GithubHelp home page GithubHelp logo

peculiar97 / intro_python Goto Github PK

View Code? Open in Web Editor NEW

This project forked from benedictpaten/intro_python

0.0 0.0 0.0 5.24 MB

Lecture Notes and Slides for UCSC CSE20, formatted as Jupyter Notebooks.

License: MIT License

Shell 0.06% Jupyter Notebook 99.94%

intro_python's Introduction

These are lecture notes for the UCSC CSE20: Beginning Programming in Python course

Each lecture is composed of a Jupyter notebook.

The lecture syllabus is here: https://bit.ly/intro_python_00

You can view each of these notebooks using Google Colab.

Google Colab provides a notebook environment you can run from your web browser without installing any software.

Step 1: open Google Colab.

Step 2: paste https://github.com/benedictpaten/intro_python into the Github URL search box under the Github tab (hit return).

Step 3: pick the notebook for the lecture you want.

For an introduction to using Google Colab (and Juptyer Notebooks in general) see the following tutorial.

To install and use these notebooks on your computer with Jupyter

If you prefer to have these notebooks installed on your computer and to use Jupyter to edit them follow the following instructions.

These instructions should work on Linux or Mac OS and require you to be familiar with using unix shell commands (e.g. with a terminal app). It is not necessary to install these notebooks on your computer to take this course.

First, make sure you have python3 installed on your computer.

Next make a directory to hold the notebooks:

mkdir cse20 && cd cse20

To avoid problems with conflicting versions of dependencies on your system, we strongly recommend installing these notebooks inside a Python 3 virtual environment. To install the virtualenv command, if you don't have it already, run:

python3 -m pip install virtualenv

To set up a virtual environment in the directory python_intro_env, run:

python3 -m virtualenv -p python3.9 python_intro_env

Then, to enter the virtualenv, run:

source python_intro_env/bin/activate

You can always exit out of the virtualenv by running deactivate.

To install these notebooks in Python, clone the repo:

git clone https://github.com/benedictpaten/intro_python.git
cd intro_python

Now install Jupyter and some Python packages we'll use:

pip install jupyter
pip install rise
pip install numpy
pip install pandas
pip install matplotlib

Now you're ready to run the notebooks:

jupyter notebook

That's it! A browser should then open showing you the running Juptyer notebook launch page. Simply navigate to the desired notebook and select it to open.

Later, after following the above steps, if you want to start the notebook server again (e.g. after shutting down the computer) simply navigate to the cse20 directory in the terminal and then execute the following two commands:

source python_intro_env/bin/activate
jupyter notebook

When you're finished with these notebooks you just need to delete the parent directory (cse20) and everything we've installed (including all the notebooks, Jupyter and Python packages, but not including Python3) will be removed.

rm -rf cse20

Building html versions of the notebooks as slides

If you've followed the above instructions to download and run the notebooks on your computer you can build html formatted versions of the slides by running the make_slides.sh script in the intro_python subdirectory:

./make_slides.sh

However, you may prefer to use RISE to view the slides (it is installed with the above instructions). RISE allows you to interactively edit and run the notebook and toggle back and forth into a slide viewer.

intro_python's People

Contributors

benedictpaten avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.