micro_train

Setup & run

Build and run the app with docker-compose

docker-compose up -d --build

List all running containers

docker container ls
CONTAINER ID        IMAGE                     COMMAND                  CREATED             STATUS              PORTS                      NAMES
d6c20ed23c3b        micro_train_lineman_api   "gunicorn --bind=10.…"   6 minutes ago       Up 6 minutes        127.0.0.1:5002->5002/tcp   micro_train_lineman_api_1
8c8e45e01b49        worker                    "celery beat --app=w…"   36 minutes ago      Up 36 minutes                                  micro_train_beat_1
c8926dc61a7b        worker                    "celery worker --app…"   36 minutes ago      Up 36 minutes                                  micro_train_worker_1
a5d04541f565        redis                     "docker-entrypoint.s…"   13 hours ago        Up About an hour    127.0.0.1:6379->6379/tcp   micro_train_redis_1

Usage & live check

###API Endpoints: To check or set barrier state at given station name

Endpoint	Method	Params	Description
/<station_name>	GET	n/a	Get barrier state
/<station_name>	PUT	barrier_state	Set barrier state

e.g. http://127.0.0.1:5002/Sochaczew

###Checking generated logs: All files are stored in Celery Worker container /worker/logfiles/

docker exec -it c8926dc61a7b bash
# ls -lah logfiles/
# cat logfiles/stations.log
# cat logfiles/slow.log
# cat logfiles/normal.log
# cat logfiles/fast.log

###Checking database: Database is SQLite placed in /tmp/test.db file in lineman_api container.

docker exec -it d6c20ed23c3b python
>>> import sqlite3
>>> conn = sqlite3.connect('////tmp/test.db')
>>> c = conn.cursor()
>>> c.execute("SELECT * FROM Station")

Last two commands can be repeated to get latest data from db.

Running tests inside containers

Be aware of that this is actually triggering jobs inside application (generate logs)

Lineman API containter

docker exec -it d6c20ed23c3b pytest /lineman_api/tests_resources.py -vvv

Celery Worker containter (please remember there is 10 sec waiting time)

docker exec -it c8926dc61a7b pytest /app/tests_tasks.py -vvv

Development

Define environment variables in your IDE

CELERY_BROKER_URL=redis://redis:6379/0
CELERY_RESULT_BACKEND=redis://redis:6379/0
TRAIN_SPEED_SCHEDULE=10
STATIONS_SCHEDULE=180
LOG_FILES_PATH=~/micro_train/app/logfiles
HOST=localhost
PORT=5002

Summary

Solution has been implemented with usage of 4 Docker container:

• Tasks Scheduler - Celery Beat
• Tasks Worker - Celery
• DB broker ("the queue") - Redis
• API REST - Flask-RESTfull