This is a blog software completely written in C# / Blazor. The aim is to have it configurable as possible.

The basic idea is that the content creator writes his posts in markdown language (like this readme file). The markdown will then by translated to HTML and displayed to the client. This gives an easy entry to writing posts with all the flexibility markdown has. This also includes source code snippets. Right now only C# is highlighted properly but other languages can be extended easily as the highlighting is done via highlight.js.

Just clone this repository and you are good to go. There are some settings you can tweak. The following chapter will guide you through the possibilities.

The appsettings.json file has a lot of options to customize the content of the blog. The following table shows which values are used when.

{
  "BlogName": "linkdotnet",
  "GithubAccountUrl": "",
  "LinkedInAccountUrl": "",
  "Introduction": {
    "Description": "Some nice text about yourself. Markup can be used [Github](https://github.com/someuser/somerepo)",
    "BackgroundUrl": "assets/profile-background.webp",
    "ProfilePictureUrl": "assets/profile-picture.webp"
  },
  "PersistenceProvider": "SqlServer",
  "ConnectionString": "",
  "DatabaseName": "",
  "Auth0": {
    "Domain": "",
    "ClientId": "",
    "ClientSecret": ""
  },
  "BlogPostsPerPage": 10,
  "AboutMeProfileInformation": {
    "Name": "Steven Giesel",
    "Heading": "Software Engineer",
    "ProfilePictureUrl": "assets/profile-picture.webp"
  },
  "Giscus": {
    "Repository": "github/repo",
    "RepositoryId": "id",
    "Category": "general",
    "CategoryId": "id"
  }
}

Currently there are 4 Storage-Provider:

• InMemory - Basically a list holding your data (per request). If the User hits a hard reload, the data is gone.
• RavenDb - As the name suggests for RavenDb
• Sqlite - Based on EF Core, so it can be easily adapted for other Sql Dialects
• SqlServer - Based on EF Core, so it can be easily adapted for other Sql Dialects

For comments the blog is using giscus. To provide the necessary values head over to https://giscus.app/ and go to the configuration section. There you can enter all the information. You will find a detailed guide on the site.

In short:

• You need a public repository where the comments are hosted. Recommendation: Create a new repository just for the comments
• You have to link the giscuss app to at least the repository where the comments are hosted
• You have to enable the discussion feature in the repository (see (here)[https://docs.github.com/en/github/administering-a-repository/managing-repository-settings/enabling-or-disabling-github-discussions-for-a-repository] )

After you configured everything on the site, you get the <script> tag which you could embed. The blog needs the following information.

Here you can find an example. This is how the script tag looks on giscus.

<script src="https://giscus.app/client.js"
       data-repo="your_username/reponame"
       data-repo-id="M9/ab=="
       data-category="General"
       data-category-id="AbC==/8_D"
       async>
</script>

Now you can copy/paste those information into the appsettings.json. With the given information abobe your appsettings.json looks like this:

  "Giscus": {
    "Repository": "your_username/reponame",
    "RepositoryId": "M9/ab==",
    "Category": "General",
    "CategoryId": "AbC==/8_D"
  }

There is only one real mechanism enabled via Auth0. For more information go to: https://auth0.com/docs/applications

The main advantage of Auth0 is the easy configurable dashboard on their website.

For testing purposes you can use services.UseDummyAuthentication();. This allows every user, who presses Login, to be logged in.

The blog includes some of the most important tags to get indexed by a crawler. Furthermore some aspects of the Open Graph specification are implemented.

In the wwwroot/ you can find a default robots.txt. It allows that the site gets completely indexed. If you want to tweak that behavior feel free. Also you can provide a sitemap.xml to get a better ranking.

To get better results when for example shared via LinkedIn some of the <meta property="og:tag"> tags are implemented.

The following tags are set depending on the page:

Furthermore the following tags are set: