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Testing Guide

This guide covers testing procedures for Stream Daemon in both local and Docker environments.

Table of Contents

Prerequisites

General Requirements

  • Git
  • Access to streaming platform APIs (Twitch, YouTube, Kick)
  • Access to social platform APIs (Bluesky, Mastodon, Discord, Matrix)

Local Testing Requirements

  • Python 3.10+
  • pip or pip3
  • Virtual environment (recommended)

Docker Testing Requirements

  • Docker Engine 20.10+
  • docker-compose (optional)
  • 2GB+ free disk space

Local Environment Testing

1. Quick Installation Test

Run the comprehensive installation test:

python3 test_local_install.py

This test validates:

  • ✅ Python version (3.10+)
  • ✅ Core dependencies (TwitchAPI, Mastodon, Bluesky, Discord, Matrix)
  • ✅ AI/LLM dependencies (Gemini, Ollama)
  • ✅ Security providers (AWS Secrets, Vault, Doppler)
  • ✅ Stream Daemon module imports
  • ✅ CVE-affected package versions

Expected Output:

✅ SUCCESS: 7/7 tests passed

2. Manual Dependency Check

If you prefer to check manually:

# Check Python version
python3 --version

# Install dependencies
pip3 install -r requirements.txt

# Test imports
python3 -c "import twitchAPI; import mastodon; import atproto; print('Core deps OK')"
python3 -c "import google.genai; import ollama; print('AI deps OK')"

3. Module Import Test

Test that all Stream Daemon modules load correctly:

python3 -c "from stream_daemon import messaging, publisher; print('Modules OK')"
python3 -c "from stream_daemon.ai import generator; print('AI module OK')"
python3 -c "from stream_daemon.platforms.streaming import twitch, youtube, kick; print('Streaming OK')"
python3 -c "from stream_daemon.platforms.social import bluesky, mastodon, discord, matrix; print('Social OK')"

4. CVE Security Check

Verify critical packages meet minimum versions:

pip3 list | grep -E "requests|urllib3|protobuf"

Required versions:

  • requests >= 2.32.5
  • urllib3 >= 2.5.0
  • protobuf >= 6.33.1

Docker Environment Testing

1. Full Docker Build Test

Run the comprehensive Docker test:

./test_docker_build.sh

This test validates:

  • ✅ Docker installation
  • ✅ Docker daemon running
  • ✅ Image builds successfully
  • ✅ Python works in container
  • ✅ All dependencies install
  • ✅ docker-compose configuration (if present)

Expected Output:

✅ SUCCESS - Docker build and tests passed!

2. Manual Docker Build

Build the image manually:

cd /path/to/twitch-and-toot
docker build -t stream-daemon:test -f Docker/Dockerfile .

Troubleshooting build failures:

  • Check Dockerfile syntax
  • Verify requirements.txt is present
  • Ensure base image is accessible
  • Check Docker daemon logs: docker system events

3. Test Container Runtime

Start a test container:

# Create test .env
cp .env.example .env
# Edit .env with your credentials

# Run container
docker run --rm --env-file .env stream-daemon:test python3 --version

# Test with actual daemon
docker run --rm --env-file .env stream-daemon:test python3 stream-daemon.py

4. docker-compose Testing

If using docker-compose:

# Validate configuration
docker-compose -f Docker/docker-compose.yml config

# Start services
docker-compose -f Docker/docker-compose.yml up -d

# Check logs
docker-compose -f Docker/docker-compose.yml logs -f

# Stop services
docker-compose -f Docker/docker-compose.yml down

Ollama Integration Testing

Local Ollama Testing

Quick Connection Test

./test_ollama_quick.sh

This tests basic connectivity to your Ollama server.

Comprehensive Ollama Test

# Ensure .env is configured with Ollama settings
python3 test_ollama.py

Expected output:

✅ Ollama connection initialized
✅ Connected to: http://YOUR_IP:11434
✅ Model: gemma3:4b

Generated Bluesky message (202 chars):
[AI-generated message content]

Generated Mastodon message (286 chars):
[AI-generated message content]

Generated stream end message (208 chars):
[AI-generated message content]

✅ SUCCESS: All Ollama tests passed!

Required .env Configuration

LLM_ENABLE=True
LLM_PROVIDER=ollama
LLM_OLLAMA_HOST=http://192.168.1.100
LLM_OLLAMA_PORT=11434
LLM_MODEL=gemma3:4b

Docker Ollama Testing

Test Ollama from within Docker container:

docker run --rm --env-file .env \
  -e LLM_ENABLE=True \
  -e LLM_PROVIDER=ollama \
  -e LLM_OLLAMA_HOST=http://YOUR_OLLAMA_IP:11434 \
  -e LLM_MODEL=gemma3:4b \
  stream-daemon:test python3 test_ollama.py

Note: Ensure Docker container can reach your Ollama server's IP address. Do not use localhost - use actual IP or Docker network names.

Ollama Network Troubleshooting

If Docker can't reach Ollama:

# Test connectivity from container
docker run --rm stream-daemon:test ping -c 3 YOUR_OLLAMA_IP

# Check Ollama is listening on all interfaces
curl http://YOUR_OLLAMA_IP:11434/api/tags

# Verify firewall rules allow Docker bridge network
sudo iptables -L | grep 11434

Continuous Integration

Pre-commit Checks

Before committing code:

# Run all tests
python3 tests/run_all_tests.py

# Check for security issues
pip3 check

# Validate syntax
python3 -m py_compile stream_daemon/**/*.py

Test Matrix

Test Type Local Docker CI/CD
Installation ✅ ✅ ✅
Unit Tests ✅ ✅ ✅
Integration ✅ ✅ ⚠️
Ollama ✅ ✅ ❌
Gemini ✅ ✅ ⚠️

Legend:

  • ✅ Fully supported
  • ⚠️ Requires credentials/configuration
  • ❌ Not available (requires local server)

Common Issues

Python Version Mismatch

Error: Python 3.10+ required, found 3.9.x

Solution:

# Ubuntu/Debian
sudo apt install python3.10 python3.10-venv

# Update alternatives
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 1

Missing Dependencies

Error: ModuleNotFoundError: No module named 'X'

Solution:

# Reinstall dependencies
pip3 install -r requirements.txt --force-reinstall

# Or install specific package
pip3 install X

Docker Build Failures

Error: ERROR: failed to solve

Solution:

# Clear Docker cache
docker builder prune -a

# Rebuild without cache
docker build --no-cache -t stream-daemon:test -f Docker/Dockerfile .

Ollama Connection Refused

Error: Connection refused or Failed to connect

Solution:

  1. Verify Ollama is running: curl http://YOUR_IP:11434/api/tags
  2. Check firewall: sudo ufw allow 11434/tcp
  3. Use IP address, not localhost from Docker
  4. Verify .env has correct LLM_OLLAMA_HOST and LLM_OLLAMA_PORT

Next Steps

After successful testing:

  1. Configure platforms: Set up API credentials in .env
  2. Start monitoring: Run python3 stream-daemon.py or use Docker
  3. Monitor logs: Check for successful connections and message posts
  4. Production deployment: Follow systemd-service.md for persistent service

Additional Resources