Merge remote-tracking branch 'origin/dev' into dev

# Conflicts:
#	tests/external/test_external_models.py

.github/workflows/build_sphinx_website.yml

@@ -25,6 +25,7 @@ jobs:
       - name: install dependencies
         run: |
           python -m pip install --upgrade pip
+          pip install -e .
           pip install -r requirements_dev.txt
 
       - name: make html & commit the changes

requirements_dev.txt

@@ -13,3 +13,7 @@ meteostat
 pytest-mock
 furo
 myst-parser
+earthengine-api
+python-dotenv
+myst_parser
+furo

setup.py

@@ -22,13 +22,20 @@
                 'pooch',
                 'python-dateutil',
                 'meteostat',
-                'cyclopts', 'requests', 'pydantic', 'pyyaml',
+                'cyclopts', 'requests',
+                'pydantic>=2.0',
+                'pyyaml',
                 'geopandas', 'libpysal', 'docker',
                 'jax', 'jaxlib', 'blackjax', 'dynamax', 'flax', 'optax',
                 'scipy',
                 'fastapi',
                 'gitpython',  'earthengine-api', 'python-dotenv', 'rq', "python-multipart", "uvicorn",
-                 'pydantic-geojson', 'annotated_types'
+                 'pydantic-geojson', 'annotated_types',
+                'pycountry',
+                'unidecode',
+                'httpx',
+                'earthengine-api'
+
                 ]
 
 test_requirements = ['pytest>=3', "hypothesis"]

tests/external/test_external_models.py

@@ -9,11 +9,11 @@
 
 from climate_health.api import get_model_from_directory_or_github_url
 from climate_health.spatio_temporal_data.temporal_dataclass import DataSet
-from climate_health.datatypes import ClimateHealthTimeSeries
+from climate_health.datatypes import ClimateHealthTimeSeries,FullData
 
 logging.basicConfig(level=logging.INFO)
 from climate_health.external.external_model import get_model_from_yaml_file, run_command
-from ..data_fixtures import full_data, train_data, future_climate_data
+from ..data_fixtures import full_data, train_data, train_data_pop, future_climate_data
 from climate_health.util import conda_available
 
 
@@ -35,7 +35,7 @@ def test_python_model_from_folder(models_path, train_data, future_climate_data):
     assert results is not None
 
 
-def get_dataset_from_yaml(yaml_path: Path):
+def get_dataset_from_yaml(yaml_path: Path, datatype=ClimateHealthTimeSeries):
     specs = yaml.load(yaml_path.read_text(), Loader=yaml.FullLoader)
     if 'demo_data' in specs:
         path = yaml_path.parent / specs['demo_data']
@@ -49,19 +49,20 @@ def get_dataset_from_yaml(yaml_path: Path):
                 df[to_name] = df[from_name]
     #df['disease_cases'] = np.arange(len(df))
 
-    return DataSet.from_pandas(df, ClimateHealthTimeSeries)
+    return DataSet.from_pandas(df, datatype)
+
 
 
 #@pytest.mark.skipif(not conda_available(), reason='requires conda')
 @pytest.mark.parametrize('model_directory', ['ewars_Plus'])
 #@pytest.mark.parametrize('model_directory', ['naive_python_model'])
-def test_all_external_models_acceptance(model_directory, models_path, train_data, future_climate_data):
+def test_all_external_models_acceptance(model_directory, models_path, train_data_pop, future_climate_data):
     """Only tests that the model can be initiated and that train and predict
     can be called without anything failing"""
     print("Running")
     yaml_path = models_path / model_directory / 'config.yml'
     model = get_model_from_yaml_file(yaml_path, working_dir=models_path / model_directory)
-    train_data = get_dataset_from_yaml(yaml_path)
+    train_data = get_dataset_from_yaml(yaml_path, FullData)
     model.setup()
     model.train(train_data)
     #results = model.predict(future_climate_data)
@@ -72,7 +73,7 @@ def test_all_external_models_acceptance(model_directory, models_path, train_data
 @pytest.mark.parametrize('model_directory', ['ewars_Plus'])
 def test_external_model_predict(model_directory, models_path):
     yaml_path = models_path / model_directory / 'config.yml'
-    train_data = get_dataset_from_yaml(yaml_path)
+    train_data = get_dataset_from_yaml(yaml_path, FullData)
     model = get_model_from_yaml_file(yaml_path, working_dir=models_path / model_directory)
     model.setup()
     #model.setup()