Skip to content

Latest commit

 

History

History
111 lines (76 loc) · 3.08 KB

local.md

File metadata and controls

111 lines (76 loc) · 3.08 KB
Raw

NOTE: The installation guide below is only tested to work on Ubuntu, we recommend using docker for other operating systems.

Local Installation Requirements.

  • Install GDAL on your computer using the command below:
sudo apt-get update && \
sudo apt-get -y install gdal-bin python3-gdal && \
sudo apt-get -y autoremove && \
sudo apt-get clean
  • Install redis on your computer using the command below:
sudo apt-get -y install redis
sudo apt-get -y install redis-tools # For client
  • Confirm Redis Installation
redis-cli

Type ping it should return pong.

If redis is not running check out its documentation

  • Clone the Raw Data API repository on your computer
git clone https://github.com/hotosm/raw-data-api.git
  • Navigate to the repository directory
cd raw-data-api
  • Install the python dependencies
pip install -r requirements.txt

Optional : For Tiles Output

If you opt for tiles output and have ENABLE_TILES : True in env variable . Make sure you install [Tippecanoe] (https://github.com/felt/tippecanoe)

Start the Server

uvicorn API.main:app --reload

Queues

Currently there are two type of queue implemented :

  • "raw_daemon" : Queue for recurring exports which will replace the previous exports if present on the system , can be enabled through uuid:false API Param
  • "raw_ondemand" : Queue for default exports which will create each unique id for exports

Start Celery Worker

You should be able to start celery worker by running following command on different shell

  • Start for default queue 
    celery --app API.api_worker worker --loglevel=INFO --queues="raw_ondemand" -n 'default_worker'
  • Start for recurring queue 
    celery --app API.api_worker worker --loglevel=INFO --queues="raw_daemon" -n 'recurring_worker'

Set no of request that a worker can take at a time by using --concurrency

Note

If you are using postgres database as result_backend for celery you need to install sqlalchemy

pip install SQLAlchemy==2.0.25

Start flower for monitoring queue [OPTIONAL]

Raw Data API uses flower for monitoring the Celery distributed queue. Run this command on a different shell , if you are running redis on same machine your broker could be redis://localhost:6379//.

celery --broker=redis://redis:6379// --app API.api_worker flower --port=5000 --queues="raw_daemon,raw_ondemand"

OR Simply use flower from application itself

celery --broker=redis://localhost:6379// flower

Navigate to the docs to view Raw Data API endpoints

After sucessfully starting the server, visit http://127.0.0.1:8000/v1/docs on your browser to view the API docs.

http://127.0.0.1:8000/v1/docs

Flower dashboard should be available on port 5000 on your localhost.

http://127.0.0.1:5000/