Skip to main content

How to download single file from github?

Problem:

Often, you will need a single file to download from github, but you can't figure out how to do that. In such a case, a lot of people will suggest that you will need to download the whole repository. But that's not a useful suggestion and you know it. So what to do?

Solution:

In such a case, first click the view raw option in github ui. This will redirect into a new tab generally and show the rawgithubusercontent.com/... site and the raw content in that tab. Avoid this. Get this raw content in the same tab. This will create a similar rawgithubusercontent.com/... url. 

Now, using this url, use curl <url> to fetch this content. This will download the raw content in your computer. 

Installation (if needed):

For linux and mac, you will have this curl installed by default. For windows, you need to install it if your version is not later than windows 10. To try out the installation see Testing your cURL installation below. [the following part is taken from zendesk website]

You can download and install cURL as follows.
  1. In Windows, create a new folder called curl in your C: drive.

    C:\curl

  2. Go to http://curl.haxx.se/download.html and download one of the following zip files:

    • If you have a Windows 64 system, scroll to the Win64 - Generic section and look for the latest Win64 ia64 zip version with SSL support. It's normally second in the list. Click the version number to start the download.
    • If you have a Windows 32 system, scroll to the Win32 - Generic section and look for the latest Win32 zip version with SSL support. It's normally second in the list. Click the version number to start the download.
  3. Unzip the downloaded file and move the curl.exe file to your C:\curl folder.

  4. Go to http://curl.haxx.se/docs/caextract.html and download the digital certificate file named cacert.pem.

    The PEM file contains a bundle of valid digital certificates. The certificates are used to verify the authenticity of secure websites. They're distributed by certificate authority (CA) companies such as GlobalSign and VeriSign. The PEM file allows cURL to connect securely to the Zendesk API using the Secure Sockets Layer (SSL) protocol.

  5. Move the cacert.pem file to your C:\curl folder and rename it curl-ca-bundle.crt.

  6. Add the curl folder path to your Windows PATH environment variable so that the curl command is available from any location at the command prompt. Update the variable as follows:

    1. In the Start menu, right-click This PC and select More > Properties.

      Note: In Windows 7, right-click Computer and select Properties.

    2. Click Advanced System Settings.

    3. In the Advanced tab, click the Environment Variables button on the lower right side.

    4. Select the "Path" variable in System Variables, and click Edit.

    5. In the Edit environment variable dialog box, click New and add the path to the curl.exe file. Example: C:\curl.

      curl installation in windows 7: what is curl, using file directory arranging files for curl 

      Windows 7: In the Variable Value textbox, append a semicolon to the value, followed by the path to the curl.exe file. Example: ;C:\curl

    6. Keep clicking OK to accept the change and close the dialog box.

Now that you have curl in your windows computer also, you can curl the url in above mentioned procedure.

Conclusion:

So in this article, not only we resolved the hiccup of downloading single file from github, but we also saw how to use curl and how to download curl if you don't have it in your machine. Hope it helped you.

Comments

Popular posts from this blog

Tinder bio generation with OpenAI GPT-3 API

Introduction: Recently I got access to OpenAI API beta. After a few simple experiments, I set on creating a simple test project. In this project, I will try to create good tinder bio for a specific person.  The abc of openai API playground: In the OpenAI API playground, you get a prompt, and then you can write instructions or specific text to trigger a response from the gpt-3 models. There are also a number of preset templates which loads a specific kind of prompt and let's you generate pre-prepared results. What are the models available? There are 4 models which are stable. These are: (1) curie (2) babbage (3) ada (4) da-vinci da-vinci is the strongest of them all and can perform all downstream tasks which other models can do. There are 2 other new models which openai introduced this year (2021) named da-vinci-instruct-beta and curie-instruct-beta. These instruction models are specifically built for taking in instructions. As OpenAI blog explains and also you will see in our

Can we write codes automatically with GPT-3?

 Introduction: OpenAI created and released the first versions of GPT-3 back in 2021 beginning. We wrote a few text generation articles that time and tested how to create tinder bio using GPT-3 . If you are interested to know more on what is GPT-3 or what is openai, how the server look, then read the tinder bio article. In this article, we will explore Code generation with OpenAI models.  It has been noted already in multiple blogs and exploration work, that GPT-3 can even solve leetcode problems. We will try to explore how good the OpenAI model can "code" and whether prompt tuning will improve or change those performances. Basic coding: We will try to see a few data structure coding performance by GPT-3. (a) Merge sort with python:  First with 200 words limit, it couldn't complete the Write sample code for merge sort in python.   def merge(arr, l, m, r):     n1 = m - l + 1     n2 = r- m       # create temp arrays     L = [0] * (n1)     R = [0] * (n

What is Bort?

 Introduction: Bort, is the new and more optimized version of BERT; which came out this october from amazon science. I came to know about it today while parsing amazon science's news on facebook about bort. So Bort is the newest addition to the long list of great LM models with extra-ordinary achievements.  Why is Bort important? Bort, is a model of 5.5% effective and 16% total size of the original BERT model; and is 20x faster than BERT, while being able to surpass the BERT model in 20 out of 23 tasks; to quote the abstract of the paper,  ' it obtains performance improvements of between 0 . 3% and 31%, absolute, with respect to BERT-large, on multiple public natural language understanding (NLU) benchmarks. ' So what made this achievement possible? The main idea behind creation of Bort is to go beyond the shallow depth of weight pruning, connection deletion or merely factoring the NN into different matrix factorizations and thus distilling it. While methods like knowle