CCPP-I · Setup

First-day setup

Master TCCM · Universitat de València · October 2026

Do steps 1–3 before Monday if you can. If anything fails, stop there: we fix it together in the first hour of class.

Before class

Bring your own laptop, charged. The lab has desktop computers, but you will do the homework and the course project at home, so it must work on your machine.
Open the course notes and skim Setting yourself up: kimikateorikoa.github.io/python-notes-tccm
Accept the Slack invitation sent to your @alumni.uv.es address, and install Slack or check it works in your browser. Exercises, homework and questions all go through Slack.

Installation

Install Anaconda
Download the installer for your system from anaconda.com/download (the free "Distribution"; skip the registration if it is offered) and run it with the default options.

Windows: keep "Add to PATH" unticked, as the installer suggests; you will use Anaconda Prompt instead of the normal terminal.
Open a terminal and check
Windows: Start menu → Anaconda Prompt. macOS: Terminal. Linux: any terminal. Type:
```
conda --version
python --version
```
Both should print a version number. If conda is "not found", see Troubleshooting below.
Create the course environment
This installs Python and Jupyter Lab. It takes a few minutes; answer y when asked.
```
conda create -n pytccm -c conda-forge python=3.12 jupyterlab
```
The scientific libraries (NumPy, Matplotlib, SciPy, …) are installed during the course, when a class first needs them. The command is always of the form
```
conda install -c conda-forge <package>
```
Every time you open a new terminal to work on the course, activate the environment first:
```
conda activate pytccm
```
The prompt then starts with (pytccm). "Module not found" errors almost always mean you forgot this step.
Start Jupyter Lab
Make a folder for the course (for example pytccm in your home directory), move into it and start Jupyter Lab:
```
conda activate pytccm
mkdir pytccm
cd pytccm
jupyter lab
```
A browser tab opens. Leave the terminal window open while you work; Ctrl+C there stops Jupyter Lab.
Test it
In the Jupyter Lab Launcher tab click Python 3 under Notebook, type the line below in the first cell and run it with Shift+Enter.
```
print("Hello world!")
```
If it prints Hello world! with no error, you are ready.
A text editor (can wait until the first homework)
Homework is submitted as .py files, which you write in an editor, not in a notebook. Any editor works; VS Code with its Python extension is a good default. Jupyter Lab also has a built-in text editor (File → New → Python File).

Troubleshooting

conda: command not found (macOS / Linux)

The installer did not set up your shell. Run the line below once, then close and reopen the terminal.

~/anaconda3/bin/conda init

conda not recognized (Windows)

You are in PowerShell or cmd instead of Anaconda Prompt. Search the Start menu for "Anaconda Prompt" and use that window.

The conda create step is very slow or ends with a conflict

Update conda in the base environment and try again:

conda update -n base conda
conda create -n pytccm -c conda-forge python=3.12 jupyterlab

jupyter lab opens nothing

Copy the address printed in the terminal (it starts with http://localhost:8888/lab?token=) into your browser.

I already have Anaconda or Miniconda installed

Fine: skip step 1 and go straight to step 2.

Schedule

Aula PC-5, 1st floor, building E, Facultat de Química

Date	Time	Topic
Mon 5 Oct	09:00–13:00	Python fundamentals, control flow, functions
Thu 15 Oct	17:00–19:00	NumPy
Fri 16 Oct	09:00–13:00	Plotting, SciPy, ASE
Mon 26 Oct	09:00–13:00	Object-oriented programming; course project handed out
Fri 30 Oct	11:00–13:00	Open session: project questions, interactive widgets
Mon 2 Nov	09:00–13:00	Exam: oral discussion of your project

How the course works

In class we follow the online notes live. You get short exercises to solve on the spot and send on Slack.
After most classes there is a homework. It is due two days before the next class, so that there is time to look at it.
Homework is not marked for correctness. What counts is a genuine attempt on your own: the errors you make show which concepts need more time in class. Use the notes, the documentation and the web freely, but do not paste code from chatbots.
The course project (parsing a quantum chemistry output, two scripts) is handed out on 26 Oct and discussed one-to-one at the exam on 2 Nov.