new api

Author: ExpDev07

.env.example

@@ -1,9 +1,2 @@
 # Port to serve app on.
-PORT = 5000
-
-# Id of spreadsheet to collect data from (found in the URL).
-# https://docs.google.com/spreadsheets/d/1wQVypefm946ch4XDp37uZ-wartW4V7ILdg-qYiDXUHM/htmlview?usp=sharing&sle=true
-SPREADSHEET_ID = 1wQVypefm946ch4XDp37uZ-wartW4V7ILdg-qYiDXUHM
-
-# A Google Cloud API key that has Google Sheets API enabled.
-GOOGLE_API_KEY = your_api_key
+PORT = 5000

Pipfile

@@ -12,8 +12,8 @@ python-dotenv = "*"
 requests = "*"
 gunicorn = "*"
 flask-cors = "*"
-geopy = "*"
 cachetools = "*"
+python-dateutil = "*"
 
 [requires]
 python_version = "3.8"

Pipfile.lock

@@ -1,7 +1,6 @@
 from flask import Flask
 from flask_cors import CORS
 from app.settings import *
-from app.location import get_locations
 
 # Create the flask application.
 app = Flask(__name__)

app/__init__.py

@@ -0,0 +1,60 @@
+import requests
+import csv
+from cachetools import cached, TTLCache
+from app.utils import date as date_util
+
+"""
+Base URL for fetching data.
+"""
+base_url = 'https://raw.githubusercontent.com/CSSEGISandData/2019-nCoV/master/time_series/time_series_2019-ncov-%s.csv';
+
+@cached(cache=TTLCache(maxsize=1024, ttl=3600))
+def get_data(type):
+    """
+    Retrieves the data for the provided type.
+    """
+
+    # Adhere to type naming standard.
+    type = type.lower().capitalize();
+    
+    # Request the data 
+    request = requests.get(base_url % type)
+    text    = request.text
+
+    # Parse the CSV.
+    data = list(csv.DictReader(text.splitlines()))
+
+    # The normalized locations.
+    locations = []
+
+    for item in data:
+
+        # Normalize the item and append to locations.
+        locations.append({
+            # General info.
+            'country':  item['Country/Region'],
+            'province': item['Province/State'],
+
+            # Coordinates.
+            'coordinates': {
+                'lat':  item['Lat'],
+                'long': item['Long'],
+            },
+
+            # History.
+            'history': dict(filter(lambda element: date_util.is_date(element[0]), item.items())),
+
+            # TODO: Total.
+            'total': 0
+        })
+
+    # Return the final data.
+    return locations
+
+
+
+
+
+
+    
+

app/data/__init__.py

@@ -1 +1,4 @@
-from . import latest
+from . import confirmed
+from . import deaths
+from . import recovered
+from . import latest

app/location.py

@@ -0,0 +1,7 @@
+from flask import jsonify
+from app import app
+from app.data import get_data
+
+@app.route('/confirmed')
+def confirmed():
+    return jsonify(get_data('confirmed'))

app/routes/__init__.py

@@ -0,0 +1,7 @@
+from flask import jsonify
+from app import app
+from app.data import get_data
+
+@app.route('/deaths')
+def deaths():
+    return jsonify(get_data('deaths'))

app/routes/confirmed.py

@@ -1,26 +1,6 @@
-import requests
-import functools
-from flask import jsonify
 from app import app
-from app.location import get_locations
+from app.data import get_data
 
 @app.route('/latest')
 def latest():
-    # Get all the locations.
-    locations = list(map(lambda loc: loc.serialize(), get_locations()))
-
-    # Make some simple statistic calculations.
-    confirmed = sum(map(lambda loc: loc['confirmed'], locations))
-    deaths    = sum(map(lambda loc: loc['deaths'], locations))
-    recovered = sum(map(lambda loc: loc['recovered'], locations))
-
-    # Return the stats and data as json.
-    return {
-        # Stats
-        'confirmed': confirmed,
-        'deaths':    deaths,
-        'recovered': recovered,
-
-        # Data
-        'locations': locations,
-    }
+    return { }