Merge pull request #1 from dev-abuke/setup-environment

Setup environment

.github/workflows/ci.yml

@@ -0,0 +1,25 @@
+name: CI/CD
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.8'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+    - name: Run tests
+      run: |
+        pytest

.gitignore

@@ -126,6 +126,7 @@ celerybeat.pid
 .venv
 env/
 venv/
+backtest/
 ENV/
 env.bak/
 venv.bak/

LICENSE

@@ -1,6 +1,5 @@
                                  Apache License
                            Version 2.0, January 2004
-                        http://www.apache.org/licenses/
 
    TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
 

README.md

@@ -1,2 +1,83 @@
-# Scalable_Backtesting_Infrastructure_for_Crypto_Trading
-Our startup, Mela, aims to simplify cryptocurrency trading for everyone and provide reliable investment sources while mitigating risks. We aim to design and build a reliable, large-scale trading data pipeline that can run various backtests and store useful artifacts in a robust data warehouse.
+# Scalable Crypto Backtesting Infrastructure
+
+## Overview
+
+Mela, a startup, aims to simplify cryptocurrency trading for everyone and provide reliable investment sources while mitigating risks. This project is focused on designing and building a reliable, large-scale trading data pipeline that can run various backtests and store useful artifacts in a robust data warehouse.
+
+## Key Objectives
+
+- **Run Multiple Backtests**: Utilize various technical indicators and assets to perform backtests.
+- **Design Database Schema**: Store backtest artifacts in a well-structured database.
+- **Integrate MLOps Tools**: Use Apache Kafka, Airflow, MLflow, and CML.
+- **Build Frontend**: Create an interface for users to run backtests.
+- **Test Pipeline**: Ensure the pipeline's functionality and reliability.
+
+## Skills and Knowledge
+
+- **Skills**: Technical analysis, backtesting, trading, data pipeline building, structured streaming, workflow orchestration.
+- **Knowledge**: Financial prediction, enterprise-grade data engineering using Apache and Databricks tools.
+
+## Technical Skills
+
+- **Python Programming**
+- **SQL Programming**
+- **Data & Analytics Engineering**
+- **MLOps**
+- **Software Development Frameworks**
+
+## Setup Instructions
+
+### Clone the Repository
+
+```bash
+git clone https://github.com/dev-abuke/Scalable_Backtesting_Infrastructure_for_Crypto_Trading.git
+```
+### Move to Working Directory
+
+```bash
+cd Scalable_Backtesting_Infrastructure_for_Crypto_Trading
+```
+## Set Up Local Development Environment
+
+**Create a virtual environment for the project**
+
+```bash
+python -m venv env
+```
+
+```sh
+source env/bin/activate  # On Windows, use `env\Scripts\activate`
+```
+
+**Install necessary packages**
+
+```bash
+pip install -r requirements.txt
+```
+## Project Structure
+```bash
+├── data/
+├── scripts/
+│   └── download_data.py
+├── tests/
+├── .github/
+│   └── workflows/
+│       └── ci.yml
+├── requirements.txt
+└── README.md
+```
+## Contributors
+- Abubeker Shamil
+
+## License
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## Acknowledgments
+**Instructors** 
+- Yabebal
+- Nathnael
+- Emtinan
+- Rehmet
+
+**References:** 
+backtrader, Freqtrade, Vectorbt, Kafka, Airflow, MLflow, CML

requirements.txt

@@ -0,0 +1,7 @@
+pandas
+numpy
+matplotlib
+scikit-learn
+backtrader
+freqtrade
+yfinance