Documentación interactiva para la API

Priorizador

Environment variables

cd priorizador
touch .env
touch .env.development.local

.env.development.local

REACT_APP_API_URL='http://localhost:5000/reaccion'
TEKOPORA='1C4YS7tiQxAZ8vH4A46HpSc03xR0PVRA74itIcUdjYjQ'
ALMUERZO='18NgsyLY-BVR9lQ48oDs-2tf3QeQYxSGF0ywf1aW661c'
TECHO='11jSqn_p_uXK3xHntUmjws_Eaka1ei3CNyhZ9VRpKJ-w'
FUNDACION='1TnF5CaBj8EQLa8JbNMVnxYMP6W2YGG56mVDg6PeabLo'
CESTAS='1NSrEt9-z6LB0c1RlgXhbvsXbGWZEqJsfk05NAb94lhM'
KOBO_API_TOKEN='XXXXCHANGEXXXX'
ANDE_QUERY=SELECT "COORD_X", "COORD_Y" from "131e75f7-9073-46f6-9e49-f8673595dfc7" WHERE "DPTO" LIKE 'Alto Paran%' AND ("MUNICIPIO" LIKE 'CIUDAD DEL ESTE' OR "MUNICIPIO" LIKE 'HERNANDARIAS' OR "MUNICIPIO" LIKE 'MINGA GUAZU' OR "MUNICIPIO" LIKE 'PRESIDENTE FRANCO')
DASH_DEBUG_MODE=False
REACT_APP_DASH_URL='http://localhost:8050'
REDIS_SERVER=redis

.env

REACT_APP_API_URL='http://localhost:8080/api'
TEKOPORA='1C4YS7tiQxAZ8vH4A46HpSc03xR0PVRA74itIcUdjYjQ'
ALMUERZO='18NgsyLY-BVR9lQ48oDs-2tf3QeQYxSGF0ywf1aW661c'
TECHO='11jSqn_p_uXK3xHntUmjws_Eaka1ei3CNyhZ9VRpKJ-w'
FUNDACION='1TnF5CaBj8EQLa8JbNMVnxYMP6W2YGG56mVDg6PeabLo'
CESTAS='1NSrEt9-z6LB0c1RlgXhbvsXbGWZEqJsfk05NAb94lhM'
KOBO_API_TOKEN='XXXXCHANGEXXXX'
ANDE_QUERY=SELECT "COORD_X", "COORD_Y" from "131e75f7-9073-46f6-9e49-f8673595dfc7" WHERE "DPTO" LIKE 'Alto Paran%' AND ("MUNICIPIO" LIKE 'CIUDAD DEL ESTE' OR "MUNICIPIO" LIKE 'HERNANDARIAS' OR "MUNICIPIO" LIKE 'MINGA GUAZU' OR "MUNICIPIO" LIKE 'PRESIDENTE FRANCO')
DASH_DEBUG_MODE=False
REACT_APP_DASH_URL='http://localhost:8050'
REDIS_SERVER=redis

For the API:

cd priorizador/flask_api
touch .env

.env content

TEKOPORA='1C4YS7tiQxAZ8vH4A46HpSc03xR0PVRA74itIcUdjYjQ'
ALMUERZO='18NgsyLY-BVR9lQ48oDs-2tf3QeQYxSGF0ywf1aW661c'
TECHO='11jSqn_p_uXK3xHntUmjws_Eaka1ei3CNyhZ9VRpKJ-w'
FUNDACION='1TnF5CaBj8EQLa8JbNMVnxYMP6W2YGG56mVDg6PeabLo'
CESTAS='1NSrEt9-z6LB0c1RlgXhbvsXbGWZEqJsfk05NAb94lhM'
KOBO_API_TOKEN='XXXXCHANGEXXXX'
ANDE_QUERY=SELECT "COORD_X", "COORD_Y" from "131e75f7-9073-46f6-9e49-f8673595dfc7" WHERE "DPTO" LIKE 'Alto Paran%' AND ("MUNICIPIO" LIKE 'CIUDAD DEL ESTE' OR "MUNICIPIO" LIKE 'HERNANDARIAS' OR "MUNICIPIO" LIKE 'MINGA GUAZU' OR "MUNICIPIO" LIKE 'PRESIDENTE FRANCO')

For Dash App:

cd priorizador/visualizations_dash
touch .env

.env content

REACT_APP_API_URL='http://localhost:5000/reaccion'
DASH_DEBUG_MODE=True
REDIS_SERVER=localhost

Running the frontend locally

yarn install

In the project directory, you can run:

yarn start

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

yarn test

Launches the test runner in the interactive watch mode. See the section about running tests for more information.

yarn build

Builds the app for production to the build folder. It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes. Your app is ready to be deployed!

See the section about deployment for more information.

Running the API locally

For Python=3.7

To use the api you should create a virtual environment with python, install virtualenv with pip

pip install virtualenv

Then redirect yourself to the flask_api folder and create an env folder

cd flask_api/ && mkdir env

Then, create the virtual environment and install the requirements

python -m venv env && pip install -r requirements.txt

Finally to run the tests use the following command and everything should be green

pytest

Create a folder named geojson_data and download the geojson file available here in it, then execute the script with the virtual environment activated. python geojson_api.py

Running the Dash App locally

For Python=3.7 It is necessary Redis and to run the API.

Redirect yourself to the visualizations_dash folder and create an env folder

cd visualizations_dash/ && mkdir env

Then, create the virtual environment and install the requirements

python -m venv env && pip install -r requirements.txt

Execute:

. env/bin/activate
python dash_main.py

It is possible to pre-calculate the data periodically at the time specified in dash_main.py (celery.conf.beat_schedule dictionary). To do it:

Run the Celery Worker:

. env/bin/activate
celery -A dash_main.celery worker --loglevel=info

Run the Celery Beat scheduler:

. env/bin/activate
celery -A dash_main.celery beat --loglevel=info

Deploy with docker-compose

Install docker (minimun 17.05) and docker-compose in your local environment.

Execute docker-compose build docker-compose up -d

For production deployment you should change the localhost and port 8080 with your port and servername int the nginx_config files.

Access the API documentation

Easy OpenAPI specs and Swagger UI for your Flask API. Flasgger is a Flask extension to extract OpenAPI-Specification from all Flask views registered in your API.

To open the API documentation on the browser, open the following URL.

http://localhost:5000/apidocs

Contributors / Thanks

Grosip https://github.com/grosip
Javier Perez https://github.com/javierpf
Nahuel Hernandez https://github.com/nahu
Rodrigo Parra https://github.com/rparrapy
Walter Benitez https://github.com/walter-bd
Iván Cáceres https://github.com/ivanarielcaceres
Fernando Cardenas https://github.com/dev-cardenas

reaccionpy / priorizador Goto Github PK

priorizador's Introduction

Priorizador

Environment variables

Running the frontend locally

Running the API locally

Running the Dash App locally

Deploy with docker-compose

Access the API documentation

Contributors / Thanks

Licencia MIT: Licencia

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