symbol and target date will return a prediction for the mid price. The endpoint supports the following symbols:
- LUBP4
- LUBP3
- ULK5
- UFRAUG
Dates in April 2018 are supported. This limitation is due to the training set including dates prior to this.
Section TBC
MIT License
Copyright (c) 2021 Morgan Pare
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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