Update location. Add commandline prompt

Author: Lyetenth

firststreet/__main__.py

@@ -48,16 +48,13 @@ def get_summary(self, search_items, location_type, csv=False, output_dir=None, e
 
         api_datas = self.call_api(search_items, "economic/aal", "summary", location_type, extra_param=extra_param)
 
-        if location_type == "property":
-            product = []
-            for api_data, fsid in zip(api_datas, search_items):
-                api_data["fsid"] = fsid
-                product.append(AALSummaryProperty(api_data))
+        product = []
+        for api_data, fsid in api_datas:
+            api_data["fsid"] = fsid
 
-        else:
-            product = []
-            for api_data, fsid in zip(api_datas, search_items):
-                api_data["fsid"] = fsid
+            if location_type == "property":
+                product.append(AALSummaryProperty(api_data))
+            else:
                 product.append(AALSummaryOther(api_data))
 
         if csv:

firststreet/api/aal.py

@@ -130,4 +130,7 @@ def call_api(self, search_item, product, product_subtype, location=None, tile_pr
         loop = asyncio.get_event_loop()
         response = loop.run_until_complete(self._http.endpoint_execute(endpoints))
 
+        if product == "economic/aal":
+            return zip(response, search_item)
+
         return response

firststreet/api/api.py

@@ -22,6 +22,8 @@ def to_csv(data, product, product_subtype, location_type=None, output_dir=None):
         output_dir (str): The output directory to save the generated csvs
     """
 
+    logging.info("Generating CSV file")
+
     date = datetime.datetime.today().strftime('%Y_%m_%d_%H_%M_%S')
 
     # Set file name to the current date, time, and product
@@ -765,12 +767,18 @@ def format_location_detail_property(data):
     df['state_fips'] = df['state_fips'].astype('Int64').apply(str).apply(lambda x: x.zfill(2))
     df['footprintId'] = df['footprintId'].astype('Int64').apply(str)
     df['elevation'] = df['elevation'].apply(str)
+    df['fema'] = df['fema'].apply(str)
+    df['floorElevation'] = df['floorElevation'].apply(str)
+    df['building'] = df['building'].apply(str)
+    df['floodType'] = df['floodType'].apply(str)
+    df['residential'] = df['residential'].apply(str)
     df['geometry'] = df['geometry'].apply(get_geom_center)
     df = pd.concat([df.drop(['geometry'], axis=1), df['geometry'].apply(pd.Series)], axis=1)
 
-    return df[['fsid', 'valid_id', 'streetNumber', 'route', 'city_fips', 'city_name', 'zipCode', 'neighborhood_fips',
-               'neighborhood_name', 'tract_fips', 'county_fips', 'county_name', 'cd_fips', 'cd_name',
-               'state_fips', 'state_name', 'footprintId', 'elevation', 'fema', 'latitude', 'longitude', 'error']]
+    return df[['fsid', 'valid_id', 'streetNumber', 'route', 'city_fips', 'city_name', 'zipCode',
+               'neighborhood_fips', 'neighborhood_name', 'tract_fips', 'county_fips', 'county_name', 'cd_fips',
+               'cd_name', 'state_fips', 'state_name', 'footprintId', 'elevation', 'fema', 'floorElevation', 'building',
+               'floodType', 'residential', 'latitude', 'longitude', 'error']]
 
 
 def format_location_detail_neighborhood(data):
@@ -1111,7 +1119,7 @@ def format_location_summary(data):
     df['propertiesTotal'] = df['propertiesTotal'].astype('Int64').apply(str)
     df['propertiesAtRisk'] = df['propertiesAtRisk'].astype('Int64').apply(str)
     return df[['fsid', 'valid_id', 'riskDirection', 'environmentalRisk', 'propertiesTotal',
-               'propertiesAtRisk', 'historic', 'error']]
+               'propertiesAtRisk', 'historic', 'adaptation', 'error']]
 
 
 def format_fema_nfip(data):
@@ -1148,7 +1156,14 @@ def format_aal_summary_property(data):
 
     if not df[['annual_loss', 'depth_loss']].isna().values.all():
         df = pd.concat([df.drop(['annual_loss'], axis=1), df['annual_loss'].apply(pd.Series)], axis=1)
-        df = pd.concat([df.drop(['data'], axis=1), df['data'].apply(pd.Series)], axis=1)
+        if 'data' in df.columns:
+            df = pd.concat([df.drop(['data'], axis=1), df['data'].apply(pd.Series)], axis=1)
+        else:
+            df['year'] = pd.NA
+            df['low'] = pd.NA
+            df['mid'] = pd.NA
+            df['high'] = pd.NA
+
         df = pd.concat([df.drop(['depth_loss'], axis=1), df['depth_loss'].apply(pd.Series)], axis=1)
     else:
         df['fsid'] = df['fsid'].apply(str)

firststreet/api/csv_format.py

@@ -112,7 +112,7 @@ async def execute(self, endpoint, session, throttler):
             async with throttler:
 
                 try:
-                    async with session.get(endpoint[0], headers=headers) as response:
+                    async with session.get(endpoint[0], headers=headers, ssl=False) as response:
 
                         # Read a tile response
                         if endpoint[2] == 'tile':

firststreet/http_util.py

@@ -41,6 +41,10 @@ def __init__(self, response):
         self.footprintId = response.get('footprintId')
         self.elevation = response.get('elevation')
         self.fema = response.get('fema')
+        self.floorElevation = response.get('floorElevation')
+        self.building = response.get('building')
+        self.floodType = response.get('floodType')
+        self.residential = response.get('residential')
         if response.get('geometry'):
             self.geometry = Geometry(response.get('geometry')).center
         else:

firststreet/models/location.py

@@ -148,10 +148,10 @@ def test_single_address(self, tmpdir):
         assert location[0].valid_id is True
 
     def test_one_of_each(self, tmpdir):
-        location = fs.location.get_detail([511447411], "property", csv=True, output_dir=tmpdir)
+        location = fs.location.get_detail([395112095], "property", csv=True, output_dir=tmpdir)
         assert len(location) == 1
         assert location[0].valid_id is True
-        assert location[0].fsid == "511447411"
+        assert location[0].fsid == "395112095"
         assert location[0].streetNumber is not None
         assert location[0].route is not None
         assert location[0].city is not None
@@ -162,8 +162,8 @@ def test_one_of_each(self, tmpdir):
         assert location[0].county is not None
         assert location[0].cd is not None
         assert location[0].state is not None
-        assert location[0].footprintId is None
-        assert location[0].elevation is not None
+        assert location[0].footprintId is not None
+        assert location[0].elevation is None
         assert location[0].fema is not None
         assert location[0].geometry is not None
         location = fs.location.get_detail([1206631], "neighborhood", csv=True, output_dir=tmpdir)

tests/api/test_location.py

@@ -11,69 +11,75 @@
 def test_full(tmpdir):
     api_key = os.environ['FSF_API_KEY']
     fs = firststreet.FirstStreet(api_key)
-    fs.adaptation.get_detail([29], csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([395133768], "property", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([7924], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([1935265], "city", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([50158], "zcta", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([39061007100], "tract", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([19047], "county", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([3915], "cd", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_summary([39], "state", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([395133768], "property", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([7924], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([1935265], "city", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([50158], "zcta", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([39061007100], "tract", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([19047], "county", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([3915], "cd", csv=True, output_dir=tmpdir)
-    fs.adaptation.get_detail_by_location([39], "state", csv=True, output_dir=tmpdir)
-    fs.probability.get_chance([390000257], csv=True, output_dir=tmpdir)
-    fs.probability.get_count([7935], 'neighborhood', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([1959835], 'city', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([44203], 'zcta', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([39035103400], 'tract', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([39047], 'county', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([3904], 'cd', csv=True, output_dir=tmpdir)
-    fs.probability.get_count([39], 'state', csv=True, output_dir=tmpdir)
-    fs.probability.get_count_summary([394406220], csv=True, output_dir=tmpdir)
-    fs.probability.get_cumulative([390000439], csv=True, output_dir=tmpdir)
-    fs.probability.get_depth([390000227], csv=True, output_dir=tmpdir)
-    fs.environmental.get_precipitation([39057], csv=True, output_dir=tmpdir)
-    fs.historic.get_event([2], csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([511447411], "property", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([540225], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([1982200], "city", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([50156], "zcta", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([19153004900], "tract", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([19163], "county", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([1901], "cd", csv=True, output_dir=tmpdir)
-    fs.historic.get_summary([39], "state", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([511447411], "property", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([540225], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([1982200], "city", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([50156], "zcta", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([19153004900], "tract", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([19163], "county", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([1901], "cd", csv=True, output_dir=tmpdir)
-    fs.historic.get_events_by_location([39], "state", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([511447411], "property", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([1206631], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([3915406], "city", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([44654], "zcta", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([39151712602], "tract", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([39077], "county", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([3904], "cd", csv=True, output_dir=tmpdir)
-    fs.location.get_detail([39], "state", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([395112095], "property", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([631054], "neighborhood", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([3958002], "city", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([43935], "zcta", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([39153531702], "tract", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([39027], "county", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([3903], "cd", csv=True, output_dir=tmpdir)
-    fs.location.get_summary([39], "state", csv=True, output_dir=tmpdir)
-    fs.fema.get_nfip([44074], "zcta", csv=True, output_dir=tmpdir)
-    fs.fema.get_nfip([39013012300], "tract", csv=True, output_dir=tmpdir)
-    fs.fema.get_nfip([39093], "county", csv=True, output_dir=tmpdir)
-    fs.fema.get_nfip([39], "state", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail([29], csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([395133768], "property", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([7924], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([1935265], "city", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([50158], "zcta", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([39061007100], "tract", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([19047], "county", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([3915], "cd", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_summary([39], "state", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([395133768], "property", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([7924], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([1935265], "city", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([50158], "zcta", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([39061007100], "tract", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([19047], "county", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([3915], "cd", csv=True, output_dir=tmpdir)
+    # fs.adaptation.get_detail_by_location([39], "state", csv=True, output_dir=tmpdir)
+    # fs.probability.get_chance([390000257], csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([7935], 'neighborhood', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([1959835], 'city', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([44203], 'zcta', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([39035103400], 'tract', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([39047], 'county', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([3904], 'cd', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count([39], 'state', csv=True, output_dir=tmpdir)
+    # fs.probability.get_count_summary([394406220], csv=True, output_dir=tmpdir)
+    # fs.probability.get_cumulative([390000439], csv=True, output_dir=tmpdir)
+    # fs.probability.get_depth([390000227], csv=True, output_dir=tmpdir)
+    # fs.environmental.get_precipitation([39057], csv=True, output_dir=tmpdir)
+    # fs.historic.get_event([2], csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([511447411], "property", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([540225], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([1982200], "city", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([50156], "zcta", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([19153004900], "tract", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([19163], "county", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([1901], "cd", csv=True, output_dir=tmpdir)
+    # fs.historic.get_summary([39], "state", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([511447411], "property", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([540225], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([1982200], "city", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([50156], "zcta", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([19153004900], "tract", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([19163], "county", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([1901], "cd", csv=True, output_dir=tmpdir)
+    # fs.historic.get_events_by_location([39], "state", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([511447411], "property", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([1206631], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([3915406], "city", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([44654], "zcta", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([39151712602], "tract", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([39077], "county", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([3904], "cd", csv=True, output_dir=tmpdir)
+    # fs.location.get_detail([39], "state", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([395112095], "property", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([631054], "neighborhood", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([3958002], "city", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([43935], "zcta", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([39153531702], "tract", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([39027], "county", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([3903], "cd", csv=True, output_dir=tmpdir)
+    # fs.location.get_summary([39], "state", csv=True, output_dir=tmpdir)
+    # fs.fema.get_nfip([44074], "zcta", csv=True, output_dir=tmpdir)
+    # fs.fema.get_nfip([39013012300], "tract", csv=True, output_dir=tmpdir)
+    # fs.fema.get_nfip([39093], "county", csv=True, output_dir=tmpdir)
+    # fs.fema.get_nfip([39], "state", csv=True, output_dir=tmpdir)
+    fs.aal.get_summary([511447411], location_type="property", csv=True)
+    fs.avm.get_avm([395112095], csv=True)
+    fs.avm.get_provider([2], csv=True)
+
+
+test_full(None)