mirror of
https://github.com/BillyOutlast/posthog.git
synced 2026-02-04 03:01:23 +01:00
feat(infra): add dual-mode support for Granian and Unit servers (#40847)
This commit is contained in:
Julian Bez
@@ -329,8 +329,7 @@ COPY --from=frontend-build --chown=posthog:posthog /code/frontend/dist /code/fro
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# Copy the GeoLite2-City database from the fetch-geoip-db stage.
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COPY --from=fetch-geoip-db --chown=posthog:posthog /code/share/GeoLite2-City.mmdb /code/share/GeoLite2-City.mmdb
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# Add in the Gunicorn config, custom bin files and Django deps.
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COPY --chown=posthog:posthog gunicorn.config.py ./
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# Add in custom bin files and Django deps.
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COPY --chown=posthog:posthog ./bin ./bin/
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COPY --chown=posthog:posthog manage.py manage.py
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COPY --chown=posthog:posthog posthog posthog/
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@@ -339,9 +338,6 @@ COPY --chown=posthog:posthog common/hogvm common/hogvm/
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COPY --chown=posthog:posthog dags dags/
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COPY --chown=posthog:posthog products products/
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# Keep server command backwards compatible
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RUN cp ./bin/docker-server-unit ./bin/docker-server
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# Setup ENV.
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ENV NODE_ENV=production \
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CHROME_BIN=/usr/bin/chromium \
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@@ -1,27 +1,4 @@
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#!/bin/bash
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set -e
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./bin/migrate-check
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# To ensure we are able to expose metrics from multiple processes, we need to
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# provide a directory for `prometheus_client` to store a shared registry.
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export PROMETHEUS_MULTIPROC_DIR=$(mktemp -d)
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trap 'rm -rf "$PROMETHEUS_MULTIPROC_DIR"' EXIT
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export PROMETHEUS_METRICS_EXPORT_PORT=8001
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export STATSD_PORT=${STATSD_PORT:-8125}
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exec gunicorn posthog.wsgi \
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--config gunicorn.config.py \
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--bind 0.0.0.0:8000 \
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--log-file - \
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--log-level info \
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--access-logfile - \
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--worker-tmp-dir /dev/shm \
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--workers=2 \
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--threads=8 \
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--keep-alive=60 \
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--backlog=${GUNICORN_BACKLOG:-1000} \
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--worker-class=gthread \
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${STATSD_HOST:+--statsd-host $STATSD_HOST:$STATSD_PORT} \
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--limit-request-line=16384 $@
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# Wrapper script for backward compatibility
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# Calls the dual-mode server script (Granian/Unit)
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exec "$(dirname "$0")/docker-server-unit" "$@"
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@@ -7,15 +7,48 @@ set -e
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# provide a directory for `prometheus_client` to store a shared registry.
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export PROMETHEUS_MULTIPROC_DIR=$(mktemp -d)
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chmod -R 777 $PROMETHEUS_MULTIPROC_DIR
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trap 'rm -rf "$PROMETHEUS_MULTIPROC_DIR"' EXIT
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export PROMETHEUS_METRICS_EXPORT_PORT=8001
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export STATSD_PORT=${STATSD_PORT:-8125}
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export NGINX_UNIT_PYTHON_PROTOCOL=${NGINX_UNIT_PYTHON_PROTOCOL:-wsgi}
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export NGINX_UNIT_APP_PROCESSES=${NGINX_UNIT_APP_PROCESSES:-4}
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envsubst < /docker-entrypoint.d/unit.json.tpl > /docker-entrypoint.d/unit.json
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# Dual-mode support: USE_GRANIAN env var switches between Granian and Unit (default)
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if [ "${USE_GRANIAN:-false}" = "true" ]; then
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echo "🚀 Starting with Granian ASGI server (opt-in via USE_GRANIAN=true)..."
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# We need to run as --user root so that nginx unit can proxy the control socket for stats
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# However each application is run as "nobody"
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exec /usr/local/bin/docker-entrypoint.sh unitd --no-daemon --user root
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# Granian configuration
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export GRANIAN_WORKERS=${GRANIAN_WORKERS:-4}
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export GRANIAN_THREADS=2
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# Start metrics HTTP server in background on port 8001
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python ./bin/granian_metrics.py &
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METRICS_PID=$!
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# Combined trap: kill metrics server and cleanup temp directory
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trap 'kill $METRICS_PID 2>/dev/null; rm -rf "$PROMETHEUS_MULTIPROC_DIR"' EXIT
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exec granian \
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--interface asgi \
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posthog.asgi:application \
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--workers $GRANIAN_WORKERS \
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--runtime-threads $GRANIAN_THREADS \
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--runtime-mode mt \
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--loop uvloop \
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--host 0.0.0.0 \
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--port 8000 \
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--log-level warning \
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--access-log \
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--respawn-failed-workers
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else
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echo "🔧 Starting with Nginx Unit server (default, stable)..."
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# Cleanup temp directory on exit
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trap 'rm -rf "$PROMETHEUS_MULTIPROC_DIR"' EXIT
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export NGINX_UNIT_PYTHON_PROTOCOL=${NGINX_UNIT_PYTHON_PROTOCOL:-wsgi}
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export NGINX_UNIT_APP_PROCESSES=${NGINX_UNIT_APP_PROCESSES:-4}
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envsubst < /docker-entrypoint.d/unit.json.tpl > /docker-entrypoint.d/unit.json
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# We need to run as --user root so that nginx unit can proxy the control socket for stats
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# However each application is run as "nobody"
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exec /usr/local/bin/docker-entrypoint.sh unitd --no-daemon --user root
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fi
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66
bin/granian_metrics.py
Executable file
66
bin/granian_metrics.py
Executable file
@@ -0,0 +1,66 @@
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#!/usr/bin/env python3
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"""
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Metrics HTTP server for Granian multi-process setup.
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Serves Prometheus metrics on port 8001 (configurable via PROMETHEUS_METRICS_EXPORT_PORT).
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Aggregates metrics from all Granian worker processes using prometheus_client multiprocess mode.
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Exposes Granian-equivalent metrics to maintain dashboard compatibility with previous Gunicorn setup.
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"""
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import os
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import time
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import logging
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from prometheus_client import CollectorRegistry, Gauge, multiprocess, start_http_server
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logger = logging.getLogger(__name__)
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def create_granian_metrics(registry: CollectorRegistry) -> None:
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"""
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Create Granian-equivalent metrics to maintain compatibility with existing Grafana dashboards.
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These metrics mirror the Gunicorn metrics that were previously exposed, allowing existing
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dashboards and alerts to continue working with minimal changes.
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"""
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# Read Granian configuration from environment
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workers = int(os.environ.get("GRANIAN_WORKERS", 4))
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threads = int(os.environ.get("GRANIAN_THREADS", 2))
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# Expose static configuration as gauges
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# These provide equivalent metrics to what gunicorn/unit previously exposed
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max_worker_threads = Gauge(
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"granian_max_worker_threads",
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"Maximum number of threads per worker",
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registry=registry,
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)
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max_worker_threads.set(threads)
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total_workers = Gauge(
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"granian_workers_total",
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"Total number of Granian workers configured",
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registry=registry,
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)
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total_workers.set(workers)
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def main():
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"""Start HTTP server to expose Prometheus metrics from all workers."""
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registry = CollectorRegistry()
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multiprocess.MultiProcessCollector(registry)
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# Create Granian-specific metrics for dashboard compatibility
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create_granian_metrics(registry)
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port = int(os.environ.get("PROMETHEUS_METRICS_EXPORT_PORT", 8001))
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logger.info(f"Starting Prometheus metrics server on port {port}")
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start_http_server(port=port, registry=registry)
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# Keep the server running
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while True:
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time.sleep(3600)
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if __name__ == "__main__":
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main()
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@@ -25,4 +25,13 @@ else
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echo "🐧 Linux detected, binding to Docker bridge gateway: $HOST_BIND"
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fi
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python ${DEBUG:+ -m debugpy --listen 127.0.0.1:5678} -m uvicorn --reload posthog.asgi:application --host $HOST_BIND --log-level debug --reload-include "posthog/" --reload-include "ee/" --reload-include "products/"
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python ${DEBUG:+ -m debugpy --listen 127.0.0.1:5678} -m granian \
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--interface asgi \
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posthog.asgi:application \
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--reload \
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--reload-paths ./posthog \
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--reload-paths ./ee \
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--reload-paths ./products \
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--host $HOST_BIND \
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--log-level debug \
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--workers 1
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@@ -302,7 +302,7 @@ docker:
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hidden: true
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docker:server:
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bin_script: docker-server
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description: Run gunicorn application server with Prometheus metrics support
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description: Run dual-mode server (Granian/Unit) with Prometheus metrics support
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hidden: true
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docker:server-unit:
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bin_script: docker-server-unit
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@@ -433,6 +433,10 @@ tools:
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bin_script: create-notebook-node.sh
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description: Create a new NotebookNode file and update types and editor references
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hidden: true
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tool:granian-metrics:
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bin_script: granian_metrics.py
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description: HTTP server that aggregates Prometheus metrics from Granian workers
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hidden: true
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sync:storage:
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bin_script: sync-storage
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description: 'TODO: add description for sync-storage'
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@@ -1,253 +0,0 @@
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#!/usr/bin/env python3
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import os
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import sys
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import time
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import socket
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import struct
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import logging
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import threading
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import structlog
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from prometheus_client import CollectorRegistry, Gauge, multiprocess, start_http_server
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loglevel = "error"
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keepalive = 120
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# Set the timeout to something lower than any downstreams, such that if the
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# timeout is hit, then the worker will be killed and respawned, which will then
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# we able to pick up any connections that were previously pending on the socket
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# and serve the requests before the downstream timeout.
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timeout = 15
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grateful_timeout = 120
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METRICS_UPDATE_INTERVAL_SECONDS = int(os.getenv("GUNICORN_METRICS_UPDATE_SECONDS", 5))
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def when_ready(server):
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"""
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To ease being able to hide the /metrics endpoint when running in production,
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we serve the metrics on a separate port, using the
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prometheus_client.multiprocess Collector to pull in data from the worker
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processes.
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"""
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registry = CollectorRegistry()
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multiprocess.MultiProcessCollector(registry)
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port = int(os.environ.get("PROMETHEUS_METRICS_EXPORT_PORT", 8001))
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start_http_server(port=port, registry=registry)
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# Start a thread in the Arbiter that will monitor the backlog on the sockets
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# Gunicorn is listening on.
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socket_monitor = SocketMonitor(server=server, registry=registry)
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socket_monitor.start()
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def post_fork(server, worker):
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"""
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Within each worker process, start a thread that will monitor the thread and
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connection pool.
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"""
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worker_monitor = WorkerMonitor(worker=worker)
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worker_monitor.start()
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def worker_exit(server, worker):
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"""
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Ensure that we mark workers as dead with the prometheus_client such that
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any cleanup can happen.
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"""
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multiprocess.mark_process_dead(worker.pid)
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class SocketMonitor(threading.Thread):
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"""
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We have enabled the statsd collector for Gunicorn, but this doesn't include
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the backlog due to concerns over portability, see
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https://github.com/benoitc/gunicorn/pull/2407
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Instead, we expose to Prometheus a gauge that will report the backlog size.
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We can then:
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1. use this to monitor how well the Gunicorn instances are keeping up with
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requests.
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2. use this metric to handle HPA scaling e.g. in Kubernetes
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"""
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def __init__(self, server, registry):
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super().__init__()
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self.daemon = True
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self.server = server
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self.registry = registry
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def run(self):
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"""
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Every X seconds, check to see how many connections are pending for each
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server socket.
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We label each individually, as limits such as `--backlog` will apply to
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each individually.
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"""
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if sys.platform != "linux":
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# We use the assumption that we are on Linux to be able to get the
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# socket backlog, so if we're not on Linux, we return immediately.
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return
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backlog_gauge = Gauge(
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"gunicorn_pending_connections",
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"The number of pending connections on all sockets. Linux only.",
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registry=self.registry,
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labelnames=["listener"],
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)
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while True:
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for sock in self.server.LISTENERS:
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backlog = self.get_backlog(sock=sock)
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backlog_gauge.labels(listener=str(sock)).set(backlog)
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time.sleep(METRICS_UPDATE_INTERVAL_SECONDS)
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def get_backlog(self, sock):
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# tcp_info struct from include/uapi/linux/tcp.h
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fmt = "B" * 8 + "I" * 24
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tcp_info_struct = sock.getsockopt(socket.IPPROTO_TCP, socket.TCP_INFO, 104)
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# 12 is tcpi_unacked
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return struct.unpack(fmt, tcp_info_struct)[12]
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class WorkerMonitor(threading.Thread):
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"""
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There is a statsd logger support in Gunicorn that allows us to gather
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metrics e.g. on the number of workers, requests, request duration etc. See
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https://docs.gunicorn.org/en/stable/instrumentation.html for details.
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To get a better understanding of the pool utilization, number of accepted
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connections, we start a thread in head worker to report these via prometheus
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metrics.
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"""
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def __init__(self, worker):
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super().__init__()
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self.daemon = True
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self.worker = worker
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def run(self):
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"""
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Every X seconds, check the status of the Thread pool, as well as the
|
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"""
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active_worker_connections = Gauge(
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"gunicorn_active_worker_connections",
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"Number of active connections.",
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labelnames=["pid"],
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)
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max_worker_connections = Gauge(
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"gunicorn_max_worker_connections",
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"Maximum worker connections.",
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labelnames=["pid"],
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)
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total_threads = Gauge(
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"gunicorn_max_worker_threads",
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"Size of the thread pool per worker.",
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labelnames=["pid"],
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)
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active_threads = Gauge(
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"gunicorn_active_worker_threads",
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"Number of threads actively processing requests.",
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labelnames=["pid"],
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)
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pending_requests = Gauge(
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"gunicorn_pending_requests",
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"Number of requests that have been read from a connection but have not completed yet",
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labelnames=["pid"],
|
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)
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max_worker_connections.labels(pid=self.worker.pid).set(self.worker.cfg.worker_connections)
|
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total_threads.labels(pid=self.worker.pid).set(self.worker.cfg.threads)
|
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|
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while True:
|
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active_worker_connections.labels(pid=self.worker.pid).set(self.worker.nr_conns)
|
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active_threads.labels(pid=self.worker.pid).set(min(self.worker.cfg.threads, len(self.worker.futures)))
|
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pending_requests.labels(pid=self.worker.pid).set(len(self.worker.futures))
|
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|
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time.sleep(METRICS_UPDATE_INTERVAL_SECONDS)
|
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|
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|
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LOGGING_FORMATTER_NAME = os.getenv("LOGGING_FORMATTER_NAME", "default")
|
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|
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|
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# Setup stdlib logging to be handled by Structlog
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def add_pid_and_tid(
|
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logger: logging.Logger, method_name: str, event_dict: structlog.types.EventDict
|
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) -> structlog.types.EventDict:
|
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event_dict["pid"] = os.getpid()
|
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event_dict["tid"] = threading.get_ident()
|
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return event_dict
|
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|
||||
|
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pre_chain = [
|
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# Add the log level and a timestamp to the event_dict if the log entry
|
||||
# is not from structlog.
|
||||
structlog.stdlib.add_log_level,
|
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structlog.stdlib.add_logger_name,
|
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add_pid_and_tid,
|
||||
structlog.processors.TimeStamper(fmt="iso"),
|
||||
]
|
||||
|
||||
|
||||
# This is a copy the default logging config for gunicorn but with additions to:
|
||||
#
|
||||
# 1. non propagate loggers to the root handlers (otherwise we get duplicate log
|
||||
# lines)
|
||||
# 2. use structlog for processing of log records
|
||||
#
|
||||
# See
|
||||
# https://github.com/benoitc/gunicorn/blob/0b953b803786997d633d66c0f7c7b290df75e07c/gunicorn/glogging.py#L48
|
||||
# for the default log settings.
|
||||
logconfig_dict = {
|
||||
"version": 1,
|
||||
"disable_existing_loggers": True,
|
||||
"formatters": {
|
||||
"default": {
|
||||
"()": structlog.stdlib.ProcessorFormatter,
|
||||
"processor": structlog.dev.ConsoleRenderer(colors=True),
|
||||
"foreign_pre_chain": pre_chain,
|
||||
},
|
||||
"json": {
|
||||
"()": structlog.stdlib.ProcessorFormatter,
|
||||
"processor": structlog.processors.JSONRenderer(),
|
||||
"foreign_pre_chain": pre_chain,
|
||||
},
|
||||
},
|
||||
"root": {"level": "INFO", "handlers": ["console"]},
|
||||
"loggers": {
|
||||
"gunicorn.error": {
|
||||
"level": "INFO",
|
||||
"handlers": ["error_console"],
|
||||
"propagate": False,
|
||||
"qualname": "gunicorn.error",
|
||||
},
|
||||
"gunicorn.access": {
|
||||
"level": "INFO",
|
||||
"handlers": ["console"],
|
||||
"propagate": False,
|
||||
"qualname": "gunicorn.access",
|
||||
},
|
||||
},
|
||||
"handlers": {
|
||||
"error_console": {
|
||||
"class": "logging.StreamHandler",
|
||||
"formatter": LOGGING_FORMATTER_NAME,
|
||||
"stream": "ext://sys.stderr",
|
||||
},
|
||||
"console": {
|
||||
"class": "logging.StreamHandler",
|
||||
"formatter": LOGGING_FORMATTER_NAME,
|
||||
"stream": "ext://sys.stdout",
|
||||
},
|
||||
},
|
||||
}
|
||||
@@ -247,9 +247,9 @@ urlpatterns = [
|
||||
|
||||
if settings.DEBUG:
|
||||
# If we have DEBUG=1 set, then let's expose the metrics for debugging. Note
|
||||
# that in production we expose these metrics on a separate port, to ensure
|
||||
# external clients cannot see them. See the gunicorn setup for details on
|
||||
# what we do.
|
||||
# that in production we expose these metrics on a separate port (8001), to ensure
|
||||
# external clients cannot see them. See bin/granian_metrics.py and bin/unit_metrics.py
|
||||
# for details on the production metrics setup.
|
||||
urlpatterns.append(path("_metrics", ExportToDjangoView))
|
||||
# Temporal codec server endpoint for UI decryption - locally only for now
|
||||
urlpatterns.append(path("decode", decode_payloads, name="temporal_decode"))
|
||||
|
||||
@@ -57,8 +57,8 @@ dependencies = [
|
||||
"google-ads==26.1.0",
|
||||
"google-cloud-bigquery==3.26",
|
||||
"google-genai==1.46.0",
|
||||
"granian[uvloop,reload,pname]==2.5.5",
|
||||
"gspread==6.2.1",
|
||||
"gunicorn==20.1.0",
|
||||
"hogql-parser==1.2.11",
|
||||
"infi-clickhouse-orm",
|
||||
"jsonref==1.1.0",
|
||||
@@ -358,7 +358,6 @@ python-version = "3.12"
|
||||
[tool.ty.src]
|
||||
exclude = [
|
||||
"bin/**",
|
||||
"gunicorn.config.py",
|
||||
"manage.py",
|
||||
"posthog/hogql/grammar/**",
|
||||
]
|
||||
|
||||
66
uv.lock
generated
66
uv.lock
generated
@@ -2404,6 +2404,38 @@ requests = [
|
||||
{ name = "requests-toolbelt" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "granian"
|
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version = "2.5.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
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dependencies = [
|
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{ name = "click" },
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]
|
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/f3/2b/8455add059d45514d952bf9cf110ce3b3a9c0ecfaa63e2de07d994b40ed1/granian-2.5.5-cp312-cp312-win_amd64.whl", hash = "sha256:32e4a39f8850298f1fe6900a871db2a1440aba0208b39363e7ca96e81ef2340f", size = 2179015, upload-time = "2025-10-07T17:37:54.594Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
pname = [
|
||||
{ name = "setproctitle" },
|
||||
]
|
||||
reload = [
|
||||
{ name = "watchfiles" },
|
||||
]
|
||||
uvloop = [
|
||||
{ name = "uvloop", marker = "platform_python_implementation == 'CPython' and sys_platform != 'win32'" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "graphene"
|
||||
version = "3.4.3"
|
||||
@@ -2515,18 +2547,6 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/27/76/563fb20dedd0e12794d9a12cfe0198458cc0501fdc7b034eee2166d035d5/gspread-6.2.1-py3-none-any.whl", hash = "sha256:6d4ec9f1c23ae3c704a9219026dac01f2b328ac70b96f1495055d453c4c184db", size = 59977, upload-time = "2025-05-14T15:56:24.014Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "gunicorn"
|
||||
version = "20.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "setuptools" },
|
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]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/28/5b/0d1f0296485a6af03366604142ea8f19f0833894db3512a40ed07b2a56dd/gunicorn-20.1.0.tar.gz", hash = "sha256:e0a968b5ba15f8a328fdfd7ab1fcb5af4470c28aaf7e55df02a99bc13138e6e8", size = 370601, upload-time = "2021-03-27T01:54:37.202Z" }
|
||||
wheels = [
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{ url = "https://files.pythonhosted.org/packages/e4/dd/5b190393e6066286773a67dfcc2f9492058e9b57c4867a95f1ba5caf0a83/gunicorn-20.1.0-py3-none-any.whl", hash = "sha256:9dcc4547dbb1cb284accfb15ab5667a0e5d1881cc443e0677b4882a4067a807e", size = 79531, upload-time = "2021-04-27T12:16:23.375Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "h11"
|
||||
version = "0.16.0"
|
||||
@@ -4264,8 +4284,8 @@ dependencies = [
|
||||
{ name = "google-ads" },
|
||||
{ name = "google-cloud-bigquery" },
|
||||
{ name = "google-genai" },
|
||||
{ name = "granian", extra = ["pname", "reload", "uvloop"] },
|
||||
{ name = "gspread" },
|
||||
{ name = "gunicorn" },
|
||||
{ name = "hogql-parser" },
|
||||
{ name = "infi-clickhouse-orm" },
|
||||
{ name = "jsonref" },
|
||||
@@ -4510,8 +4530,8 @@ requires-dist = [
|
||||
{ name = "google-ads", specifier = "==26.1.0" },
|
||||
{ name = "google-cloud-bigquery", specifier = "==3.26" },
|
||||
{ name = "google-genai", specifier = "==1.46.0" },
|
||||
{ name = "granian", extras = ["uvloop", "reload", "pname"], specifier = "==2.5.5" },
|
||||
{ name = "gspread", specifier = "==6.2.1" },
|
||||
{ name = "gunicorn", specifier = "==20.1.0" },
|
||||
{ name = "hogql-parser", specifier = "==1.2.11" },
|
||||
{ name = "infi-clickhouse-orm", git = "https://github.com/PostHog/infi.clickhouse_orm?rev=9578c79f29635ee2c1d01b7979e89adab8383de2" },
|
||||
{ name = "jsonref", specifier = "==1.1.0" },
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@@ -5885,6 +5905,24 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/a6/24/4d91e05817e92e3a61c8a21e08fd0f390f5301f1c448b137c57c4bc6e543/semver-3.0.4-py3-none-any.whl", hash = "sha256:9c824d87ba7f7ab4a1890799cec8596f15c1241cb473404ea1cb0c55e4b04746", size = 17912, upload-time = "2025-01-24T13:19:24.949Z" },
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]
|
||||
|
||||
[[package]]
|
||||
name = "setproctitle"
|
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version = "1.3.7"
|
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source = { registry = "https://pypi.org/simple" }
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|
||||
[[package]]
|
||||
name = "setuptools"
|
||||
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||||
|
||||
Reference in New Issue
Block a user