sklls is a POC and not actively maintained
sklls is a simple CLI tool that aggregates git-blames by committer and generates line-counts for every committer based on file-extension and NPM dependencies.
The purpose of sklls is to automatically generate tech-usage profiles of contributors (which can serve as a proxy for tech sklls - get it?) working on any number of repositories.
Check out how we used sklls at Axel Springer to build an automatically generated team-directory that helps developers find each other based on tech-stack: https://medium.com/axel-springer-tech/do-your-git-blames-show-your-technical-skills-yes-and-no-2da5b88315e6
- Install
sklls(see below) - Run
$ sklls -out sklls-example-data
After installing sklls (see below) just run sklls -out sklls-example-data in any folder that contains git-repos.
sklls will run through all sub-folders and analyze any git-repos it can find (that have an origin set - aka which are hosted somewhere).
After sklls has run through successfully, you will find JSON files in /sklls-example-data similar to the following example output:
{
"Ext": {
"": {
"Thu, 29 Dec 2022 16:19:58 +0100": 38617,
"Wed, 21 Dec 2022 16:45:57 +0100": 21
},
".ds_store": {
"Thu, 29 Dec 2022 16:19:58 +0100": 2
},
".gitignore": {
"Thu, 29 Dec 2022 16:19:58 +0100": 1
},
".go": {
"Thu, 29 Dec 2022 16:19:58 +0100": 2929
},
".json": {
"Thu, 29 Dec 2022 16:19:58 +0100": 668310
},
".md": {
"Thu, 29 Dec 2022 16:19:58 +0100": 51
},
".mod": {
"Thu, 29 Dec 2022 16:19:58 +0100": 22
},
".sum": {
"Thu, 29 Dec 2022 16:19:58 +0100": 41
},
".txt": {
"Thu, 29 Dec 2022 16:19:58 +0100": 1
}
},
"Dep": {
"EcmaScript": {
"@jest/globals@^29.1.2": {
"Mon, 05 Sep 2022 12:12:24 +0200": 63,
"Sun, 06 Nov 2022 14:12:51 +0100": 520,
"Sun, 06 Nov 2022 15:51:31 +0100": 8
},
"@mui/icons-material@^5.10.9": {
"Sun, 06 Nov 2022 14:12:51 +0100": 728
},
"@mui/material@^5.10.12": {
"Sun, 06 Nov 2022 14:12:51 +0100": 843
},
"@octokit/graphql@^5.0.1": {
"Sun, 06 Nov 2022 14:12:51 +0100": 404
},
"@storybook/react@^6.5.12": {
"Mon, 19 Sep 2022 16:11:56 +0200": 92
},
"@storybook/testing-library@^0.0.13": {
"Mon, 19 Sep 2022 16:11:56 +0200": 26
},
"file-extension-icon-js@^1.1.6": {
"Sun, 06 Nov 2022 14:12:51 +0100": 728
},
"glob@^8.0.3": {
"Mon, 05 Sep 2022 12:12:24 +0200": 115,
"Sun, 06 Nov 2022 14:12:51 +0100": 51,
"Thu, 08 Sep 2022 13:18:28 +0200": 4
},
"http-proxy@^1.18.1": {
"Mon, 19 Sep 2022 16:11:56 +0200": 12
},
"react-dom@^18.2.0": {
"Mon, 19 Sep 2022 10:19:53 +0200": 13
},
"react-router-dom@^6.4.0": {
"Mon, 19 Sep 2022 10:19:53 +0200": 5,
"Mon, 19 Sep 2022 16:11:56 +0200": 13,
"Sun, 06 Nov 2022 14:12:51 +0100": 145
},
"react@^18.2.0": {
"Mon, 19 Sep 2022 10:19:53 +0200": 13,
"Mon, 19 Sep 2022 16:11:56 +0200": 269,
"Sun, 06 Nov 2022 14:12:51 +0100": 843
},
"swr@^1.3.0": {
"Mon, 19 Sep 2022 10:19:53 +0200": 5,
"Mon, 19 Sep 2022 16:11:56 +0200": 25,
"Sun, 06 Nov 2022 14:12:51 +0100": 30
}
}
},
"Usernames": [
"aGuyNamedJonas"
]
}$ sklls -help
Usage of sklls:
-cloneDir string
Directory to use for cloning repos into (default: Temp dir is being used
-concurrency int
Dictates how many files are analyzed in parallel (default 10)
-dir string
Directory where to look for repos for. Default is CWD.
-exclude string
Comma separated list of file suffixes to exclude from scanning (can be both extensions and filenames) (default "package-lock.json,yarn.lock")
-ghpat string
Github Personal Access Token for cloning non-public repos
-ghrepos string
Comma separated list of Github repos (org/repo - e.g. spring-media/ep-curato) to clone from Github & analyze (requires ghpat to be set as well, if repos are non-public)
-out string
Output folder (default "./")
-perfLogThreshold int
Performance data is logged for any file analysis that takes longer than perfLogThreshold (in ms) (default 500)
-timeout int
Timeout in seconds for analyzing repositieries (default: 30 [seconds]) (default 30)
-verbose
Enable verbose output
- Make sure go is installed
- Clone this repo
- Run
make installfrom the project root - After installation is complete, you can run
skllsfrom anywhere on your machine
MIT