Claude
017e3a61a8
Address issue #20 and the CI divergence between Gitea and GitHub. Issue #20 (staging seeded from a prod snapshot): - Read SECRET_KEY from the environment with the insecure dev key as fallback, so each deployment can have its own key. - Add a `scrub_staging` management command that clears django_session and the django-q schedule/queue/results, removing copied prod sessions and the inherited convert_prices() schedule. - Run the scrub from entrypoint.sh when STAGING=true, and wire STAGING plus a per-branch SECRET_KEY into the Gitea staging deploy. CI parity (both systems kept, independent): - Add the Node/pnpm/TypeScript build steps to the Gitea build workflow to match the GitHub test job. - Add a GitHub staging workflow that deploys per-branch ephemeral instances to Fly.io (*.fly.dev) with a fresh database seeded from sample fixtures and its own SECRET_KEY, never production data. Tears the app down on branch delete and comments the URL on the open PR via github-script. - Add fly.staging.toml and a LOAD_SAMPLE_DATA entrypoint hook for the fresh-database public staging. https://claude.ai/code/session_01KYjUcNjLfZ8Hq1GAC8J4oZ
30 lines
801 B
TOML
30 lines
801 B
TOML
# Shared Fly.io configuration for ephemeral, per-branch GitHub staging deploys.
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#
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# The app name is NOT set here on purpose; each branch supplies its own via
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# `flyctl deploy --app timetracker-staging-<slug>`. These instances run with a
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# fresh database seeded from sample fixtures (never production data) and their
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# own SECRET_KEY, so they are safe to expose on a public *.fly.dev hostname.
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primary_region = "ams"
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[build]
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dockerfile = "Dockerfile"
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[env]
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PROD = "1"
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TZ = "Europe/Prague"
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DATA_DIR = "/home/timetracker/app/data"
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LOAD_SAMPLE_DATA = "true"
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CREATE_DEFAULT_SUPERUSER = "true"
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[http_service]
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internal_port = 8000
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force_https = true
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auto_stop_machines = "stop"
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auto_start_machines = true
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min_machines_running = 0
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[[vm]]
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size = "shared-cpu-1x"
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memory = "512mb"
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