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Module 2: Set Up Your Python Environment

What you will learn

  • Install Python and verify the version.
  • Install ddi-l and helper packages.
  • Confirm everything works by running a quick test.
  • Choose a workspace for writing Python code.

Prerequisites: Module 1: What Is Metadata and Why Does It Matter?

Time: 20 min self-paced / 30 min instructor-led.

1. What you need: Python 3.11 or newer

Python is a programming language. ddi-l runs inside Python, so you must have Python installed on your computer.

Open a terminal (also called a command prompt) and type:

python --version

You should see something like:

Python 3.12.3

The version number must be 3.11 or higher. If your version is older, visit https://www.python.org/downloads/ and install a newer version.

Common issue

On some systems the command is python3 instead of python. If python --version does not work, try python3 --version.

2. Install ddi-l

In your terminal, run:

pip install ddi-l

This command downloads ddi-l from the internet and installs it. The word pip is Python's package installer. It is the standard way to add new tools to your Python setup.

Next, install two helper packages you will need in later modules:

pip install pandas openpyxl
  • pandas is a popular tool for working with tables of data.
  • openpyxl lets Python read and write Excel files.

You can install everything in one line if you prefer:

pip install ddi-l pandas openpyxl

3. Check it works

3a. Test the command-line tool

ddi-l includes a command-line tool called ddi. Run:

ddi --help

You should see a list of available commands. This confirms the tool is installed and ready to use.

3b. Test in Python

Open a Python session by typing python in your terminal. Then type:

import ddi_l as ddi

print(ddi.__version__)

You should see a version number printed, such as 0.1.0. This confirms that Python can find and load the ddi-l package.

Type exit() to leave the Python session.

4. Choose your workspace

You can write Python code in several ways. Pick the one that feels most comfortable:

Workspace How to start Best for
Python REPL Type python in the terminal. Quick tests and exploring.
Script file Create a file like my_script.py. Saving your work.
Jupyter Notebook Run jupyter notebook in terminal. Step-by-step exploration.
  • REPL stands for Read-Eval-Print Loop. It is an interactive prompt where you type one line of Python at a time and see the result right away.
  • A script file is a plain text file ending in .py that you run all at once.
  • A Jupyter Notebook is a tool that lets you mix text, code, and output in one document.

For this curriculum, any of the three options will work.

5. More installation options

For advanced setups (such as installing from source code, using Poetry, or adding the optional lxml backend), see the full Installation guide.

Exercises

Scenario

You are setting up a new laptop for a training workshop. You need to make sure Python and ddi-l are ready to go before the workshop starts.

Exercise 1. Run the following command in your terminal:

pip install ddi-l pandas openpyxl

Paste the last line of the output. It usually says something like Successfully installed ....

Exercise 2. Open a Python session and run:

import ddi_l as ddi

print(ddi.__version__)

Write down the version number you see.

Exercise 3. Run ddi --help in your terminal. How many commands are listed in the output?

Quiz

Question 1: What is the minimum Python version for ddi-l?

A. Python 2.7

B. Python 3.8

C. Python 3.11

D. Python 3.14

Answer

C. ddi-l requires Python 3.11 or newer.

Question 2: Which command shows the ddi-l CLI help?

A. python --help

B. pip --help

C. ddi --help

D. ddi-l --help

Answer

C. The command ddi --help shows the list of commands available in the ddi-l command-line tool.

Question 3: What does pip install do?

A. It deletes old Python files.

B. It downloads and installs a Python package from the internet.

C. It opens a web browser.

D. It creates a new Python script.

Answer

B. pip install downloads a package from PyPI (the Python Package Index) and installs it on your computer so you can use it.

Instructor notes

  • Budget extra time for environment issues. Python version problems, permission errors, and network issues are common in live workshops.
  • Have a fallback ready: a cloud notebook (such as Google Colab) or a pre-built container with everything installed.
  • Why install pandas now? Installing it here avoids disruption in Module 6, where learners will load CSV and Excel files. Getting the install out of the way early keeps later modules focused on DDI.
  • Pair up learners who finish early with those who need help. Setup problems are easier to solve with a partner.