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louisoutin / deep_gas_oracle

Unofficial implementation of the paper: "Step on the Gas? A Better Approach for Recommending the Ethereum Gas Price"
MIT License
22 stars 6 forks source link
arxiv data-science deep-learning ethereum forecasting neural-network pytorch time-series

readme

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Ethereum Deep Gas Price Oracle

This is an unofficial implementation of the paper: Step on the Gas? A Better Approach for Recommending the Ethereum Gas Price (by Sam M. Werner, Paul J. Pritz, Daniel Perez)!

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgements
## About The Project This is a price gas recommender for the Ethereum network. The network is trained to predict the next `S`th prices (with a resampling over 5 minutes periods). As the minimum gas price is very noisy, the idea is to predict the prices on the next minutes/hours. From thoses predictions the algorithm will return a recommended price, taking into account the slope of the predictions. Few plots from this repository: Note: We try to forecast the minimum eth gas price over the next 3 hours. The loss of the GRU model: Model first timestamp predictions (5min) on the test range: Some predictions over the 3 hours: Results of the simulation between the block `8965759` and the block `8995344`: DEEP GAS ORACLE : GETH (my implementation): As a comparison, here is the paper original results: Note: I just tried a few different hyper-parameters but didn't have time to tune them yet. My results are not as good as the paper but close to it. ### Built With * Python * Pytorch * Pandas & Numpy * Notebooks for visualisations ## Getting Started Follow the notebooks. ### Prerequisites This run on python 3, you can find the requirements in : `requirements.txt` Note: you need to have pip installed ### Datasets To download the raw datasets, you need a google api key to use the BigQuery service to be able to fetch historical eth blocks information. Once you have the key, place the `json` file in the `credentials/` folder. For the eth price, you can download it [here](https://www.kaggle.com/prasoonkottarathil/ethereum-historical-dataset?select=ETH_1min.csv) on Kaggle. You should put the ETH price `csv` file in the `datasets/` folder. ### Installation 1 - Clone this repo 2 - Install the package with pip: `pip install .` ## Usage You can run the notebooks to: * 01 -> Explore the data and preprocess it * 02 -> Modelise the minimum gas prices (5min avg) with a GRU neural-network * 03 -> Evaluate the recommendation made by the deep oracle VS "Geth strategy" ## License Distributed under the MIT License. See `LICENSE` for more information. [stars-shield]: https://img.shields.io/github/stars/louisoutin/deep_gas_oracle.svg?style=for-the-badge [stars-url]: https://github.com/louisoutin/deep_gas_oracle/stargazers [issues-shield]: https://img.shields.io/github/issues/louisoutin/deep_gas_oracle.svg?style=for-the-badge [issues-url]: https://github.com/louisoutin/deep_gas_oracle/issues [license-shield]: https://img.shields.io/github/license/othneildrew/Best-README-Template.svg?style=for-the-badge [license-url]: https://github.com/louisoutin/deep_gas_oracle/blob/master/LICENSE.txt