Analyzing and Forecasting Bitcoin data using griptape

[mikhail12310]

This commit of the Bitcoin time series analysis includes the complete data pipeline and forecasting workflow using historical price data. The pipeline is designed to fetch, clean, analyze, and forecast Bitcoin prices, with modular utilities and reporting.

Project Structure

utils.py: Core utility functions for-
Fetching and cleaning data
Streaming real-time prices
Saving to Parquet
Time series tools and model integration

analysis.py: Analytical tools including-
ADF test for stationarity
Rolling statistics and seasonal decomposition
Forecasting with Facebook Prophet
Report generation for summaries and forecasts.

main.py: Orchestration script that-
Loads config
Runs the update process
Prints data and forecast reports

pipeline/config.yaml:
Centralized config file for paths and parameters

Dockerfile:
Containerized environment with all necessary dependencies (incl. Prophet, Plotly, etc.)

Key Features:

1. End-to-end time series analysis of Bitcoin prices
2. Forecasting with Prophet for the next 30 days
3. Auto-generated summary and forecast reports
4. Containerized setup for easy deployment
5. Modular code design using Griptape-inspired tools