Apify ci integration
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Configure CI/CD pipelines for Apify Actor builds and deployments. Use when automating Actor deployment via GitHub Actions, running integration tests against the live Apify API, or building CI/CD for scrapers that push to the Apify platform. Trigger with "apify CI", "apify GitHub Actions", "apify automated deploy", "CI apify", "apify pipeline", "auto deploy actor".
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SKILL.md
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Apify CI Integration
Overview
Automate Apify Actor builds, tests, and deployments using GitHub Actions — test-on-PR, deploy-on-merge, live-API integration testing, and Docker build verification. Three workflow files do the work (test, deploy, verify-build); full copy-paste-ready definitions live in references/workflows.md.
Prerequisites
- GitHub repository with Actions enabled
- Apify API token stored as a GitHub secret
- Actor code in the repository
Authentication
CI authenticates to Apify with a personal API token, never a hard-coded credential:
- Store the token as a GitHub Actions secret (
gh secret set APIFY_TOKEN), and expose it to a job only viaenv: APIFY_TOKEN: ${{ secrets.APIFY_TOKEN }}. - The Apify CLI reads it as
apify login --token $APIFY_TOKEN; the REST API andapify-clientread it from theAPIFY_TOKENenvironment variable. - Use separate
APIFY_TOKEN_TEST/APIFY_TOKEN_PRODsecrets so integration runs never touch production data. Get tokens from Apify Console → Settings → Integrations.
Instructions
Step 1: Configure GitHub Secrets
# Store Apify token for CI
gh secret set APIFY_TOKEN --body "apify_api_YOUR_CI_TOKEN"
# Optional: separate tokens for test vs production
gh secret set APIFY_TOKEN_TEST --body "apify_api_test_token"
gh secret set APIFY_TOKEN_PROD --body "apify_api_prod_token"
Step 2: Create the test workflow
Add .github/workflows/apify-test.yml with two jobs — unit-tests on every PR
and integration-tests gated to push (merge) events. The integration job
proves connectivity before running tests:
- name: Verify Apify connection
run: |
curl -sf -H "Authorization: Bearer $APIFY_TOKEN" \
https://api.apify.com/v2/users/me | jq '.data.username'
Full two-job workflow: references/workflows.md (Test Workflow).
Step 3: Create the deploy workflow
Add .github/workflows/apify-deploy.yml — triggered on merges that touch
src/**, package.json, or .actor/** (plus workflow_dispatch). It builds,
tests, installs the Apify CLI, apify pushes, then runs a minimal smoke call to
confirm the new build actually starts. Full definition:
references/workflows.md (Deploy Workflow).
Step 4: Write integration tests
Gate live-API tests on the token so they skip cleanly when it is absent:
const SKIP_INTEGRATION = !process.env.APIFY_TOKEN;
describe.skipIf(SKIP_INTEGRATION)('Apify Integration', () => {
it('should authenticate successfully', async () => {
const user = await client.user().get();
expect(user.username).toBeTruthy();
});
});
The complete suite (auth, live Actor run, create/delete a named dataset with cleanup) is in references/integration-tests.md.
Step 5: Verify the Actor build
Add a verify-build.yml that docker builds the Actor image and boots it once
to confirm the entry point loads. Optionally add branch-protection rules that
require the CI contexts before merge. Both blocks:
references/workflows.md (Actor Build Verification).
Output
Applying this skill produces committed CI/CD infrastructure in the repository:
.github/workflows/apify-test.yml— unit tests on every PR, integration tests on merge tomain..github/workflows/apify-deploy.yml—apify push+ post-deploy smoke test on merge, plus manualworkflow_dispatch..github/workflows/verify-build.yml— Docker build + entry-point check on PRs.tests/integration/apify.test.ts— token-gated live-API integration suite.- Configured GitHub secrets (
APIFY_TOKEN, optional_TEST/_PRODvariants) and, optionally, branch-protection requiring the CI checks to pass.
Once merged, every PR runs unit tests, every merge deploys and smoke-tests the
Actor, and a failed deploy surfaces a ::error:: annotation in the run log.
Error Handling
| Issue | Cause | Solution |
|---|---|---|
APIFY_TOKEN not set | Secret not configured | gh secret set APIFY_TOKEN |
| Integration test timeout | Slow Actor run | Increase timeout, use smaller input |
| Docker build fails in CI | Local-only deps | Commit package-lock.json |
apify push fails | Not logged in | Add apify login --token step |
| Flaky integration tests | External service issues | Add retries, use test.retry(2) |
Examples
Minimal test-on-PR gate — the smallest useful setup is Step 1 (store the
secret) plus the unit-tests job from the test workflow. Every PR then runs
npm ci && npm run build && npm test before it can merge.
Full deploy pipeline — add the deploy workflow so a merge to main that
touches src/** builds, tests, runs apify push, then smoke-tests the new
build:
- name: Push Actor to Apify
run: apify push
- name: Verify deployment
run: |
ACTOR_ID=$(jq -r '.name' .actor/actor.json)
apify actors call $ACTOR_ID \
--input='{"startUrls":[{"url":"https://example.com"}],"maxItems":1}' \
--timeout=120
apify-client app (not Actor dev) — for an app that calls Actors rather than
publishing one, mock apify-client in unit tests and gate a real-token
integration job to main. Full workflow:
references/workflows.md (CI Configuration for apify-client Apps).
See references/workflows.md for every full workflow and references/integration-tests.md for the complete integration suite.
Resources
Next Steps
For runtime deployment patterns beyond CI wiring — release channels, versioned
Actor builds, and rollback — see the apify-deploy-integration skill in this
pack.