A beginner's guide to setting up and using the Stock Indicators for Python library for financial market analysis.

git clone https://github.com/facioquo/stock-indicators-python-quickstart.git cd stock-indicators-python-quickstart python -m venv .venv source .venv/bin/activate # On Windows use: .venv\Scripts\activate pip install stock-indicators python main.py

Required software versions:

• Python ≥ 3.8
• .NET SDK ≥ 6.0
• Git (any recent version)
• VS Code (recommended)

VS Code Extensions:

• Python Extension Pack (includes primary Python extension)
• Pylance
• Python Debugger

# Verify installations python --version # Should be ≥ 3.8 dotnet --version # Should be ≥ 6.0

1. Create a new project folder.

2. Optional: initialize a git repository in this folder with git init bash command and add a Python flavored .gitignore file. I found this one in the gitignore templates repo.

3. Initialize Python workspace with a virtual environment (a cached instance):

   # create environment python -m venv .venv # then activate it source .venv/bin/activate # On Windows use: .venv\Scripts\activate

   You can also use VS Code command: Python: Create Environment ... and then Python: Select Interpreter to pick your just created venv instance. When done correctly, you should have a .venv folder in the root of your project folder. There are other ways to initialize in a global environment; however, this is the recommended approach from the Python tutorial I'd mentioned above.

4. Install the stock-indicators package from PyPI

   # install the package pip install stock-indicators

   I'm using v1.3.1, the latest version. You should see it installed in .venv/Lib/site-packages.

   # verify the install pip freeze --local

   ... clr-loader==0.2.7 pycparser==2.22 pythonnet==3.0.5 stock-indicators==1.3.1 typing_extensions==4.12.2 ...

It's time to start writing some code.

5. To start, add a quotes.csv file containing historical financial market prices in OHLCV format. Use the one I put in this repo. You can worry about all the available stock quote sources later.

6. Create a main.py file and import the utilities we'll be using at the top of it.

   import csv from datetime import datetime from itertools import islice from stock_indicators import indicators, Quote

7. Import the data from the CSV file and convert it into an iterable list of the Quote class.

   # Get price history data from CSV file with open("quotes.csv", "r", newline="", encoding="utf-8") as file: rows = list(csv.reader(file)) # Convert rows into Quote objects that stock-indicators understands # CSV returns strings, but Quote needs numbers for prices and volume quotes = [] for row in rows[1:]: # skip header row quotes.append( Quote( datetime.strptime(row[0], "%Y-%m-%d"), # date row[1], # open row[2], # high row[3], # low row[4], # close row[5], # volume ) )

   These quotes can now be used by the stock-indicators library. For a quickstart that uses pandas.DataFrame, see our online ReplIt code example for the Williams Fractal indicator.

8. Calculate an indicator from the quotes

   # Calculate 5-period Simple Moving Average results = indicators.get_sma(quotes, 5)

9. Configure results for console output

   # Show the results print("Date SMA") for r in islice(results, 0, 30): # show first 30 days sma = f"{r.sma:.3f}" if r.sma else "" print(f"{r.date:%Y-%m-%d} {sma}")

10. Click the Run Python File in Terminal (►) play button in the top-right side of the VS Code editor to run the code, or execute from the commandline in your bash terminal. The SMA indicator output will print to the console.

    # from CLI (optional) python main.py

    Date SMA -------------------- 2017-01-03 2017-01-04 2017-01-05 2017-01-06 2017-01-09 213.872 2017-01-10 214.102 2017-01-11 214.200 2017-01-12 214.226 2017-01-13 214.196 2017-01-17 214.156 2017-01-18 214.210 2017-01-19 213.986 2017-01-20 214.024 ...

    The small deviations shown in these raw results are normal for double floating point precision data types. They're not programming errors. Developers will usually truncate or round to fewer significant digits when displaying. We're showing 3 decimal places here.

You've done it! That's the end of this QuickStart guide.

• Import errors: Ensure you've activated the virtual environment
• Runtime errors: Verify .NET SDK installation
• .NET loading issues: On Linux/macOS, you may need additional dependencies

• Explore all available indicators
• Learn about data sources
• Join our community discussions

Having trouble? Try these resources:

• Documentation
• GitHub Discussions
• Stack Overflow

Built something cool? Share it with the community!

— @DaveSkender, January 2025