Basic working something

.gcloudignore

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+# This file specifies files that are *not* uploaded to Google Cloud Platform
+# using gcloud. It follows the same syntax as .gitignore, with the addition of
+# "#!include" directives (which insert the entries of the given .gitignore-style
+# file at that point).
+#
+# For more information, run:
+#   $ gcloud topic gcloudignore
+#
+.gcloudignore
+# If you would like to upload your .git directory, .gitignore file or files
+# from your .gitignore file, remove the corresponding line
+# below:
+.git
+.gitignore
+
+node_modules

.gitignore

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+.DS_Store

.pylintrc

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+generated-members=netCDF4.*

main.py

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+import numpy as np  # numpy module
+import netCDF4 as nc  # netcdf module
+from flask import jsonify
+
+
 def heatwave_api(request):
-    return 'Hello, World!\n'
+    request_json = request.get_json()
+    print(request_json)
+
+    in_nc = nc.Dataset("./data/CCRC_NARCliM_YEA_1950-2009_HWN_EHF_NF13.nc")
+    print(in_nc)
+
+    temps = in_nc.variables['HWN_EHF']
+    print(temps)  # print the variable attributes
+
+    print(temps.dimensions)
+    print(temps.shape)
+
+    mt = in_nc.variables['time']  # read time variable
+    print(mt)  # print the variable attributes
+
+    time = mt[:]  # Reads the netCDF variable MT, array of one element
+    print(time)
+    time_unit = in_nc.variables["time"].getncattr('units')
+    time_cal = in_nc.variables["time"].getncattr(
+        'calendar')  # read calendar type
+    local_time = nc.num2date(time, units=time_unit,
+                             calendar=time_cal)  # convert time
+    print("Original time %s is now converted as %s" %
+          (time[0], local_time[0]))  # check conversion
+
+    lat, lon = in_nc.variables['lat'], in_nc.variables['lon']
+
+    target_lat = -27.4698
+    target_lon = 153.0251
+
+    latvals = lat[:]
+    lonvals = lon[:]  # extract lat/lon values (in degrees) to numpy arrays
+    import numpy as np
+
+    def getclosest_ij(lats, lons, latpt, lonpt):
+        # find squared distance of every point on grid
+        dist_sq = (lats-latpt)**2 + (lons-lonpt)**2
+        minindex_flattened = dist_sq.argmin()  # 1D index of minimum dist_sq element
+        # Get 2D index for latvals and lonvals arrays from 1D index
+        return np.unravel_index(minindex_flattened, latvals.shape)
+
+    iy_min, ix_min = getclosest_ij(latvals, lonvals, target_lat, target_lon)
+    print(iy_min, ix_min)
+
+    temps_vals = temps[:]
+    location_data = []
+
+    for year in range(19):
+        print(temps[year, iy_min, ix_min])
+        location_data.append(int(temps_vals[year, iy_min, ix_min]))
+
+    print(location_data)
+
+    return jsonify({"1960": location_data})
 
 
 if __name__ == "__main__":
     from flask import Flask, request
     app = Flask(__name__)
 
-    @app.route('/')
+    @app.route('/', methods=["GET", "POST"])
     def index():
         return heatwave_api(request)
 

requirements.txt

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+# Function dependencies, for example:
+# package>=version
+
+# Pre-installed packages
+click==6.7
+Flask==1.0.2
+itsdangerous==0.24
+Jinja2==2.10
+MarkupSafe==1.0
+pip==18.0
+requests==2.21.0
+setuptools==40.2.0
+Werkzeug==0.14.1
+wheel==0.31.1
+
+# Custom packages
+numpy==1.17.3
+netCDF4===1.5.3