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README.md

Experimental TUID Project

TUID is an acronym for "temporally unique identifiers". These are numbers that effectively track "blame" throughout the source code.

Branch Status
master Build Status
dev Build Status

Overview

This is an attempt to provide a high speed cache for TUIDs. It is intended for use by CodeCoverage; mapping codecoverage by tuid rather than (revsion, file, line) triples.

More details can be gleaned from the motivational document.

Running tests

Running any tests requires access to an Elastic Search cluster for mo_hg on localhost:9201. This requires Elastic Search version 6.2.4. To look at the Elastic Search cluster, you can use Elasticsearch-head, found here.

After cloning the repo into ~/TUID:

Linux

cd ~/TUID
pip install -r ./tests/requirements.txt
pre-commit install
export PYTHONPATH=.:vendor
python -m pytest -m first_run --capture=no ./tests
python -m pytest -m 'not first_run' --capture=no ./tests

Windows

cd %userprofile%\TUID
pip install -r .\tests\requirements.txt
pre-commit install
set PYTHONPATH=.;vendor
python -m pytest -m first_run --capture=no tests
python -m pytest -m 'not first_run' --capture=no tests

Just one test

Some tests take long, and you want to run just one of them. Here is an example:

For Linux

python -m pytest tests/test_basic.py::test_one_http_call_required

For windows

python -m pytest tests\test_basic.py::test_one_http_call_required

If there are issues that arise concerning a private.json file, you may be required to set the following environment variable: TUID_CONFIG=tests/travis/config.json

Running the web application for development

You can run the web service locally with

cd ~/TUID
export PYTHONPATH=.:vendor
python tuid\app.py

The config.json file has a flask property which is sent to the Flask service constructor. Notice the service is set to listen on port 5000.

"flask": {
    "host": "0.0.0.0",
    "port": 5000,
    "debug": false,
    "threaded": true,
    "processes": 1,
}

The web service was designed to be part of a larger service. You can assign a route that points to the tuid_endpoint() method, and avoid the Flask server construction.

Deploying the web service

First, the server needs to be setup, which can be done by running the server setup script resources/scripts/setup_server.sh, and then the app can be setup using resources/scripts/prod_app.sh. If an error is encountered when running sudo supervisorctl, try restarting it by running the few commands in the server setup script.

Using the web service

The app.py sets up a Flask application with an endpoint at /tuid. This endpoint models a database: It has one table called files and it can accept queries on that table. The number of queries supported is extremely limited:

{
    "from":"files"
    "where": {"and": [
        {"eq": {"branch": "<BRANCH>"}},
        {"eq": {"revision": "<REVISION>"}},
        {"in": {"path": ["<PATH1>", "<PATH2>", "...", "<PATHN>"]}}
    ]}
}

Here is an example curl:

curl -XGET http://localhost:5000/tuid -d "{\"from\":\"files\", \"where\":{\"and\":[{\"eq\":{\"branch\":\"mozilla-central\"}}, {\"eq\":{\"revision\":\"9cb650de48f9\"}}, {\"eq\":{\"path\":\"modules/libpref/init/all.js\"}}]}}"

After some time (70sec as of March 23, 2018) we get a response (formatted and clipped for clarity):

{
    "format":"table",
    "header":["path","tuids"],
    "data":[[
        "modules/libpref/init/all.js",
        [
            242488,
            245829,
            ...<snip>...
            243144
        ]
    ]]
}

Using the client

This repo includes a client (in ~/TUID/tuid/client.py) that will send the necessary query to the service and cache the results in a local Sqlite database. This TuidClient was made for the ActiveData-ETL pipeline, so it has methods specifically suited for that project; but one method, called get_tuid(), you may find useful.

Examples using this service

  1. Web-extension for Phabricator. See the README in that repo for installation instructions.

TUID Service Improvements as part of GSoC 2019

Porting to Elasticsearch from SQLite and caching to make the service faster. Details can be found here.