wehub-resource-sync
75 lines
2.2 KiB
TypeScript
75 lines
2.2 KiB
TypeScript
import { spawn } from 'child_process';
|
|
import { tmpdir } from 'os';
|
|
import { mkdtempSync } from 'fs';
|
|
import { join } from 'path';
|
|
import { TEST_PORT, TEST_TRACKING_URI } from './core/tests/helper';
|
|
|
|
/**
|
|
* Start MLflow Python server. This is necessary for testing Typescript SDK because
|
|
* the SDK does not have a server implementation and talks to the Python server instead.
|
|
*/
|
|
module.exports = async () => {
|
|
const tempDir = mkdtempSync(join(tmpdir(), 'mlflow-test-'));
|
|
|
|
const mlflowRoot = join(__dirname, '../..'); // Use the local dev version
|
|
|
|
// Only start a server if one is not already running
|
|
try {
|
|
const response = await fetch(TEST_TRACKING_URI);
|
|
if (response.ok) {
|
|
return;
|
|
}
|
|
} catch (error) {
|
|
// Ignore error
|
|
}
|
|
|
|
// eslint-disable-next-line no-console
|
|
console.log(`Starting MLflow server on port ${TEST_PORT}. This may take a few seconds...
|
|
To speed up the test, you can manually start the server and keep it running during local development.`);
|
|
|
|
const mlflowProcess = spawn(
|
|
'uv',
|
|
['run', '--directory', mlflowRoot, 'mlflow', 'server', '--port', TEST_PORT.toString()],
|
|
{
|
|
cwd: tempDir,
|
|
stdio: 'inherit',
|
|
// Create a new process group so we can kill the entire group
|
|
detached: true,
|
|
env: {
|
|
...process.env,
|
|
// Disable job execution to avoid timing issues in tests
|
|
MLFLOW_SERVER_ENABLE_JOB_EXECUTION: 'false',
|
|
},
|
|
},
|
|
);
|
|
|
|
try {
|
|
await waitForServer(TEST_PORT);
|
|
// eslint-disable-next-line no-console
|
|
console.log(`MLflow server is ready on port ${TEST_PORT}`);
|
|
} catch (error) {
|
|
console.error('Failed to start MLflow server:', error);
|
|
throw error;
|
|
}
|
|
|
|
// Set global variables for cleanup in jest.global-teardown.ts
|
|
const globals = globalThis as any;
|
|
globals.mlflowProcess = mlflowProcess;
|
|
globals.tempDir = tempDir;
|
|
};
|
|
|
|
async function waitForServer(maxAttempts: number = 30): Promise<void> {
|
|
for (let i = 0; i < maxAttempts; i++) {
|
|
try {
|
|
const response = await fetch(TEST_TRACKING_URI);
|
|
if (response.ok) {
|
|
return;
|
|
}
|
|
} catch (error) {
|
|
// Ignore error
|
|
}
|
|
await new Promise((resolve) => setTimeout(resolve, 1000));
|
|
}
|
|
throw new Error('Failed to start MLflow server');
|
|
}
|