adding python functionalities

Python/example.py

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+import time
+from ninja_automator import ninja_download_wind_csv
+
+#####
+## ##  DOWNLOAD RENEWABLE TIME SERIES DATA FOR MULTIPLE LOCATIONS
+#####
+
+# downloading data for a single loaction would be the same, but with calling either of wind or solar functions for a single location
+# location_df in this example would be like:
+# locations_df = pd.DataFrame({'lat': [-37.23, -37.23, -37.23, -37.23, -37.23],
+#                              'lon': [143.05, 143.05, 143.05, 143.05, 143.05]})
+#                           'name': ['location1', 'location2', 'location3', 'location4', 'location5']})
+
+i = 0
+for index, row in locations_df.iterrows():
+    if i < 50:
+        ninja_download_wind_csv(lat = row['lat'], lon = row['lon'], out_dir = 'ninja_wind', out_naming = row['name'], token = 'your_token_here')
+        time.sleep(10)
+        i += 1
+    else:
+        print('Sleeping for an hour')
+        time.sleep(3600)
+        i = 0

Python/ninja_automator.py

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+import csv
+import pandas as pd
+from pathlib import Path
+import requests
+
+
+#####
+## ##  FUNCTIONS TO BUILD THE URL FOR API REQUESTS 
+#####
+
+# example wind url: https://www.renewables.ninja/api/data/wind?&lat=-37.23&lon=143.05&date_from=2014-01-01&date_to=2014-02-28&capacity=240&dataset=merra2&height=83&turbine=Vestas+V80+2000&format=csv
+def ninja_build_wind_url(lat, lon, start_date='2019-01-01', end_date='2019-12-31', dataset='merra2', 
+                         capacity=1, height=60, turbine='Vestas+V80+2000', raw='false', format='csv'):
+		return f'https://www.renewables.ninja/api/data/wind?&lat={lat}&lon={lon}&date_from={start_date}\
+            &date_to={end_date}&capacity={capacity}&dataset={dataset}&height={height}&turbine={turbine}&raw={raw}&format={format}'.replace(" ", "")
+
+# example solar url: https://www.renewables.ninja/api/data/pv?lat=45&lon=22&date_from=2014-01-01&date_to=2014-01-31&dataset=merra2&capacity=1&system_loss=0.1&tracking=0&tilt=35&azim=180&raw=false&format=csv
+def ninja_build_solar_url(lat, lon, start_date='2019-01-01', end_date='2019-12-31', dataset='merra2', 
+                          capacity=1, system_loss=0.1, tracking=0, tilt=35, azim=180, raw='false', format='csv'):
+		return f'https://www.renewables.ninja/api/data/pv?&lat={lat}&lon={lon}&date_from={start_date}\
+            &date_to={end_date}&capacity={capacity}&dataset={dataset}&system_loss={system_loss}&tracking={tracking}&raw={raw}&tilt={tilt}&azim={azim}&format={format}'.replace(" ", "")
+
+#####
+## ##  FUNCTIONS TO DOWNLOAD A SINGLE REQUEST FROM THE API 
+#####
+
+# download wind or solar power output for a given location
+#
+# pass 'lat' and 'lon', and optionally other api variables
+#
+# pass naming, and directory for output file(s)
+#
+# returns a data frame with timestamp and power output
+#
+
+def ninja_download_wind_csv(lat, lon, output_dir, output_naming, token, start_date='2019-01-01', end_date='2019-12-31'):
+    with requests.Session() as s:
+        headers = {'Authorization': 'Token ' + token}
+        download = s.get(ninja_build_wind_url(lat, lon, start_date, end_date), headers=headers)
+        decoded_content = download.content.decode('utf-8')
+        cr = csv.reader(decoded_content.splitlines(), delimiter=',')
+        ninja_wind_df = pd.DataFrame(list(cr))
+        ninja_wind_df.to_csv(Path(output_dir) / f"ninja_wind_{output_naming}.csv", index=False)
+
+        return ninja_wind_df
+
+def ninja_download_solar_csv(lat, lon, output_dir, output_naming, token, start_date='2019-01-01', end_date='2019-12-31'):
+    with requests.Session() as s:
+        headers = {'Authorization': 'Token ' + token}
+        download = s.get(ninja_build_solar_url(lat, lon, start_date, end_date), headers=headers)
+        decoded_content = download.content.decode('utf-8')
+        cr = csv.reader(decoded_content.splitlines(), delimiter=',')
+        ninja_solar_df = pd.DataFrame(list(cr))
+        ninja_solar_df.to_csv(Path(output_dir) / f"ninja_solar_{output_naming}.csv", index=False)
+
+        return ninja_solar_df