Intro to Version Control with Git


Teaching: 30 min
Exercises: 5 min
  • How do I use git to keep a record of my project?

  • Explain the purpose of version control.

  • Introduce common git commands.

  • Understand how to view and check out previous versions of files.


  • Created GitHub account (described in set-up)
  • Configured git (described in set-up)
  • The Python package created in Episode 1.

Version Control

Version control keeps a complete history of your work on a given project. It facilitates collaboration on projects where everyone can work freely on a part of the project without overwriting others’ changes. You can move between past versions and rollback when needed. Also, you can review the history of your project through commit messages that describe changes on the source code, and see what exactly has been modified in any given commit. You can see who made the changes and when it happened.

This is greatly beneficial whether you are working independently or within a team.

git vs. GitHub

git is the software used for version control, while GitHub is a hosting service. You can use git locally (without using an online hosting service), or you can use it with other hosting services such as GitLab or BitBucket. Other examples of version control software include Subversion (svn) and Mercurial (hg).

MolSSI recommends using git for version control, and GitHub as a hosting service, though there are other options.

Recommended Hosting Service: GitHub
Other hosting Services: GitLab, BitBucket

Making Commits

You should have git installed and configured from the setup instructions.

In this section, we are going to edit files in the Python package that we created earlier, and use git to track those changes.

First, use a terminal to cd into the top directory of the local repository.

In order for git to keep track of your project, or any changes in your project, you must first tell it that you want it to do this. You must manually create check-points in your project if you wish to have points to return to. If you were not using the CookieCutter, you would first have to initialize your project (i.e. tell git that you were working on a project) using the command git init.

When we ran the CMS CookieCutter, it actually initialized git for us, added our files, and made a commit (how convenient!). We can see this by typing the following into the terminal on Linux or Mac

$ ls -la

Here, the -la says that we want to list the files in long format (-l), and show hidden files (-a).

If you are on Windows and using the Anaconda Prompt:

dir /a

If you are on Windows and using the Anaconda PowerShell Prompt:

> ls -hidden

You should see .git in the output. .git is a directory where git stores the repository data. This is one way to see that we are in a git repository.

Next, type

$ git status
On branch main
nothing to commit, working tree clean

This tells us that we are on the main branch (more about branching later), and that no files have been changed since the last commit.

Next, type

$ git log

You will get an output resembling the following. This is something called your git commit log. Whenever you make a version, or checkpoint, of your project, you will be able to see information about that checkpoint using the git log command. The CookieCutter has already made a commit and written a message for you, and that is what we see for this first commit in the log.

commit 25ab1f1a066f68e433a17454c66531e5a86c112d (HEAD -> main, tag: 0.0.0)
Author: Your Name <>
Date:   Mon Feb 4 10:45:26 2019 -0500

    Initial commit after CMS Cookiecutter creation, version X.X

Your version number for the Cookiecutter will depend on when you ran the Cookiecutter and the current released version.

Each line of this log tells you something important about the commit, or check point, that exists for the project. On the first line,

commit 25ab1f1a066f68e433a17454c66531e5a86c112d (HEAD -> main, tag: 0.0.0)

You have a unique identifier for the commit (25ab1…). You can use this hexadecimal number to reference this checkpoint.

Then, git records the name of the author who made the change.

Author: Your Name <>

This should be your information. This way, anyone who downloads this project can see who made each commit. Note that this name and email address matches what you specified when you configured git in the setup, with the name and email address you specified to cookiecutter having no effect.

Date:   Mon Feb 4 10:45:26 2019 -0500

Next, it lists the date and time the commit was made.

    Initial commit after CMS Cookiecutter creation, version 1.0

Finally, there will be a blank line followed by a commit message. The commit message is a message that whoever made the commit chose to write, but should describe the change that took place when the commit was made. This commit message was written by cookiecutter for you.

When we have more commits (or versions) of our code, git log will show a history of these commits, and they will all have the same format discussed above. Right now, we have only one commit: the one created by the CMS CookieCutter.

The 3 steps of a commit

Now, we will change some files and use git to track those changes.

Let’s edit our README. Open in your text editor of choice. On line 8, you should see the description of the repository we typed when running cookiecutter.

Add the following sentence to your under the initial description and save the file.

This repository is currently under development. To do a development install, download this repository and type

`pip install -e .`

in the repository directory.

git add, git status, git commit

Making a commit is like making a checkpoint for a particular version of your code. You can easily return to, or revert to that checkpoint.

To create the checkpoint, we first have to make changes to our project. We might modify many files at a time in a repository. Thus, the first step in creating a checkpoint (or commit) is to tell git which files we want to include in the checkpoint. We do this with a command called git add. This adds files to what is called the staging area.

Let’s look at our output from git status again.

On branch main
Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git checkout -- <file>..." to discard changes in working directory)


no changes added to commit (use "git add" and/or "git commit -a")

Git even tells us to use git add to include what will be committed. Let’s follow the instructions and tell git that we want to create a checkpoint with the current version of

$ git add
$ git status
On branch main
Changes to be committed:
  (use "git reset HEAD <file>..." to unstage)


We are now on the second step of creating a commit. We have added our files to the staging area. In our case, we only have one file in the staging area, but we could add more if we needed.

To create the checkpoint, or commit, we will now use the git commit command. We add a -m after the command for “message.” Whenever you create a commit, you should write a message about what the commit does.

$ git commit -m "update readme to have instructions for developmental install"

Now when we look at our log using git log, we see the commit we just made along with information about the author and the date of the commit.

If you neglect the -m option, and you configured an editor during set-up, git will open the editor for you to compose your commit message.

Let’s continue to edit this readme to include more information. This is a file which will describe what is in this directory. Open in your text editor of choice and add the following to the end.

This package requires the following:
  - numpy
  - matplotlib

This file is using a language called Markdown.

Check your understanding

Create a commit for these changes to your repository.


To add the file to the staging area and tell git we would like to track the changes to the file, we first use the git add command.

$ git add

Now the file is staged for a commit. Next, create the commit using the git commit command.

$ git commit -m "add information about dependencies to readme"

Once you have saved this file, type

$ git log

Now, check git status and git log. You should see the following:

$ git status
On branch main
nothing to commit, working tree clean
$ git log

We now have a log with three commits. This means there are three versions of the repository we are working in.

git log lists all commits made to a repository in reverse chronological order. The listing for each commit includes the commit’s full identifier, the commit’s author, when the commit was created, and the commit title.

We can see differences in files between commits using git diff.

$ git diff HEAD~1

The argument to git diff refers to the comparison point in our commit history. HEAD is an alias for the commit at the tip of our checked-out branch. ~1 is a modifier that refers to the given commit minus 1. We are asking git to show us the difference between the current files and the second-most-recent commit.

Lines that have been added are indicated in green with a plus sign next to them (+), while lines that have been deleted are indicated in red with a minus sign next to them (-)

Viewing our previous versions

If you need to check out a previous version,

$ git checkout COMMIT_ID

This will temporarily revert the repository to whatever the state was at the specified commit ID.

Let’s checkout the version before we made the most recent edit to the README.

$ git log --oneline
d857c74 (HEAD -> main) add information about dependencies to readme
3c0e1c6 update readme to have instructions for developmental install
116f0cf (tag: 0.0.0) Initial commit after CMS Cookiecutter creation, version 1.1

In this log, the commit ID is the first number on the left.

To revert to the version of the repository where we first edited the readme, use the git checkout command with the appropriate commit ID.

$ git checkout 3c0e1c6

If you now view your, it has reverted to the previous version of the file.

To return to the most recent point,

$ git checkout main


What list of commands would mimic what CMS CookieCutter did when it created the repository and performed the first commit? (hint - to initialize a repository, you use git init)


To recreate the CMS Cookiecutter’s first commit exactly,

$ git init
$ git add .
$ git commit -m "Initial commit after CMS Cookiecutter creation, version 1.0"

The first line initializes the git repository. The second line add all modified files in the current working directory, and the third line commits these files and writes the commit message.

Creating new features - using branches

When you are working on a project to implement new features, it is a good practice to isolate the changes you are making and work on one particular topic at a time. To do this, you can use something called a branch in git. Working on branches allows you to isolate particular changes. If you make sure that your code works before merging to your main or main branch, you will ensure that you always have a working version of code on your main branch.

If you followed the set-up instructions, you should be in the main branch by default. To create a new branch and move to it, you can use the command

$ git checkout -b new_branch_name

The command git checkout switches branches when followed by a branch name. When you use the -b option, git will create the branch and switch to it. For this exercise, we will add a new feature: We are going to add a function to print the Zen of Python.

First, we’ll create a new branch:

$ git checkout -b zen

Next, add a new function to your module. We are going to add the ability to print “The Zen of Python”. You can get the Zen of Python by typing

import this

into the interactive Python prompt.

def zen(with_attribution=True):
    quote = """Beautiful is better than ugly.
    Explicit is better than implicit.
    Simple is better than complex.
    Complex is better than complicated.
    Flat is better than nested.
    Sparse is better than dense.
    Readability counts.
    Special cases aren't special enough to break the rules.
    Although practicality beats purity.
    Errors should never pass silently.
    Unless explicitly silenced.
    In the face of ambiguity, refuse the temptation to guess.
    There should be one-- and preferably only one --obvious way to do it.
    Although that way may not be obvious at first unless you're Dutch.
    Now is better than never.
    Although never is often better than *right* now.
    If the implementation is hard to explain, it's a bad idea.
    If the implementation is easy to explain, it may be a good idea.
    Namespaces are one honking great idea -- let's do more of those!"""

    if with_attribution:
      quote += "\n\tTim Peters"

    return quote

Verify that this function works in the interactive Python prompt. Next, commit this change:

$ git add .
$ git commit -m "add function to print Zen of Python

Let’s switch back to the main branch to see what it is like. You can see a list of branches in your repo by using the command

$ git branch

This will list your local branches. The active branch, or the branch you are on will be noted with an asterisk (*).

To switch back to the main branch,

$ git checkout main

When you look at the module on the main branch, you should not see your most recent changes.

You can verify this by using the git log command.

Consider that at the same time we have some changes or features we’d like to implement. Let’s make a branch to do a documentation update.

Create a new branch.

$ git checkout -b doc_update

Let’s add some information about developing on branches to the README. Update your README to include this information:

Features should be developed on branches. To create and switch to a branch, use the command

`git checkout -b new_branch_name`

To switch to an existing branch, use

`git checkout new_branch_name`

Save and commit this change.

To incorporate these changes in main, you will need to do a git merge. When you do a merge, you should be on the branch you would like to merge into. In this case, we will first merge the changes from our doc_update branch, then our zen branch, so we should be on our main branch. Next we will use the git merge command.

The syntax for this command is

$ git merge branch_name

where branch_name is the name of the branch you would like to merge.

We can merge our doc_update branch to get changes on our main branch:

$ git checkout main
$ git merge doc_update

Now our changes from the branch are on main.

We can merge our zen branch to get our changes on main:

$ git merge zen

This time, you will see a different message, and a text editor will open for a merge commit message.

Merge made by the 'recursive' strategy.

This is because main and zen have development histories which have diverged. git had to do some work in this case to merge the branches. A merge commit was created.

Merge commits create a branched git history. We can visualize the history of our project by adding --graph. There are other workflows you can use to make the commit history more linear, but we will not discuss them in this course.

Once we are done with a feature branch, we can delete it:

$ git branch -d zen

Using Branches - Exercise

For this exercise, you will be adding all the functions from your Jupyter notebook to the package. Create a branch to add your functions. Add all of the functions from your Jupyter notebook to the module in your package. Verify that you can use your functions. Once the functions are added and working, merge into your main branch.


First, create a new branch in your repository

$ git checkout -b add-functions

Next, copy all of your imports from the first cell of your Jupyter notebook and paste them into the top of your file.

Next, copy the function definitions from the first cell and paste them above or below the canvas function.

Your file should look something like this.

A Python package for analyzing and visualizing xyz files. For MolSSI Workshop Python Package development workshop.

Handles the primary functions

import os
import numpy as np
import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

def canvas(with_attribution=True):
    Placeholder function to show example docstring (NumPy format)

    Replace this function and doc string for your own project

    with_attribution : bool, Optional, default: True
        Set whether or not to display who the quote is from

    quote : str
        Compiled string including quote and optional attribution

    quote = "The code is but a canvas to our imagination."
    if with_attribution:
        quote += "\n\t- Adapted from Henry David Thoreau"
    return quote

def zen():
    quote = """Beautiful is better than ugly.
    Explicit is better than implicit.
    Simple is better than complex.
    Complex is better than complicated.
    Flat is better than nested.
    Sparse is better than dense.
    Readability counts.
    Special cases aren't special enough to break the rules.
    Although practicality beats purity.
    Errors should never pass silently.
    Unless explicitly silenced.
    In the face of ambiguity, refuse the temptation to guess.
    There should be one-- and preferably only one --obvious way to do it.
    Although that way may not be obvious at first unless you're Dutch.
    Now is better than never.
    Although never is often better than *right* now.
    If the implementation is hard to explain, it's a bad idea.
    If the implementation is easy to explain, it may be a good idea.
    Namespaces are one honking great idea -- let's do more of those!"""
    return quote

def calculate_distance(rA, rB):
    return dist

def open_pdb(f_loc):
    with open(f_loc) as f:
        data = f.readlines()
    c = []
    sym = []
    for l in data:
        if 'ATOM' in l[0:6] or 'HETATM' in l[0:6]:
            c2 = [float(x) for x in l[30:55].split()]
    coords = np.array(c)
    return sym, coords

atomic_weights = {
    'H': 1.00784,
    'C': 12.0107,
    'N': 14.0067,
    'O': 15.999,
    'P': 30.973762,
    'F': 18.998403,
    'Cl': 35.453,
    'Br': 79.904,

def open_xyz(file_location):
    # Open an xyz file and return symbols and coordinates.
    xyz_file = np.genfromtxt(fname=file_location, skip_header=2, dtype='unicode')
    symbols = xyz_file[:,0]
    coords = (xyz_file[:,1:])
    coords = coords.astype(np.float)
    return symbols, coords

def write_xyz(file_location, symbols, coordinates):
    num_atoms = len(symbols)
    with open(file_location, 'w+') as f:
        f.write('XYZ file\n')
        for i in range(num_atoms):
                                              coordinates[i,0], coordinates[i,1], coordinates[i,2]))

def draw_molecule(coordinates, symbols, draw_bonds=None, save_location=None, dpi=300):
    # Create figure
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    # Get colors - based on atom name
    colors = []
    for atom in symbols:
    size = np.array(plt.rcParams['lines.markersize'] ** 2)*200/(len(coordinates))

    ax.scatter(coordinates[:,0], coordinates[:,1], coordinates[:,2], marker="o",
               edgecolors='k', facecolors=colors, alpha=1, s=size)
    # Draw bonds
    if draw_bonds:
        for atoms, bond_length in draw_bonds.items():
            atom1 = atoms[0]
            atom2 = atoms[1]
            ax.plot(coordinates[[atom1,atom2], 0], coordinates[[atom1,atom2], 1],
                    coordinates[[atom1,atom2], 2], color='k')
    # Save figure
    if save_location:
        plt.savefig(save_location, dpi=dpi, graph_min=0, graph_max=2)
    return ax

def calculate_angle(rA, rB, rC, degrees=False):
    AB = rB - rA
    BC = rB - rC
    theta=np.arccos(, BC)/(np.linalg.norm(AB)*np.linalg.norm(BC)))

    if degrees:
        return np.degrees(theta)
        return theta

def bond_histogram(bond_list, save_location=None, dpi=300, graph_min=0, graph_max=2):
    lengths = []
    for atoms, bond_length in bond_list.items():
    bins = np.linspace(graph_min, graph_max)
    fig = plt.figure()
    ax = fig.add_subplot(111)
    plt.xlabel('Bond Length (angstrom)')
    plt.ylabel('Number of Bonds')
    ax.hist(lengths, bins=bins)
    # Save figure
    if save_location:
        plt.savefig(save_location, dpi=dpi)
    return ax
def build_bond_list(coordinates, max_bond=1.5, min_bond=0):
    # Find the bonds in a molecule
    bonds = {}
    num_atoms = len(coordinates)

    for atom1 in range(num_atoms):
        for atom2 in range(atom1, num_atoms):
            distance = calculate_distance(coordinates[atom1], coordinates[atom2])
            if distance > min_bond and distance < max_bond:
                bonds[(atom1, atom2)] = distance

    return bonds

atom_colors = {
    'H': 'white',
    'C': '#D3D3D3',
    'N': '#add8e6',
    'O': 'red',
    'P': '#FFA500',
    'F': '#FFFFE0',
    'Cl': '#98FB98',
    'Br': '#F4A460',
    'S': 'yellow'

if __name__ == "__main__":
    # Do something if this file is invoked on its own

Open the interactive Python interface and try out some functions to verify that your package still works.

Make a commit to commit this change to your branch:

$ git add .
$ git commit -m "add functions to package"

Next, switch back to your main branch to merge:

$ git checkout main
$ git merge add-functions

More Tutorials

If you want more git, see the following tutorials.

Basic git

Key Points

  • Git provides a way to track changes in your project.

  • Git is a software for version control, and is separate from GitHub.