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Git Fetch vs. Git Pull

Git Fetch vs. Git Pull
Hostman Team
Technical writer
Git
20.02.2025
Reading time: 10 min

In most cases, working with the Git version control system is done locally. However, you sometimes need to sync with a remote repository to update your local storage. Git provides two key commands for this: git fetch and git pull.

A remote repository is a storage location hosted on the network, usually on platforms like GitHub, GitLab, or Bitbucket. These services allow developers to collaborate on projects, make changes, and synchronize code between local and remote versions.

Both commands are used to download updates from a remote repository, but they work differently. In this guide, we will explore their practical applications and highlight their key differences.

Prerequisites

Since this article covers practical usage, you’ll need the following:

  • A server, virtual machine, or computer with any operating system where Git can be installed.
  • A Git client pre-installed.
  • An account on GitHub.

The git fetch Command

Let’s start with what git fetch does. git fetch is used to grab the latest data from a remote repository and put it into your local storage without modifying any files in your working directory. Instead, it updates the so-called remote-tracking branches, which reflect the state of the remote repository at the time the command is executed.

This is how git fetch works:

  1. Establishes a connection with the remote repository.
  2. Downloads new commits, files, branches, and tags.
  3. The data is added to the local repository but not merged with the current working branch.

Basic syntax of git fetch:

git fetch <remote-repository-url>

Useful options:

  • git fetch --all — Downloads updates from all remote repositories linked to the local storage.
  • git fetch --dry-run — Checks for changes before downloading without making any actual changes.
  • git fetch --force — Forcefully updates data in the local repository, overwriting any conflicts.
  • git fetch --tags — Downloads all tags from the remote repository.
  • git fetch --prune — Removes references to branches that were deleted in the remote repository.

The git pull Command

Unlike git fetch, the git pull command downloads the latest changes from a remote repository and automatically merges them into your current local branch. Essentially, executing git pull involves two operations:

  1. git fetch — Downloads new data.
  2. git merge — Merges the downloaded changes with the local branch.

This is how git pull works:

  1. Establishes a connection with the remote repository.
  2. Downloads the latest data, including commits, files, tags, and branches.
  3. The downloaded changes are merged into the current local branch.

Basic syntax of git pull:

git pull

Useful options:

  • git pull [remote-repository] [branch] — Downloads changes only from the specified repository and branch. For example, git pull origin main updates the local main branch from the remote repository origin.

  • git pull --rebase — Instead of performing a standard merge, this applies the changes on top of the local commits, helping to avoid unnecessary merge commits.

Comparison: git fetch vs git pull

To better understand the differences between these two commands, here's a comparison table:

Criterion

git fetch

git pull

Action

Only downloads changes

Downloads and merges changes

Impact on Local Repository

Does not modify files or branches

Modifies the current branch and files

Safety

Safe, as it does not cause conflicts

May cause conflicts during merging

Previewing Changes

Allows reviewing and analyzing changes before merging

Automatically integrates changes without preview

Flexibility

Requires manual merging

Merges automatically

When to Use Git Fetch vs. Git Pull

When to Use git fetch

  • Before Making Changes to the Source Codegit fetch allows you to see which commits have been made on the remote branch and evaluate the changes before merging them into your local branch.

  • When Working in a Team: If multiple developers are working on the project, git fetch helps you stay up-to-date with their work and minimize potential conflicts before integrating changes.

  • To Retrieve New Branches and Tags: If a new branch or tag has been added to the remote repository, git fetch will download them without automatically switching to them.

When to Use git pull

  • To Get the Latest Changes: In team projects, members regularly make updates. To bring all the latest changes into your local repository, use git pull.

  • For Quick Branch Updates: If you need to quickly update your branch without analyzing the changes beforehand, using git pull is the easiest approach.

Using Git Fetch and Git Pull in Practice

Creating a Repository on GitHub

  1. Log in to GitHub. If you don’t have an account, you can register a new one.
  2. Click on the New button to create a new repository. Provide a name for the repository and select the Public option.

1

  1. Click on your profile picture in the upper-right corner and select Settings from the drop-down menu.
  2. Scroll down to Developer settings on the left.

Image4

  1. Expand Personal access tokens and go to Tokens (classic).
  2. Click on Generate new token, then Generate new token (classic). If prompted, authenticate using the mobile app.

Image15

  1. Give the token a name and set an expiration date. Under permissions, select the repo category.

Image12

  1. Click on Generate token to create the token.
  2. Copy and save the token, as it won’t be shown again.

Creating a Local Repository

  1. Go to the server where Git is installed. Create a new directory to store your files and navigate to it:

mkdir test-git-fetch-pull && cd test-git-fetch-pull
  1. Initialize a new Git repository:

git init
  1. Create a new file and add a line to it:

echo "Test git fetch and pull commands!" > newfile1.txt
  1. Add the file to the staging area:

git add newfile1.txt
  1. Create an initial commit:

git commit -m "Initial commit"

If you see the message:

Author identity unknown
*** Please tell me who you are

You need to set your name and email using:

git config --global user.email "example@example.com"
git config --global user.name "<name>"

Then, repeat the commit command:

git commit -m "Initial commit"
  1. Add the remote repository. Use the command from the main page of your newly created repository on GitHub. For example:

git remote add origin https://github.com/<github-account>/test-git-fetch-pull.git

2

  1. Push changes to the remote repository:

git push -u origin main

When prompted for Username for 'https://github.com', enter your GitHub username. When prompted for Password for 'https://<username>@github.com', enter the previously generated token.

Go back to the GitHub web interface and check that the file is present in the repository.

Image21

Working with Changes

Now, let’s simulate changes in the remote repository.

  1. Open the file for editing directly in the GitHub interface.

Image20

  1. Add a new line at the end of the file.

Image19

  1. Click the Commit changes button on the right.
  2. Go back to the server where your local repository is located and run:
git fetch origin
  1. Now, check the file content:

cat newfile1.txt

Image3

You'll notice that git fetch downloaded the changes from the remote repository, but the local branch (main) and the file remained unchanged.

However, the changes can be seen in the remote branch:

git log origin/main

4

To see exactly what changes were made in the remote repository after running git fetch, use:

git diff main origin/main

Image23

  1. Now, let's pull the changes into the local branch:

git pull origin main
  1. Display the file content again:

cat newfile1.txt

Image14

Now, the changes made in the GitHub interface are applied to the local copy of the repository.

Resolving Conflicts When Using git pull

When using git pull, you may encounter conflicts. In Git terminology, a conflict occurs when the system cannot automatically merge changes from two different sources — the local and remote repositories.

To learn how to resolve conflicts, let's go through a practical example. We'll simulate the following situation:

  • We have a repository containing a file named future-file1.txt.
  • Two developers (Developer 1 and Developer 2) are working on the same branch (main).

Preparing the Repository

  1. Create a new repository in GitHub. Follow the same steps as in the previous chapter to create a new repository.
  2. On the server, create a new directory and navigate to it:
mkdir git-conflicts && cd git-conflicts
  1. Initialize the Git repository:

git init
  1. Create a new file:

touch future-file1.txt
  1. Write the first line into the file:
echo "First message" > future-file1.txt
  1. Stage the file:
git add future-file1.txt
  1. Commit the changes:
git commit -m "Initial commit"
  1. Connect the local repository to GitHub. Replace the URL with the one for your GitHub repository:
git remote add origin https://github.com/<github-account>/git-conflicts.git
  1. Push changes to the remote repository:
git push -u origin main

You'll be prompted to enter your GitHub username and personal access token.

Making Changes as Developer 2

Now, let's simulate the scenario from the perspective of the second developer (Developer 2). On another machine or in a new directory on the same server, run:

git clone https://github.com/<github-account>/git-conflicts.git

At this point, both developers have an up-to-date copy of the repository.

Making Changes as Developer 1

Switch back to the local repository used by Developer 1:

  1. Add a new line by overwriting the content of future-file1.txt:

echo "Second message" > future-file1.txt
  1. Stage the changes:

git add future-file1.txt
  1. Commit the changes:

git commit -m "Second commit"
  1. Push changes to the remote repository:

git push origin main

Conflict

At this point, Developer 1's changes are in the remote repository. However, Developer 2 still has the old version of future-file1.txt.

  1. Navigate to the project folder that was previously cloned by Developer 2.
  2. Overwrite the file by adding a new message:
echo "Third message" > future-file1.txt
  1. Stage the file:
git add future-file1.txt
  1. Commit the changes:
git commit -m "Third commit"
  1. Pull the latest changes from the remote repository:
git pull origin main

As you can see, Git has detected a conflict:

6

When viewing the file, you will notice a conflict block in the file, marking the conflicting changes.

Image22

Resolving the Conflict

To resolve the conflict, you need to delete the lines starting with <<<<<<< and ending with >>>>>>>. Then, you can decide whether to keep only the local changes or to retain the old ones and add the new ones.

As an example, let's keep the changes from both developers:

  • Developer 1's message ("Second message")
  • Developer 2's message ("Third message")

Image18

After editing the file, stage it again:

git add future-file1.txt

Commit the resolved conflict:

git commit -m "Resolved conflict"

Push the changes to the remote repository:

git push origin main

You will need to enter your username and token to push the changes.

Go to the GitHub interface and verify the result.

7

Conclusion

The git fetch and git pull commands are used to retrieve the latest changes from a remote repository into your local repository, but they do so differently.

  • git fetch allows you to safely fetch updates and analyze the changes made by others without affecting your current working copy. This is especially useful for avoiding unexpected conflicts, as no changes are applied automatically.

  • git pull fetches the data and immediately merges it into the local repository. This process requires caution. If conflicts occur, you will need to resolve them manually.

The choice between these commands depends on your goals:

  • If you want to check changes first, use git fetch.
  • If you need to quickly update the code, use git pull, but be aware of the possible conflicts.
Git
20.02.2025
Reading time: 10 min

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Key Features of GitHub Copilot Autocomplete – Provides real-time code suggestions and autocompletion. Code Prediction – Predicts the next steps in your code and offers options to complete structures. Code Search – Helps find relevant code within a project using keywords or code snippets. Code Refactoring – Assists in optimizing and modifying existing code with refactoring features. GitHub Copilot is currently available as a subscription service for $10 monthly. How GitHub Copilot Works GitHub Copilot provides suggestions and autocomplete features based on user comments written in natural language and existing code. To achieve this, GitHub trained Copilot using publicly available repositories hosted on its platform. The effectiveness of Copilot depends on the availability of public repositories in a given programming language. It works well with popular languages like Python and offers reliable suggestions. However, for less common languages, its performance may be weaker, providing fewer and less accurate recommendations. Integrating GitHub Copilot with PyCharm PyCharm, a JetBrains IDE, supports GitHub Copilot. To integrate it into your project, follow these steps: Visit github.com/features/copilot and click Get started for free. Log in to GitHub or create an account.  Now, you can install the GitHub Copilot plugin in PyCharm: Open PyCharm. Go to File > Settings. Navigate to Plugins and search for GitHub Copilot. Click Install to add the plugin. After installation, open the Tools menu, find GitHub Copilot and click Login to GitHub. A window will appear with an authorization link and a special code. Follow the link, enter the code, and confirm authorization. Now, GitHub Copilot is fully integrated into your PyCharm project. How to Use GitHub Copilot Let's write a simple function to verify that we have successfully installed the GitHub Copilot plugin. For example, start typing a function to add two numbers, like: def add(a, b): As you begin typing, Copilot will suggest completing the function: Suggested code appears in gray and italicized text. To accept a suggestion, press Tab. To reject a suggestion, press Esc. Useful GitHub Copilot Shortcuts Action Windows Mac Activate inline suggestions Alt+\ Option+\ View next suggestion Alt+] Option+] View previous suggestion Alt+[ Option+[ Accept suggestion Tab Tab Reject suggestion Esc Esc Open all suggestions in a new window Ctrl+Enter Ctrl+Enter Using Copilot with Comments GitHub Copilot doesn’t just rely on function names—it also generates code based on comments. For example, if you write a function for matrix multiplication with a descriptive comment: def multiply_matrices(A, B): # Multiply matrix A and B and return the result Copilot may suggest the following: def multiply_matrices(A, B): # Multiply matrix A and B and return the result rows1 = len(A) cols1 = len(A[0]) rows2 = len(B) cols2 = len(B[0]) if cols1 != rows2: raise ValueError("The number of columns in the first matrix must be equal to the number of rows in the second matrix") result = [[0 for j in range(cols2)] for i in range(rows1)] for i in range(rows1): for j in range(cols2): for k in range(cols1): result[i][j] += A[i][k] * B[k][j] return result To verify that this function works correctly, let’s use the NumPy library: import numpy as np matrix1 = [[15,24],[12,44]] matrix2 = [[112, 22],[55,90]] m1 = np.array([[15,24],[12,44]]) m2 = np.array([[112, 22],[55,90]]) print(multiply_matrices(matrix1, matrix2),'\n') print(np.dot(m1, m2)) Output: [[3000, 2490], [3764, 4224]] [[3000 2490] [3764 4224]] As you can see, the function Copilot correctly performs matrix multiplication. Cons of Using GitHub Copilot GitHub Copilot is a very useful tool, but it has some drawbacks. Copilot Doesn't Test Its Code The code suggested by Copilot may contain errors. It does not perform self-checks, meaning developers must test the generated code themselves. Additionally, Copilot doesn’t always produce optimized code, both in terms of efficiency and structure. In summary, all Copilot-generated code must be reviewed and tested. Conflicts with IDEs Modern Integrated Development Environments (IDEs) do more than just provide a space for writing and debugging code—they also offer built-in suggestions. For example, when using a built-in function in PyCharm, the IDE provides information about its attributes. At the same time, Copilot might suggest something different, which can be confusing for the developer. Potential Copyright Issues This is a controversial aspect of using Copilot in commercial development. Since Copilot was trained on public repositories, it could theoretically suggest licensed code. This raises concerns about intellectual property rights when using Copilot-generated code in proprietary projects. Negative Impact on Developer Skills Copilot doesn’t teach developers how to write code—it writes it for them. For junior developers, it’s important to gain hands-on experience by implementing common functions and algorithms manually. Over-reliance on Copilot might slow down skill development. Conclusion GitHub Copilot is a useful tool for handling repetitive coding tasks. According to GitHub’s own research: 74% of developers reported focusing on more enjoyable aspects of their work, 88% felt more productive, 96% completed repetitive tasks faster. Copilot should be seen as an assistant—someone you can delegate tasks to while focusing on more important and complex problems. However, developers must carefully review all code generated by Copilot to ensure quality and correctness. 
24 March 2025 · 6 min to read

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