Algo.Analytics.Python

This folder contains sample analytics scripts for the StockSharp trading platform written in IronPython. Each script implements the IAnalyticsScript interface and can be executed inside StockSharp Designer or any application that supports analytics scripts.

These examples illustrate the Hydra analytics feature. See the Hydra documentation for usage details.

The examples demonstrate how to analyse market data and visualize the results using StockSharp API. They can be used as a starting point for developing your own analytics tools or trading algorithms in Python.

Requirements

• .NET 6 or higher
• IronPython 3 (the scripts are tested with version 3.4.2)
• StockSharp packages, including StockSharp.Algo.Analytics

Directory Structure

Algo.Analytics.Python/
├── common/                 # Helper modules used by the scripts
├── biggest_candle_script.py
├── chart3d_script.py
├── chart_draw_script.py
├── empty_analytics_script.py
├── indicator_script.py
├── normalize_price_script.py
├── pearson_correlation_script.py
├── price_volume_script.py
└── time_volume_script.py

common helpers

The common directory provides a set of helper functions that simplify interaction with StockSharp objects from Python:

• candle_extensions.py – utilities for working with candle messages (length, body, shadows, middle price, etc.).
• chart_extensions.py – wrappers to create 2D and 3D charts with correct .NET type mapping.
• datatype_extensions.py – convenience function to create TimeFrame values.
• indicator_extensions.py – helpers to process StockSharp indicators from Python code.
• numpy_extensions.py – utility methods exposing NumPy.NET features to IronPython.
• orderbook_extensions.py – methods to get best bid/ask from order book messages.
• storage_extensions.py – extensions for loading market data from IStorageRegistry.

Example Scripts

Below is a brief description of the provided scripts.

empty_analytics_script.py

Template demonstrating the minimal implementation of an analytics script. Use it as a starting point for your own logic.

biggest_candle_script.py

Finds the candles with the largest volume and range for each selected security and displays them on separate 3D charts.

chart3d_script.py

Aggregates traded volume by hour for several securities and visualizes the results on a 3D chart.

chart_draw_script.py

Shows how to draw different series styles (lines and histograms) on charts using closing prices and volumes.

indicator_script.py

Calculates the Rate of Change (ROC) indicator for the loaded candles and plots both the candle series and indicator values.

normalize_price_script.py

Normalizes closing prices of multiple securities to start from 1, allowing them to be compared on the same chart.

pearson_correlation_script.py

Loads closing prices for multiple securities, computes the Pearson correlation matrix using NumPy.NET, and displays the matrix as a heatmap.

price_volume_script.py

Calculates how trading volume is distributed across price levels for a single security and draws the distribution as a histogram.

time_volume_script.py

Analyses when the largest trading volume occurs by grouping candles by hour and listing the totals in a grid.

Running Scripts

1. Ensure IronPython 3 is available on your PATH.
2. Launch StockSharp Designer or your own host application.
3. Load any of the .py files and execute the script. Most scripts expect candle data to be available in your storage; adjust the date range and security identifiers as needed.