Quantitative analysis for power markets
Project description
octoanalytics 📊⚡
Energy consumption forecasting & risk premium analysis for the French electricity market
Description
octoanalytics is a Python toolkit for:
- Retrieving and smoothing weather data via Open-Meteo API.
- Training and evaluating load forecasting models (MW) using Random Forest.
- Generating interactive visualizations comparing actual vs. forecasted values.
- Accessing spot and forward price data (annual, monthly, PFC) from Databricks SQL.
- Computing volume and shape risk premiums, key for energy portfolio management.
Installation
pip install octoanalytics
⚠️ You need a valid Databricks access token to retrieve market data.
Dependencies
pandasnumpyscikit-learnplotlymatplotlibtqdmrequeststentaclioyaspinholidaysdotenvdatabricks-sql-connector
Main Features
🔁 Weather data retrieval and smoothing
from octoanalytics import get_temp_smoothed_fr
temp_df = get_temp_smoothed_fr(start_date="2024-01-01", end_date="2024-12-31")
⚡ Load forecasting
from octoanalytics import eval_forecast
forecast_df = eval_forecast(df=load_df(), temp_df=temp_df, cal_year=2024)
💰 Risk premium calculation
Volume Risk
from octoanalytics import calculate_prem_risk_vol
premium = calculate_prem_risk_vol(forecast_df, spot_df, forward_df)
Shape Risk
from octoanalytics import calculate_prem_risk_shape
shape_risk = calculate_prem_risk_shape(forecast_df, pfc_df, spot_df)
🔌 Databricks SQL connections
from octoanalytics import get_spot_price_fr, get_forward_price_fr_annual
spot_df = get_spot_price_fr(token=DB_TOKEN, start_date="2024-01-01", end_date="2024-12-31")
forward_df = get_forward_price_fr_annual(token=DB_TOKEN, cal_year=2025)
Package Structure
octoanalytics/
│
├── __init__.py
├── core.py # Main logic
├── ...
Author
Jean Bertin
📧 jean.bertin@octopusenergy.fr
License
MIT – free to use, modify, and distribute.
Roadmap
- Add XGBoost model
- Load anomaly detection
- Flask REST API deployment
- Automatic PDF report generation
Full Demo
To be included in examples/forecast_demo.ipynb.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file octoanalytics-0.2.1.tar.gz.
File metadata
- Download URL: octoanalytics-0.2.1.tar.gz
- Upload date:
- Size: 13.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
23093c54c7ac4356f5744c27aebe06a9ab1bd92d9cf296bee685fd26e1abbb33
|
|
| MD5 |
059a7af8ea25a4b4548c2f2e598f6776
|
|
| BLAKE2b-256 |
7d9b7e34c960875efa371fe439a45927aba9c5254a50ed85d4a42531b4751e9c
|
File details
Details for the file octoanalytics-0.2.1-py3-none-any.whl.
File metadata
- Download URL: octoanalytics-0.2.1-py3-none-any.whl
- Upload date:
- Size: 12.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4dbe753152b6bb55ac060afe3802e134089cdaad5b924a44befa9bcd4eebc245
|
|
| MD5 |
a630305c2f58ba9183a0e9b32a90c0b0
|
|
| BLAKE2b-256 |
8c0ce32ccee737f812cee5130b76668fe3dbaa9ee93a8b9141f2980e2597386f
|