#RestPOC
###Step 1:
To install required packages
pip install -r requirements.txt
###Step 2: constants.py file have api url that receives the response and has data path that saves the data
###Step 3:
Schedule rest_call.py using cron, so that it keeps pulling the data from the rest endpoint and keep the data upto date.
python rest_call.py
init method reads the data from the requested API write_response save it in the data folder as csv file
import requests
import constants
from pprint import pprint as p
class runner(object):
"""Whole runner class to schedule it in cronjob"""
def __init__(self, url):
"""Get response data from the url and save it locally"""
self.response_dict = requests.get(url).json()
# p(self.response_dict['data'])
self.data = self.response_dict['data']
self.header_field = list(self.response_dict['data'][0].keys())
def write_response(self, path):
"""write the returned data into a csv file to release as API"""
with open(path, "w") as f:
writer = csv.DictWriter(f, fieldnames=self.header_field)
writer.writeheader()
writer.writerows(self.data)
return "Success"
help(runner)
print(runner(constants.url).write_response(constants.data_path))
###Step 3:
Run release_api.py to read the updated data and release it as an api.
python release_api.py
Reading and Exposing the data as api in "/" path : localhost:5000/ it'll be response as json release method reads csv files and exposes it as json data, sends 200 status to the api
import json
import pandas
import constants
from flask import Flask, Response
app = Flask(__name__)
@app.route('/')
def release():
'''read csv file and return as json response'''
data = pandas.read_csv(filepath_or_buffer=constants.data_path)
response_data = data.to_json(orient='records')
return Response(status=200, response=response_data, mimetype='application/json')
if __name__ == '__main__':
app.run()
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