Merge pull request #70 from hydroframe/amyj-get_site_variables_remote

adds support for remote running of _get_siteid_data_from_api

src/hf_hydrodata/point.py

@@ -440,6 +440,45 @@ def get_site_variables(*args, **kwargs):
     else:
         options = kwargs
 
+    run_remote = not os.path.exists(HYDRODATA)
+
+    if run_remote:
+
+        # Cannot pass local shapefile to API; pass bounding box instead
+        if 'polygon' in options and options['polygon'] is not None:
+            try:
+                assert 'polygon_crs' in options and options['polygon_crs'] is not None
+            except:
+                raise Exception(
+                    """Please provide 'polygon_crs' with a CRS definition accepted by pyproj.CRS.from_user_input() 
+                   to specify this shape's CRS.""")
+            latitude_range, longitude_range = _get_bbox_from_shape(options['polygon'], options['polygon_crs'])
+
+            # Send bounding box to API; remove polygon filters from API options
+            polygon = options['polygon']
+            polygon_crs = options['polygon_crs']
+            polygon_filter = True
+            del options['polygon']
+            del options['polygon_crs']
+            options['latitude_range'] = latitude_range
+            options['longitude_range'] = longitude_range
+        else:
+            polygon_filter = False
+
+        data_df = _get_siteid_data_from_api(
+            options,
+        )
+
+        # Re-filter on shapefile to trim bounding box
+        if polygon_filter == True:
+            # Clip metadata to polygon. Use this new list of sites to filter data_df.
+            clipped_df = _filter_on_polygon(data_df, polygon, polygon_crs)
+            return clipped_df
+
+        return data_df
+
+    kwargs = _convert_strings_to_type(options)
+
     # Raise error immediately if no filtering parameters supplied (return DataFrame would be too large).
     if len(options.keys()) == 0:
         raise ValueError(
@@ -602,6 +641,30 @@ def get_site_variables(*args, **kwargs):
     return final_df
 
 
+def _get_siteid_data_from_api(options):
+    options = _convert_params_to_string_dict(options)
+
+    q_params = _construct_siteids_string_from_qparams(
+        options
+    )
+
+    point_data_url = f"{HYDRODATA_URL}/api/site-variables-dataframe?{q_params}"
+
+    try:
+        headers = _validate_user()
+        response = requests.get(point_data_url, headers=headers, timeout=180)
+        if response.status_code != 200:
+            raise ValueError(
+                f"{response.content}."
+            )
+
+    except requests.exceptions.Timeout as e:
+        raise ValueError(f"The point_data_url {point_data_url} has timed out.") from e
+
+    data_df = pd.read_pickle(io.BytesIO(response.content))
+    return data_df
+
+
 def _get_data_from_api(
     data_type, data_source, variable, temporal_resolution, aggregation, options
 ):
@@ -721,6 +784,32 @@ def _convert_strings_to_type(options):
     return options
 
 
+def _construct_siteids_string_from_qparams(options):
+    """
+    Constructs the query parameters from the entry and options provided.
+
+    Parameters
+    ----------
+    entry : hydroframe.data_catalog.data_model_access.ModelTableRow
+        variable to be downloaded.
+    options : dictionary
+        datast to which the variable belongs.
+
+    Returns
+    -------
+    data : numpy array
+        the requested data.
+    """
+
+    qparam_values = options
+
+    string_parts = [
+        f"{name}={value}" for name, value in options.items() if value is not None
+    ]
+    result_string = "&".join(string_parts)
+    return result_string
+
+
 def _construct_string_from_qparams(
     data_type, data_source, variable, temporal_resolution, aggregation, options
 ):

tests/hf_hydrodata/test_point.py

@@ -30,7 +30,6 @@ def __init__(self):
 
         # Create a DataFrame with specified column names
         df = pd.DataFrame(data)
-        print("The dataframe is:", df)
         buffer = io.BytesIO()
         df.to_pickle(buffer)
         data_bytes = buffer.getvalue()
@@ -909,6 +908,7 @@ def test_get_citations_ameriflux():
 
 def test_get_variables_lat_lon():
     """Test get_site_variables function with lat/lon filter"""
+
     df = point.get_site_variables(
         latitude_range=(47, 50),
         longitude_range=(-75, -60))
@@ -920,6 +920,22 @@ def test_get_variables_lat_lon():
     assert 'groundwater well' in list(df['site_type'])
 
 
+def test_get_variables_lat_lon():
+    """Test get_site_variables function with lat/lon filter"""
+    #query_parameters = {'latitude_range': '(47, 50)', 'longitude_range': '(-75, -60)'}
+
+    query_parameters = {'latitude_range': '(47, 50)', 'longitude_range': '(-75, -60)'}
+
+    df = point.get_site_variables(
+        query_parameters)
+
+    # Bounds are flexible for if more sites are added
+    assert (len(df) >= 36) & (len(df) <= 50)
+    assert '01011000' in list(df['site_id'])
+    assert 'stream gauge' in list(df['site_type'])
+    assert 'groundwater well' in list(df['site_type'])
+
+
 def test_get_variables_variable_filter():
     """Test get_site_variables function with variable filter"""
     df = point.get_site_variables(