User sees default projects in addition to theirs

app.py

@@ -22,22 +22,31 @@ with gr.Blocks() as demo:
  headers=["Year", "Project Name", "Score"],
  datatype=["number", "str", "number"],
  label="Biodiversity scores by year",
+ row_count=0,
  )
  calc_btn.click(
  indexgenerator.calculate_biodiversity_score,
- inputs=[start_year, end_year, project_name],
+ inputs=[start_year, end_year],
  outputs=results_df,
  )
  view_btn.click(
  fn=indexgenerator.show_project_map,
- inputs=[project_name],
  outputs=[m1],
  )
 
  def update_project_dropdown_list(url_params):
  username = url_params.get("username", "default")
  projects = dq.list_projects_by_author(author_id=username)
- return gr.Dropdown.update(choices=projects["name"].tolist())
+ # Initialize the first project in the list
+ project_names = projects['name'].tolist()
+ return gr.Dropdown.update(choices=project_names)
+
+ # Change the project name in the index generator object when the
+ # user selects a new project
+ project_name.change(
+ indexgenerator.set_project,
+ inputs=project_name
+ )
 
  # Get url params
  url_params = gr.JSON({"username": "default"}, visible=False, label="URL Params")

utils/duckdb_queries.py

@@ -18,7 +18,7 @@ else:
 # to-do: pass con through decorator
 def list_projects_by_author(author_id):
  return con.execute(
- "SELECT DISTINCT name FROM project WHERE authorId = ? AND geometry != 'null'",
+ "SELECT DISTINCT name FROM project WHERE (authorId = ? OR authorId = 'default') AND (geometry IS NOT NULL)",
  [author_id],
  ).df()
 

utils/indicators.py

@@ -34,10 +34,26 @@ class IndexGenerator:
  # Authenticate to GEE & DuckDB
  self._authenticate_ee(GEE_SERVICE_ACCOUNT)
 
+ self.project_name = None
+ self.project_geometry = None
+ self.project_centroid = None
+ 
  # Use defined subset of indices
  all_indices = self._load_indices(INDICES_FILE)
  self.indices = {k: all_indices[k] for k in indices}
 
+ def set_project(self, project_name):
+ self.project_name = project_name
+ self.project_geometry = dq.get_project_geometry(self.project_name)
+ self.project_centroid = dq.get_project_centroid(self.project_name)
+
+ # to-do: refactor to involve fewer transformations
+ _polygon = json.dumps(
+ json.loads(self.project_geometry[0][0])["features"][0]["geometry"]
+ )
+ # to-do: don't use self.roi and instead pass patameter strategically
+ self.roi = ee.Geometry.Polygon(json.loads(_polygon)["coordinates"])
+
  def _cloudfree(self, gee_path, daterange):
  """
  Internal method to generate a cloud-free composite.
@@ -146,7 +162,7 @@ class IndexGenerator:
  logging.info(f"Calculated zonal mean for {index_key}.")
  return out
 
- def generate_composite_index_df(self, year, project_geometry, indices=[]):
+ def generate_composite_index_df(self, year, indices=[]):
  data = {
  "metric": indices,
  "year": year,
@@ -175,36 +191,28 @@ class IndexGenerator:
  ee.Initialize(credentials)
  logging.info("Authenticated to Google Earth Engine.")
 
- def _calculate_yearly_index(self, years, project_name):
+ def _calculate_yearly_index(self, years):
  dfs = []
  logging.info(years)
- project_geometry = dq.get_project_geometry(project_name)
- project_centroid = dq.get_project_centroid(project_name)
- # to-do: refactor to involve less transformations
- _polygon = json.dumps(
- json.loads(project_geometry[0][0])["features"][0]["geometry"]
- )
- # to-do: don't use self.roi and instead pass patameter strategically
- self.roi = ee.Geometry.Polygon(json.loads(_polygon)["coordinates"])
 
  # to-do: pararelize?
  for year in years:
  logging.info(year)
- self.project_name = project_name
  df = self.generate_composite_index_df(
- year, project_geometry, list(self.indices.keys())
+ year, self.project_geometry, list(self.indices.keys())
  )
  dfs.append(df)
 
  # Concatenate all dataframes
  df_concat = pd.concat(dfs)
- df_concat["centroid"] = str(project_centroid)
- df_concat["project_name"] = project_name
- df_concat["geojson"] = str(project_geometry)
+ df_concat["centroid"] = str(self.project_centroid)
+ df_concat["project_name"] = self.project_name
+ df_concat["geojson"] = str(self.project_geometry)
  return df_concat.round(2)
 
- # h/t: https://community.plotly.com/t/dynamic-zoom-for-mapbox/32658/12
- def _latlon_to_config(self, longitudes=None, latitudes=None):
+ # h/t: https://community.plotly.com/t/dynamic-zoom-for-mapbox/32658/12\
+ @staticmethod
+ def _latlon_to_config(longitudes=None, latitudes=None):
  """Function documentation:\n
  Basic framework adopted from Krichardson under the following thread:
  https://community.plotly.com/t/dynamic-zoom-for-mapbox/32658/7
@@ -249,9 +257,8 @@ class IndexGenerator:
  # Finally, return the zoom level and the associated boundary-box center coordinates
  return zoom, b_box["center"]
 
- def show_project_map(self, project_name):
- project_geometry = dq.get_project_geometry(project_name)
- features = json.loads(project_geometry[0][0].replace("'", '"'))["features"]
+ def show_project_map(self):
+ features = json.loads(self.project_geometry[0][0].replace("'", '"'))["features"]
  geometry = features[0]["geometry"]
  longitudes = np.array(geometry["coordinates"])[0, :, 0]
  latitudes = np.array(geometry["coordinates"])[0, :, 1]
@@ -287,15 +294,15 @@ class IndexGenerator:
 
  return fig
 
- def calculate_biodiversity_score(self, start_year, end_year, project_name):
+ def calculate_biodiversity_score(self, start_year, end_year):
  years = []
  for year in range(start_year, end_year):
- row_exists = dq.check_if_project_exists_for_year(project_name, year)
+ row_exists = dq.check_if_project_exists_for_year(self.project_name, year)
  if not row_exists:
  years.append(year)
 
  if len(years) > 0:
- df = self._calculate_yearly_index(years, project_name)
+ df = self._calculate_yearly_index(years)
 
  # Write score table to `_temptable`
  dq.write_score_to_temptable(df)
@@ -306,5 +313,5 @@ class IndexGenerator:
  # UPSERT project record
  dq.upsert_project_record()
  logging.info("upserted records into motherduck")
- scores = dq.get_project_scores(project_name, start_year, end_year)
+ scores = dq.get_project_scores(self.project_name, start_year, end_year)
  return scores