ancv 0.16.0

Render 'JSON Resume' sources to ANSI-enriched output for terminal clients (cURL, wget, ...) to consume.

ancv

Getting you an CV (ANSI-v 🤡) straight to your and anyone else's terminals.

Be warned though, for this is kinda useless and just for fun:

Getting started

1. Create a resume according to the JSON Resume Schema (see also the schema specification) either:

   • manually (see this sample for a possible starting point),
   • exporting from LinkedIn using Joshua Tzucker's LinkedIn exporter (repo), or
   • exporting from one of the platforms advertised as offering JSON resume integration.

2. Create a public gist named resume.json with those resume contents. See here for a working example from the author.

3. Try it out, using...

   • curl:

     curl -L ancv.io/username
     

     with -L being shorthand for --location, allowing you to follow the redirect from http://ancv.io through to https://ancv.io. It's shorter than its also perfectly viable alternative:

     curl https://ancv.io/username
     

     Lastly, you might want to page the output for easiest reading, top-to-bottom:

     curl -sL ancv.io/username | less
     

   • wget:

     wget -O - --quiet ancv.io/username
     

     where -O is short for --output-document, used here to redirect to stdout.

   • PowerShell (5 and 7):

     (iwr ancv.io/username).Content
     

     where iwr is an alias for Invoke-Webrequest, returning an object.

   For a quick, working example replace username with alexpovel.

Configuration

All configuration is optional.

The CV is constructed as follows:

These components may be controlled using the ancv field in your resume.json:

{
   "basics": {},
   "education": [],
   "meta": {
     "ancv": {
        "template": "Sequential",
        "theme": "basic",
        "ascii_only": false,
        "language": "en"
     }
   }
}

The shown values are the default ones. All fields, including the ancv one itself, are optional, and the above defaults will be set for omitted fields. This means a valid JSON resume (without an ancv section) is also valid here. The currently available options can be printed out:

$ pip install ancv >> /dev/null && ancv list
Components
├── Templates
│   └── Sequential
├── Themes
│   ├── plain
│   └── basic
└── Translations
    ├── en
    └── de

Installation as a library

For local use, install the package as usual. Note that it's pretty heavy on the dependencies.

pip install ancv

Self-hosting

Self-hosting is a first-class citizen here.

Context: Cloud Hosting

The https://ancv.io site is hosted on Google Cloud Run (serverless) and deployed there automatically, such that the latest release you see here is also the code executing in that cloud environment. That's convenient to get started: simply create a resume.json gist and you're good to go within minutes. It can also be used for debugging and playing around; it's a playground of sorts.

You're invited to use this service for as much and as long as you'd like. However, obviously, as an individual I cannot guarantee its availability in perpetuity. You might also feel uncomfortable uploading your CV onto GitHub, since it has to be public for this whole exercise to work. Lastly, you might also be suspicious of me inserting funny business into your CV before serving it out. If this is you, self-hosting is for you.

Setup

For simplicity, using Docker Compose (with Docker's recent Compose CLI plugin):

1. Clone this repository onto your server (or fork it, make your edits and clone that)
2. cd self-hosting
3. Edit Caddy's config file (more info) to contain your own domain name
4. Place your resume.json into the directory
5. Run docker compose up

Caddy (chosen here for simplicity) will handle HTTPS automatically for you, but will of course require domain names to be set up correctly to answer ACME challenges. Handling DNS is up to you; for dynamic DNS, I can recommend qmcgaw/ddns-updater.

If you self-host in the cloud, the server infrastructure might be taken care of for you by your provider already (as is the case for Google Cloud Run). In these cases, a dedicated proxy is unnecessary and a single Dockerfile might suffice (adjusted to your needs). True serverless is also a possibility and an excellent fit here. For example, one could use Digital Ocean's Functions. If you go that route and succeed, please let me know! (I had given up with how depressingly hard dependency management was, as opposed to tried-and-tested container images.)

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