Michael Bromley 3af21d5486 chore: Update github org name in links 1 hete
..
example-plugins 8a4ab91de1 Merge branch 'master' into minor 1 éve
graphql 3c4716036d feat(dashboard): Implement dragging to reorder collections (#4035) 1 hónapja
load-testing 3af21d5486 chore: Update github org name in links 1 hete
scripts 3af21d5486 chore: Update github org name in links 1 hete
test-plugins 3af21d5486 chore: Update github org name in links 1 hete
.gitignore e37802c1e8 chore(dev-server): Ignore generated gql file 3 hónapja
README.md 54f6c7c4c4 chore: Rename development scripts from "start" to "dev" 1 éve
dev-config.ts e62fce2756 fix(admin-ui-plugin): Deprecate `compatibilityMode` option (#3953) 2 hónapja
index-worker.ts 0441a0338a chore: Migrate from TSLint to ESLint 2 éve
index.ts 341003bd17 chore(dev-server): Add runMigrations to bootstrap 11 hónapja
instrumentation.ts 0f7ae934f8 feat(telemetry-plugin): Refine and document telemetry-plugin APIs 8 hónapja
lingui.config.js 112cb9d9e8 feat(dashboard): Support localization for dashboard extensions (#3962) 2 hónapja
memory-profiler.ts 0441a0338a chore: Migrate from TSLint to ESLint 2 éve
migration.ts a203037e1d feat(dashboard): Experimental packaging setup 10 hónapja
package.json e235d857c5 chore: Publish v3.5.2 4 hete
populate-dev-server.ts 0441a0338a chore: Migrate from TSLint to ESLint 2 éve
tsconfig.json e445bdb85d feat(dashboard): Support compilation of external plugins (#3663) 6 hónapja
vite.config.mts b599fca10f refactor(dashboard): Restructure UiConfigPluginOptions to remove AdminUiConfig dependency (#3718) 5 hónapja

README.md

Vendure Dev Server

This package is not published to npm. It is used in development of the Vendure server and plugins.

Running

Ensure you have a database running. From the root directory, run:

docker-compose up -d mariadb

To run the server, run the dev script. The database configuration can be specified by the DB=<type> environment variable:

cd packages/dev-server

[DB=mysql|postgres|sqlite] npm run dev

The default if no db is specified is mysql.

Populating data

Test data can be populated by running the populate script. This uses the same sample data as is used by the Vendure CLI when running init, albeit with the additional step of populating some sample customer & address data too.

Specify the database as above to populate that database:

[DB=mysql|postgres|sqlite] npm run populate

Testing custom ui extension compilation

In order to compile ui extensions within this monorepo, you need to add the following entry to the temporary admin ui tsconfig.json file:

  "paths": {
      "@vendure/admin-ui/*": ["../../admin-ui/package/*"]
  }

Load testing

This package also contains scripts for load testing the Vendure server. The load testing infrastructure and scripts are located in the ./load-testing directory.

Load testing is done with k6, and to run them you will need k6 installed and (in Windows) available in your PATH environment variable so that it can be run with the command k6.

The load tests assume the existence of the following tables in the database:

  • vendure-load-testing-1000
  • vendure-load-testing-10000
  • vendure-load-testing-100000

The npm scripts load-test:1k, load-test:10k and load-test:100k will populate their respective databases with test data and then run the k6 scripts against them.

Running individual scripts

An individual test script may be by specifying the script name as an argument:

npm run load-test:1k deep-query.js

pg_stat_statements

The following queries can be used when running load tests against postgres to analyze the queries:

SELECT 
  dbid,
  (total_time / 1000 / 60) as total, 
  (total_time/calls) as avg, 
  calls,
  query 
FROM pg_stat_statements 
WHERE dbid = <db_id>
ORDER BY total DESC 
LIMIT 100;

-- SELECT pg_stat_statements_reset();

Results

The results of the test are saved to the ./load-testing/results directory. Each test run creates two files:

  • load-test-<date>-<product-count>.json Contains a summary of all load tests run
  • load-test-<date>-<product-count>-<script-name>.csv Contains time-series data which can be used to create charts

Historical benchmark results with charts can be found in this Google Sheet