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Indicator Setup

  • 373 installs
  • 13 repo stars
  • Updated June 12, 2026
  • marketcalls/openalgo-indicator-skills

indicator-setup is a Python environment setup skill that installs OpenAlgo indicator dependencies and scaffolds a project for developers building indicator analysis and dashboards.

About

indicator-setup is a Python environment setup skill that prepares a complete workspace for OpenAlgo indicator analysis, charting, and dashboard development by installing required packages and creating a project folder structure. indicator-setup supports a Python version argument and explicitly requires Python 3.12+ because the skill notes that openalgo 2.x needs Python 3.12 or newer. indicator-setup installs common visualization and app frameworks used in trading analytics workflows, including Plotly, Dash, and Streamlit, plus data and plotting dependencies such as yfinance, matplotlib, and seaborn. indicator-setup is a good choice when a developer wants a repeatable, scriptable starting point before writing indicator code, running backtests, building alerts, or publishing a local dashboard.

  • Indicator parameter tuning
  • OpenAlgo configuration
  • Signal rule definitions
  • Backtest hookup
  • Alert and notification setup

Indicator Setup by the numbers

  • 373 all-time installs (skills.sh)
  • +21 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #307 of 1,106 Finance & Trading skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-setup

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Listed on Skillselion
Installs373
repo stars13
Last updatedJune 12, 2026
Repositorymarketcalls/openalgo-indicator-skills

How do you set up OpenAlgo indicator analysis?

Configure technical indicators, parameters, and data feeds in OpenAlgo for backtests, alerts, and systematic trading workflows.

Who is it for?

indicator-setup fits developers bootstrapping a Python project for OpenAlgo indicators, charts, and dashboards.

Skip if: indicator-setup is not for developers who already have a working OpenAlgo Python environment and only need indicator logic.

When should I use this skill?

Invoke when a developer asks to set up OpenAlgo indicator analysis, create a Python venv, or install plotting and dashboard dependencies for trading analytics.

What you get

Python environment, installed dependencies, scaffolded project folder structure, version gate check for Python 3.12+.

  • python environment
  • project scaffold
  • installed dependencies

By the numbers

  • Requires Python 3.12 or newer for openalgo 2.x.
  • Installs 7 packages: openalgo, plotly, dash, streamlit, yfinance, matplotlib, seaborn.

Files

SKILL.mdMarkdownGitHub ↗

Set up the complete Python environment for OpenAlgo indicator analysis, charting, and dashboard development.

Arguments

  • $0 = Python version (optional, default: python3). Examples: python3.12, python3.13

Note: openalgo 2.x requires Python 3.12 or newer (3.12 / 3.13 / 3.14). Check the version before creating the venv and abort with a clear message if it is older:

python3 --version   # must be 3.12+

Steps

Step 1: Detect Operating System

uname -s 2>/dev/null || echo "Windows"

Map: Darwin = macOS, Linux = Linux, MINGW*/CYGWIN*/Windows = Windows.

Step 2: Create Virtual Environment

macOS / Linux:

python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip

Windows:

python -m venv venv
venv\Scripts\activate
pip install --upgrade pip

If user specified a Python version argument, use that instead of python3.

Step 3: Install Python Packages

Install all required packages:

pip install openalgo yfinance plotly dash dash-bootstrap-components streamlit numpy pandas python-dotenv websocket-client httpx scipy nbformat matplotlib seaborn ipywidgets

Step 4: Create Project Folders

Create only the top-level directories. Subdirectories are created on-demand by other skills.

mkdir -p charts dashboards custom_indicators scanners

Step 5: Configure .env File

5a. Ask the user for their OpenAlgo API key using AskUserQuestion:

  • "Enter your OpenAlgo API key (from the OpenAlgo dashboard at /apikey):"

5b. Ask for the OpenAlgo host URL:

  • Default: http://127.0.0.1:5000
  • If user has a custom domain or ngrok URL, use that

5c. Optionally ask about WebSocket URL:

  • Default: derived from host automatically
  • Only needed if user has a custom WebSocket setup

5d. Write the `.env` file in the project root:

# OpenAlgo API Configuration
OPENALGO_API_KEY={user_provided_key or "your_openalgo_api_key_here"}
OPENALGO_HOST={user_provided_host or "http://127.0.0.1:5000"}

# WebSocket (optional - auto-derived from host if not set)
# OPENALGO_WS_URL=ws://127.0.0.1:8765

5e. Add `.env` to `.gitignore`:

grep -qxF '.env' .gitignore 2>/dev/null || echo '.env' >> .gitignore

Step 6: Verify Installation

python -c "
import openalgo
from openalgo import ta
import plotly
import dash
import streamlit
import numpy as np
import pandas as pd
import yfinance as yf
import matplotlib
import seaborn
import nbformat
from dotenv import load_dotenv
print('All packages installed successfully')
print(f'  openalgo: {openalgo.__version__}')
print(f'  plotly: {plotly.__version__}')
print(f'  dash: {dash.__version__}')
print(f'  streamlit: {streamlit.__version__}')
print(f'  numpy: {np.__version__}')
print(f'  pandas: {pd.__version__}')
print(f'  matplotlib: {matplotlib.__version__}')
print(f'  seaborn: {seaborn.__version__}')

# Quick indicator test
close = np.array([100.0, 101.0, 102.0, 103.0, 104.0, 105.0, 104.0, 103.0, 102.0, 101.0])
ema = ta.ema(close, 3)
rsi = ta.rsi(close, 5)
print(f'  ta.ema test: {ema[-1]:.2f}')
print(f'  ta.rsi test: {rsi[-1]:.2f}')
print('Indicator library ready')
"

Step 7: Print Summary

Print a summary showing:

  • Detected OS
  • Python version used
  • Virtual environment path
  • Installed packages and versions
  • Project folders created
  • .env file status
  • Available skills: /indicator-chart, /custom-indicator, /indicator-dashboard, /indicator-scanner, /live-feed

Important Notes

  • Never install packages globally — always use the virtual environment
  • If the user already has a virtual environment, ask before creating a new one
  • NEVER commit .env files — they contain API keys
  • python-dotenv is used by all scripts to load .env via find_dotenv()
  • openalgo 2.x indicators run on a compiled Rust core inside the wheel — no JIT compilation or warmup; requires Python 3.12+

Related skills

How it compares

Pick this when you need reproducible environment setup and scaffolding rather than strategy guidance or broker API integration.

FAQ

What Python version does indicator-setup require?

indicator-setup requires Python 3.12 or newer because the skill states that openalgo 2.x needs Python 3.12+; indicator-setup is designed to check the Python version before creating the venv and to abort with a clear message if the version is too old.

Which libraries does indicator-setup install?

indicator-setup installs openalgo along with Plotly, Dash, Streamlit, yfinance, matplotlib, and seaborn to support indicator analysis, charting, and dashboard development in a single reproducible Python environment.

What does indicator-setup create besides installing packages?

indicator-setup creates a project folder structure intended for OpenAlgo indicator analysis workflows, so developers can start adding indicator code, notebooks, dashboards, and supporting assets in a consistent layout.

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