
<EmbeddedYoutubeVideo id="r2CpLe1h89I" />

## Related links

- [Sourcegraph code search](https://sourcegraph.com/search)
- [Sourcegraph docs](https://docs.sourcegraph.com)
- [Read about literal search patterns](/how-to-search-code-with-sourcegraph-using-literal-patterns)
- [Watch: Three Ways to Search with Sourcegraph (Video)](/three-ways-to-search-code-with-sourcegraph)

## Transcript

Have you ever been faced with an error message and spent a really long time trying to figure out where it was coming from?

My name is Marek. I'm an engineer at Sourcegraph. And I'm going to share with you my own error message story.

A few months ago, I was working on a browser extension in Chrome. And I started seeing this unfamiliar message that I hadn't seen before. It looked something like this. "Extension context invalidated." What does that even mean? I didn't know where this error was being thrown. And I didn't know where to start looking. We were loading code from a few different repositories into this browser extension bundle. So I wasn't sure where this was coming from.

At first, I tried doing some searches right in my editor to try to find an exact match for the text of this error message. But I got nowhere. I didn't find any matches in the repository that I had open at all.

So I'll show you how I actually used Sourcegraph to do a code search that helped me find the answer. By default, Sourcegraph searches for code in literal search mode. That means it looks for an exact match. For an error message, this is pretty convenient. And I can show you by pasting that error message directly into the search box. Now, I don't need to surround this search with quotes, because literal search will by default already search for the entire thing.

As soon as I get results, there's a hint about where this is coming from. And that's in the name of this repository that I'm getting. So I'm seeing chromium as the repository. This gives me a hint that this is part of the Chrome browser itself and actually not at all a part of the code base that I was working on. The chromium source code is in a public GitHub repository, and Sourcegraph searches over public code. This helped me save a lot of time and a lot of struggle to get to the bottom of this error message. And it turns out it was an issue with the way that the browser extension was being reloaded for development.

Sourcegraph's default search mode is great for error messages like this, but if you're looking for patterns, you can also use regular expressions. And you can also use structural search. So you can take a look at our documentation to learn more about that.


Finding software error messages with Sourcegraph universal code search

Learn about finding error messages in your code with Sourcegraph.

How to find error messages with Sourcegraph (video)


<EmbeddedYoutubeVideo id="1qa3dyzJ3Go" />

## Learn more

- Install the [Sourcegraph browser extension](https://docs.sourcegraph.com/integration/browser_extension)
- Learn about the [“Git Extras” Sourcegraph extension](https://sourcegraph.com/extensions/sourcegraph/git-extras)
- Learn about [Sourcegraph extensions for your code editor](https://sourcegraph.com/extensions?category=Code+editors)
- Watch the video: [Open-in-editor Sourcegraph extension](https://youtu.be/Maa6jCaoZFw)

## Transcript

As a developer, I spend most of my time either in my code editor — for me, usually that's VS Code — or on GitHub, reviewing pull requests or browsing repositories. Whenever I switch between different tools, I don't like it when I lose my train of thought, and I don't like it when I lose the context of the files that I'm working on.

My name is Marek. I'm an engineer at Sourcegraph. Let me show you how I use Sourcegraph on a day-to-day basis in my own work in a way that helps me read and understand code better without losing context as I switch between tools.

My starting point is usually on GitHub. Often, I'm reviewing a pull request or just trying to understand how some piece of code works. By installing the Sourcegraph browser extension, I can have Sourcegraph features right in Github. Here, by hovering over a symbol in Github, I'm able to get Sourcegraph code intelligence right where I am.

Now, I can use the **Find references** button here to jump into Sourcegraph and start exploring the code. The bottom panel is the **References** panel, and it's listing all the places where this particular token is being used in this codebase. If I want to learn more about the context of this particular piece of code, I can use the **Git blame** action to show the history of the changes made to it and why they were made.

Often my workflow involves collaborating with other engineers. I can copy this link to this particular place in the code and share it with my colleagues on Slack. Because this is a public repository, Sourcegraph generates a preview image that helps me show what I'm linking to.

Typically after I've explored and learned about some code, my next step is to jump into my editor and make some changes. I can do that with the **Open in VS Code** action here. Now I've already configured Sourcegraph to point to my local repository. By clicking the button, I'm taken to my editor, and I'm able to start working right away.

Sometimes while I'm coding, I'm curious to learn more about a particular symbol that's in the code, like this `configurationResolver`. With the Sourcegraph VS Code extension, I can jump right into a Sourcegraph search and find out more.

I probably switch between my editor, GitHub and Sourcegraph multiple times a day. So I love having integrations that make that as smooth as possible. Now, let me show you how you can set up these integrations for your own workflow.

First, install the Sourcegraph browser extension. It's available for Chrome, Firefox, and Safari. Next, install the Sourcegraph extension for Visual Studio Code. And finally, to be able to jump from Sourcegraph right into your editor, go to the Sourcegraph extensions page and go to the **Code editors** section, you'll find our integrations for VS Code as well as several other editors. And you just have to add the local directory where you have your repositories cloned in the Sourcegraph settings for this to work.


Integrating Sourcegraph into code host and editor workflows

Learn how to switch between your code host (like GitHub), code editor or IDE (like VS Code), and Sourcegraph.

How to integrate Sourcegraph into your workflows with GitHub and VS Code extensions


<EmbeddedYoutubeVideo id="w-RrDz9hyGI" />

## Transcript

Sourcegraph code search lets you search over public repositories or your own private code. It helps you answer questions that start with _where_. For example, where is this function used across all of our repositories? Where are we using these dependencies? Or, where are all the matches for this particular regular expression search?

But, what if you could search over space and time? Sourcegraph commit search helps you answer questions that start with _when_. When was a particular keyword mentioned in a commit message? When did we add or remove a specific string across our repositories? When did a commit or a diff contain an exact function name? 

My name is Marek. I'm an engineer at Sourcegraph. And I want to show you how to search over commits and diffs with Sourcegraph.

Suppose I'm looking for some particular commits that made some changes to our database logic. In this case, I will look for commits that have the keyword `database` in the commit message. To do this, I'll use the `type` filter to specify that I'm looking for commits, and I'll use the `message` filter to specify the keyword that I want to find, in this case, the keyword `database`. I'll also add a repository filter to narrow down the results.

In the results, I see a list of commits being returned. I can browse the commit messages and also see how long ago they were committed. If I click on a commit, I can also see the entire diff associated with it, so I can browse through the changes.

Now, it can be useful to narrow down my search if, for example, I know that the commits that I'm looking for occurred in a particular time range. I can add a `before` filter and provide a date and combine it with an `after` filter to specify a range of time. Now in some cases, I might be looking for commits from a particular author on my team. I can use the `author` filter and provide a name to narrow it down further.

I've shown you an example of searching over commit messages. But I can also search over the actual diff contents of every commit as well. This is helpful if I'm really looking for an exact string that was either added or removed in a particular change. To perform a diff search, I'll start with the `type:diff` filter. Now I can specify any search query that is supported by Sourcegraph. In this case, I could use a regular expression to find all matches that start with `user_`. And like before, I'll use a repository filter to narrow down the results.

In the results, I see matches in the diffs of commits that were made in this repository across time. Now, I'm seeing matches both in lines added and lines removed. Now I can improve my search. If I'm only looking for instances where this particular match was added, not removed in a commit, I can do that by adding a `select` filter, and providing `commits.diff.added` as the value. Now, I'm only getting results where this particular match was in the added content of a commit.

Other types of filters that are supported by regular Sourcegraph code search are supported in commit search as well, such as the language filter, or the file filter to help you narrow down by file path. With commit and diff search. Sourcegraph helps you find everything that you're looking for in your code, answering not just _where_ it is, but _when_ it happened. To learn more about the different ways that you can search with Sourcegraph check out the links below.

## Learn more

Browse our [learning resources about Sourcegraph search](/tags/search).


Learn about using Sourcegraph to search commits and diffs.

How to search Git commits and diffs with Sourcegraph


<EmbeddedYoutubeVideo id="u_SmtOejFkg" />

## Transcript

Hi, I’m Lisa, Director of Developer Education at Sourcegraph, and I’m going to walk you through installing an instance of Sourcegraph on a Linux Ubuntu 20.04 cloud server. We’ll be using a [DigitalOcean Droplet](https://www.digitalocean.com/) with the recommended 4GB of RAM and 2 CPUs for this demo.

Sourcegraph is a tool that can allow you to search the code that is important to you. You can try out [Sourcegraph](https://sourcegraph.com) on the web to search through open source repositories right now. In this video, we’ll discuss an installation instead. If you would like to use Sourcegraph to access local code, server-side code, or code from several different code hosts, an instance like this may be the right fit for you. 

Installing Sourcegraph with Docker is appropriate for testing and fairly quick to set up. If you would like to use Sourcegraph in a production environment, you should follow our documentation on installing [Sourcegraph with Docker Compose](https://docs.sourcegraph.com/admin/install/docker-compose) on a single node, or on a [Kubernetes cluster](https://docs.sourcegraph.com/admin/install/kubernetes). Let’s get started.

### Server setup

I set up this DigitalOcean Droplet with a [non-root sudo user](https://www.digitalocean.com/community/tutorials/initial-server-setup-with-ubuntu-20-04), Sammy. First, I want to make sure that everything is up to date by running the following command. 

<PrismSyntaxHighlighter
input='sudo apt update'
language='bash'
/>

I’ll enter the password when prompted to use my sudo user. 

Now we know everything is up to date, and I can move ahead to installing Docker. I am going to use the snap package manager, so let’s make sure that’s installed. 

<PrismSyntaxHighlighter
input='sudo apt install snapd'
language='bash'
/>

With that installed and set up, I want to make sure I have the core libraries I need, so I’ll run sudo snap install core.

<PrismSyntaxHighlighter
input='sudo snap install core'
language='bash'
/>

Now that snap is installed, we’ll install Docker using snap.

<PrismSyntaxHighlighter
input='sudo snap install docker'
language='bash'
/>

Now that we have Docker installed, we can move on to installing Sourcegraph with Docker.

### Installing Sourcegraph

We have a multi-line Docker command that we need to run, and we’ll demonstrate how to do that here. We’ll be using the sudo command and it’s going to take a little bit. 

We’ll run the following Docker run command:

<PrismSyntaxHighlighter
input='sudo docker run -d --publish 80:7080 \
--publish 443:7443 \
--restart unless-stopped \
--volume /root/.sourcegraph/config:/etc/sourcegraph \
--volume /root/.sourcegraph/data:/var/opt/sourcegraph \
sourcegraph/server:3.30.4'
language='bash'
/>

This command is telling your server to install and run Sourcegraph, binding port 7080 to TCP port 80 of your server; it’s calling up the relevant files from the Docker image of Sourcegraph. Since this is a cloud server, we can keep our instance of Sourcegraph up and running even after closing our Terminal connection to the server, and that was one of the details we pass to this command. It is also setting up a store for your Sourcegraph data.

### Verify installation

With our installation complete, we can navigate to our web browser of choice and enter the IP address of the server with port 80. We’ll press enter and get the feedback that the installation is complete. We have validated that we have installed Sourcegraph with Docker on this Ubuntu server. At this point, you can create your account. 

Now we have verified that everything is working. For next steps, head on over to [Sourcegraph Learn](https://learn.sourcegraph.com). Or go ahead to read through our [documentation](https://docs.sourcegraph.com) to read more about Sourcegraph, the different installation methods, and how you can effectively search all of your code. Happy coding and happy searching!

_For a longer-form written tutorial of this guide, read “[How to install Sourcegraph on Linux with Docker](https://learn.sourcegraph.com/how-to-install-sourcegraph-on-linux-with-docker).”_


Test a Sourcegraph installation with Docker on DigitalOcean to search your code

Install Sourcegraph onto a DigitalOcean Ubuntu cloud server with Docker.

How to install Sourcegraph with Docker on a Linux cloud server (video)


<EmbeddedYoutubeVideo id="GnubTdnilbc" />

## Transcript

Structural search is one of the three ways that you can search code with Sourcegraph. 

My name is Marek. I'm an engineer at Sourcegraph, and in this video, I want to show you how you can use structural search in Sourcegraph. And I'll share examples of the kinds of things that you can do with it.

Structural search is a way to search code that takes into account the code’s syntactic structure. This means it goes beyond regular expressions, which are great for matching patterns of characters, and it lets you match patterns in the structure and the syntax of the code.

Let's jump into some examples. We can use a well-known codebase, the Linux kernel. It's mostly written in C, but you can use structural search with any programming language. You can search over any public repositories that are indexed by Sourcegraph. And you can also use Sourcegraph to search your own private code.

To enable structural search, click on the structural search toggle on the right side of the search box. It's represented by an icon of square brackets (`[]`). I'll begin to search with a `repo` filter to select the Linux kernel repository on GitHub that I want to use for these examples. I'll use the language filter to specify that I'm looking for files written in C. Because structural search takes into account the programming language in its matches, you'll get better results if you specify the language with the language filter.

Suppose I want to find all calls to a function with a particular first argument. Let's say I'm looking for the function `fprintf` and I want to find all cases where the first argument is the standard error stream, or `stderr`. Since I'm only interested in the first argument, I can use a placeholder for the remaining arguments. Placeholders in structural search are called holes in the pattern. The ellipses is a type of hole that matches any number of arguments. In the results, I get matches for the pattern of the function call I was looking for, followed by any various other arguments in the function call.

Now, suppose I want to do another search for instances of the `fprintf` function. But this time, I'm interested in matching a string argument. Structural search supports using placeholders or holes in the pattern inside of quoted strings. Here's a search where I use the ellipses hole to match any initial arguments, followed by a string that starts with `ERROR` and an ellipses within the string to match anything in the string after that, and finally, followed by another ellipses to match any remaining arguments. The results show instances of these function calls, where there is a string argument that matches this pattern.

Now, let me show you how to take this example further and demonstrate that structural search understands nested structures, too. Suppose I want to narrow my search to find instances where the last argument is a specific expression. Let's say it's a call to a function named `strerror`. I can use the ellipses hole in the brackets to find all calls that match this regardless of what the arguments actually are.

I can also flip this pattern around. Suppose that I know the name of the arguments that I want to find in this function call, but I want to match any function name. I can use the ellipses hole instead of the function name, but then specify the exact argument name that I'm looking for. For example, `errno`. Now I'll get results where this specific argument name matches, but the name of the function being called here can match anything.

Now I want to show you an example of a more advanced format for the holes in a pattern. In a structural search, the ellipses placeholder matches all patterns. But sometimes we want to narrow that down further, for example, to find identifiers that conform to a particular regular expression. I'll update this pattern with a hole in the final argument that will narrow down the matches by regular expression. This is part of the structural search syntax that lets you be more detailed in the matches that you're looking for. The colon and the square brackets indicate that this is a structural search hole pattern. The tilde (`~`) indicates the start of a regular expression. And then we have a regular expression that matches any identifier that starts with `opt_`. And in the results now we're getting matches where this final argument conforms to the regular expression in this pattern that we've provided.

I hope this gives you an idea of the kinds of things that you can do with Sourcegraph. Structural search is one of the three search modes supported by Sourcegraph, the others being literal search and regular expression search. To learn more about how you can use Sourcegraph to better search and better understand your code. Check out our documentation and our learning resources add the links below.

## Learn more

- Watch: [Three ways to search with Sourcegraph](/three-ways-to-search-code-with-sourcegraph)
- Read: [How to search code with Sourcegraph — a cheat sheet](/how-to-search-code-with-sourcegraph-a-cheat-sheet)
- Browse all [Sourcegraph search tutorials](/tags/search)
- [Sourcegraph search documentation](https://docs.sourcegraph.com/search)


Learn about Sourcegraph structural search patterns.