Merge Aquaveo master which includes V2 PR

[msouff]

Summary by CodeRabbit

• New Features
  • Introduced Flask application with CORS support and REST API endpoints.
  • Added Flask blueprints for handling routes related to pages and versioned API endpoints.
  • New templates for documentation, license, publications, and resources, including academic contributions.
  • Version 2 of REST endpoints with improved organization and functionality for forecasts and historical data retrieval.
  • Functionality for logging requests to CloudWatch Logs using AWS credentials.
• Bug Fixes
  • Corrected the project name casing across various templates and README for consistency.
• Documentation
  • Updated Swagger specification version and corrected project name casing in documentation.
• Chores
  • Updated .gitignore to exclude specific directories and files.
  • Modified CI/CD pipeline configurations for Helm checks and Docker builds.
  • Changed Dockerfile to use updated environment file name and command.
• Refactor
  • Restructured controllers for clarity and better organization in version 2 endpoints.
• Style
  • Updated titles, meta descriptions, and content across HTML templates for consistency and clarity.

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Commits

Files that changed from the base of the PR and between 23cde35 and 94a018d.

Walkthrough

This update enhances the project by refining configurations, improving the Flask application, and ensuring consistency in documentation. Key changes include the integration of new Flask blueprints for web pages and API endpoints, CI/CD pipeline optimizations, Dockerfile improvements, and standardization of the GEOGLOWS name across all materials. The update also introduces logging capabilities and better organization for managing forecast and historical data, resulting in a more robust and user-friendly application.

Changes

File(s)	Summary
.gitignore, .gitlab-ci.yml	Added exclusions, streamlined CI/CD with new includes, and updated variables.
Dockerfile	Updated conda environment and file references.
README.md, app/.../about.html, base_template.html, documentation.html, home.html, license.html, resources.html	Standardized naming and updated content for consistency.
app/app.py, app/blueprint_pages.py, app/v1/..., app/v2/...	Enhanced Flask app with new blueprints, API endpoints, and data handling.
app/templates/publications.html	Introduced a new template for academic publications.
check_helm_chart, docs/swagger_yml_to_html.py, supervisord.conf	Modified scripts and configurations for improved functionality and deployment.

🐰✨
In the world of code, where changes abide,
A rabbit hopped through, with eyes open wide.
"To improve, to enhance," was its cheerful song,
As it tweaked and it tuned, making the project strong.
With each line of code, and each commit pushed,
It left behind magic, in the dusk's gentle hush.
🌟🐾

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Review Status

Actionable comments generated: 10

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between 7452361 and 00546b1.

Files ignored due to path filters (45)

• app/geometry/1_simplified_region_boundary_geojsons.zip is excluded by: !**/*.zip
• app/geometry/africa-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/australia-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/boundaries.pickle is excluded by: !**/*.pickle
• app/geometry/central_america-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/central_asia-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/east_asia-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/europe-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/islands-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/japan-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/middle_east-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/north_america-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/region_coordinate_files/africa-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/australia-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/bounding_boxes.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/central_america-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/central_asia-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/east_asia-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/europe-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/global_coordinate_file.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/islands-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/japan-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/middle_east-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/north_america-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/south_america-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/south_asia-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/region_coordinate_files/west_asia-geoglows/comid_lat_lon_z.csv is excluded by: !**/*.csv
• app/geometry/south_america-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/south_asia-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/geometry/west_asia-geoglows-comid_lat_lon_z.pickle is excluded by: !**/*.pickle
• app/static/images/about1.jpg is excluded by: !**/*.jpg
• app/static/images/about2.jpg is excluded by: !**/*.jpg
• app/static/images/about3.jpg is excluded by: !**/*.jpg
• app/static/images/about4.jpg is excluded by: !**/*.jpg
• app/static/images/aquaveologo.png is excluded by: !**/*.png
• app/static/images/byulogo.png is excluded by: !**/*.png
• app/static/images/ecmwflogo.png is excluded by: !**/*.png
• app/static/images/favicon.ico is excluded by: !**/*.ico
• app/static/images/geoglowslogo.png is excluded by: !**/*.png
• assets/streamflow_animation.png is excluded by: !**/*.png
• demos/input_example.json is excluded by: !**/*.json
• docker-compose.yml is excluded by: !**/*.yml
• docs/swagger_doc.yaml is excluded by: !**/*.yaml
• environment.yaml is excluded by: !**/*.yaml
• helm/gsprestapi/Chart.yaml is excluded by: !**/*.yaml

Files selected for processing (33)

• .gitignore (1 hunks)
• .gitlab-ci.yml (5 hunks)
• Dockerfile (1 hunks)
• README.md (1 hunks)
• app/app.py (1 hunks)
• app/blueprint_pages.py (1 hunks)
• app/templates/about.html (3 hunks)
• app/templates/base_template.html (5 hunks)
• app/templates/documentation.html (2 hunks)
• app/templates/home.html (1 hunks)
• app/templates/license.html (3 hunks)
• app/templates/publications.html (1 hunks)
• app/templates/resources.html (2 hunks)
• app/v1/init.py (1 hunks)
• app/v1/analytics.py (1 hunks)
• app/v1/blueprint.py (1 hunks)
• app/v1/v1_controllers_forecasts.py (1 hunks)
• app/v1/v1_controllers_historical.py (1 hunks)
• app/v1/v1_functions.py (1 hunks)
• app/v1/v1_utilities.py (1 hunks)
• app/v2/init.py (1 hunks)
• app/v2/analytics.py (1 hunks)
• app/v2/blueprint.py (1 hunks)
• app/v2/constants.py (1 hunks)
• app/v2/controllers_forecasts.py (5 hunks)
• app/v2/controllers_historical.py (1 hunks)
• app/v2/controllers_misc.py (1 hunks)
• app/v2/data.py (1 hunks)
• app/v2/response_formatters.py (1 hunks)
• check_helm_chart (1 hunks)
• docs/index.html (2 hunks)
• docs/swagger_yml_to_html.py (1 hunks)
• supervisord.conf (1 hunks)

Files not summarized due to errors (1)

• docs/index.html: Error: Message exceeds token limit

Files skipped from review due to trivial changes (8)

• app/templates/about.html
• app/templates/base_template.html
• app/templates/home.html
• app/templates/resources.html
• app/v1/init.py
• app/v1/v1_functions.py
• app/v1/v1_utilities.py
• app/v2/init.py

Additional comments: 49

app/v2/constants.py (2)

• 3-3: The conversion factor from cubic meters to cubic feet is accurate.
• 4-4: Ensure NUM_DECIMALS is applied consistently across the application for numerical precision.

Verification successful

---

The usage of NUM_DECIMALS in app/v2/controllers_forecasts.py for rounding operations confirms that it is applied consistently across the application for numerical precision. This aligns with the intended use of ensuring numerical precision is maintained uniformly.

Scripts Executed

The following scripts were executed for the analysis:

---

Script:

#!/bin/bash
# Search for usage of NUM_DECIMALS across Python files to ensure consistent application.
rg "NUM_DECIMALS" --type py

Length of output: 736

supervisord.conf (1)

• 5-6: The updated uwsgi configuration points to a specific virtual environment, which is a common practice. Ensure the new configuration is tested and works as expected in the deployment environment.

app/app.py (1)

• 12-30: The Flask app configuration and blueprint registrations follow standard practices. Consider adding comments to explain the purpose of each major section (e.g., CORS setup, blueprint registrations) for better clarity and maintainability.

Dockerfile (1)

• 8-13: The updates to the conda environment creation command and the reference to environment.yaml are correct. Ensure the environment setup is tested and works as expected in the Docker container.

app/blueprint_pages.py (1)

• 1-53: The Flask blueprint setup, routes, and error handling in blueprint_pages.py follow standard practices. Consider adding comments to explain the purpose of each route and the custom 404 error handler for better clarity and maintainability.

check_helm_chart (1)

• 27-32: Consider enhancing the error handling by providing more detailed messages based on the HTTP status code returned by the server. This can help in diagnosing issues with chart uploads more effectively.

elif [ ${RESULT} -ne 200 ]; then
-    echo "Unknown error while trying to retrieve chart from remote" >&2
+    case ${RESULT} in
+    401)
+        echo "Unauthorized: Check if the ECCR_USER and ECCR_PASSWORD environment variables are correctly set." >&2
+        ;;
+    403)
+        echo "Forbidden: The user does not have permission to access the chart repository." >&2
+        ;;
+    500)
+        echo "Internal Server Error: There might be a problem with the chart repository server." >&2
+        ;;
+    *)
+        echo "An unexpected error occurred while trying to retrieve the chart from remote. HTTP status code: ${RESULT}" >&2
+        ;;
+    esac
     exit -2
fi

app/v2/response_formatters.py (3)

• 10-14: The implementation of df_to_csv_flask_response is correct and follows best practices for generating CSV responses in Flask.
• 17-25: The df_to_jsonify_response function correctly formats DataFrame data into a JSON response. Consider explicitly documenting the choice to replace NaN values with empty strings, as this might impact consumers of the API depending on the context.
• 28-42: The new_json_template function is well-implemented, providing a clear and reusable structure for JSON responses.

app/v1/analytics.py (1)

• 23-28: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-44]

The log_request function correctly logs requests to AWS CloudWatch. Consider adding error handling for the AWS CloudWatch logging operation to gracefully handle potential issues with logging, such as network errors or misconfigurations.

.gitignore (1)

• 185-190: The updates to .gitignore are appropriate and follow best practices for excluding editor configurations and sensitive configuration files from the repository.

docs/swagger_yml_to_html.py (1)

• 21-21: The update to the title block in the HTML template aligns with the naming consistency objective of the PR.

app/v2/data.py (2)

• 47-54: The get_return_periods_dataframe function is well-implemented, correctly retrieving and processing return period data from an S3 bucket.
• 57-61: The find_available_dates function correctly identifies available forecast dates using file listing and sorting. Good use of glob and natsort.

.gitlab-ci.yml (3)

• 5-11: The inclusion of helm-check.yml and kaniko-build.yml enhances the CI/CD pipeline by integrating additional checks and builds. This aligns with best practices for CI/CD pipeline configuration.
• 17-34: The updates to variables for the Helm stages are appropriate and improve the clarity and maintainability of the CI/CD pipeline configuration.
• 52-57: The before_script configuration for Docker authentication in the Build Tag stage is a good security practice. Verify that the Docker authentication works as expected in the CI/CD environment.

app/templates/license.html (2)

• 2-2: Ensure the updated title aligns with the project's naming conventions and accurately reflects the content of the page.
• 25-63: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [28-80]

The update to the data license and the addition of a disclaimer are significant improvements. It's important to verify that the Creative Commons license chosen (CC BY 4.0) is appropriate for the data being shared and that the disclaimer is clear and understandable to users.

app/v2/controllers_historical.py (5)

• 16-27: The function _get_retrospective_df efficiently retrieves retrospective data from an S3 bucket using xarray and pandas. Ensure that error handling is in place for potential issues with data access or transformation.
• 51-63: The daily_averages function demonstrates good use of pandas for data manipulation. Ensure consistency in date formatting across all functions for clarity and usability.
• 66-77: In the monthly_averages function, consider adding comments to explain the logic, especially for the grouping and averaging process, to improve maintainability.
• 80-91: The yearly_averages function is concise and follows similar patterns as other functions. Verify that the date range handling meets the application's requirements.
• 94-110: The return_periods function introduces a new response format. Ensure that the response structure is documented and consistent with other API endpoints.

app/templates/publications.html (2)

• 2-2: The updated title accurately reflects the content of the page and aligns with the project's naming conventions.
• 13-83: The addition of publications is a valuable update for users interested in the research behind the GEOGLOWS ECMWF Streamflow Model. Ensure that all publication links are valid and accessible.

app/v1/v1_controllers_historical.py (3)

• 9-9: The use of jsonify and make_response from Flask is appropriate for generating responses. Ensure that all responses are consistent in format across the API.
• 11-12: The relative imports for constants and functions are correctly updated to maintain modularity and ease of maintenance.
• 6-15: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-228]

Overall, the changes in app/v1/v1_controllers_historical.py improve the organization and readability of the code. Ensure that error handling and input validation are consistently applied across all functions to enhance robustness and security.

+ # Add input validation and error handling where necessary

app/v2/blueprint.py (3)

• 25-25: The creation of the Flask blueprint for version 2 endpoints is correctly implemented. Ensure that the blueprint name is unique and descriptive.
• 83-173: The handle_request function effectively parses and validates request parameters. Consider adding more detailed error messages to help users correct their requests.
• 176-185: Error handling for ValueError and general exceptions is a good practice. Ensure that logging is appropriately configured to capture sufficient details for debugging.

app/v2/controllers_forecasts.py (7)

• 10-17: The updated import statements and the use of relative imports improve modularity and maintainability. Ensure that all necessary modules are imported and unused imports are removed.
• 23-39: The hydroviewer function integrates multiple data sources to provide a comprehensive response. Ensure that the data integration logic is accurate and that the response format meets the API's standards.
• 58-140: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [51-82]

The forecast function demonstrates efficient data manipulation using numpy and pandas. Consider adding error handling for potential issues with data access or transformation.

• 87-118: The forecast_stats function correctly calculates various statistical measures. Verify that the percentile calculations are appropriate for the application's requirements.
• 58-140: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [123-166]

In the forecast_ensembles function, the handling of ensemble filtering is well-implemented. Ensure that the ensemble parameter is validated to prevent errors.

+ # Validate ensemble parameter

• 188-228: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [172-206]

The forecast_records function retrieves historical forecast records. Ensure that the date range validation is robust and that error messages are clear for users.

• 212-227: The forecast_dates function provides a list of available forecast dates. Consider adding caching to improve performance if the available dates do not change frequently.

app/v1/v1_controllers_forecasts.py (6)

• 9-10: The update to relative imports for constants and v1_functions is a good practice for module organization and helps avoid import errors in a package structure.
• 5-13: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [12-93]

The forecast_stats function integrates well with the changes to relative imports and adheres to best practices in handling parameters, units, and file paths.

• 5-13: > 📝 NOTE

This review was outside the diff hunks, and no overlapping diff hunk was found. Original lines [95-169]

The forecast_ensembles function correctly uses the updated relative imports and follows best practices in its implementation.

• 5-13: > 📝 NOTE

This review was outside the diff hunks, and no overlapping diff hunk was found. Original lines [171-234]

The forecast_warnings function correctly uses the updated relative imports and adheres to best practices in handling different scenarios for regions and forecast dates.

• 5-13: > 📝 NOTE

This review was outside the diff hunks, and no overlapping diff hunk was found. Original lines [236-287]

The forecast_records function integrates well with the changes to relative imports and adheres to best practices in handling parameters, units, and file paths.

• 5-13: > 📝 NOTE

This review was outside the diff hunks, and no overlapping diff hunk was found. Original lines [289-307]

The available_dates function correctly uses the updated relative imports and follows best practices in its implementation.

app/templates/documentation.html (2)

• 2-2: The update to the title casing to "GEOGLOWS" aligns with the PR's objective to standardize the project name's casing.
• 11-11: The update of the version number in the Swagger specification to "1.5.0" likely reflects the introduction of new features or significant updates in the API.

docs/index.html (1)

• 11-11: The JavaScript code for removing the Swagger UI top bar is effective but consider the maintainability of this approach. Future updates to Swagger UI might change class names or the structure, requiring updates to this script. Documenting this customization or exploring alternative, more maintainable approaches could be beneficial.

[coderabbitai]

The Swagger specification is using version 2.0. Consider upgrading to OpenAPI 3.0 for enhanced features and improved support for API documentation. Additionally, ensure that the inclusion of both HTTP and HTTPS schemes is intentional and that appropriate security measures are in place for HTTP connections.

[coderabbitai]

Hardcoded paths to forecasts and forecast records may limit flexibility in different deployment environments. Consider making these paths configurable through environment variables.

[coderabbitai]

Hardcoded S3 bucket URI and region may expose sensitive information and limit flexibility. Consider making these details configurable through environment variables.

[coderabbitai]

The get_reach_id function lacks input validation for lat and lon parameters. Consider adding checks to ensure they are within valid ranges for latitude (-90 to 90) and longitude (-180 to 180).

[coderabbitai]

The log_request function lacks error handling for potential failures in logging to CloudWatch Logs. Consider adding try-except blocks to gracefully handle exceptions and ensure the application's stability.

[coderabbitai]

The Flask Blueprint and routes for version 1 REST endpoints are correctly defined. Consider enhancing the error handling for unsupported products by providing more detailed information or suggestions for valid products. This can improve the API's usability and help consumers in diagnosing issues.

[coderabbitai]

The get_forecast_dataset function correctly retrieves forecast data. Consider adding more detailed error messages for cases where the data is not found or there's an error reading the zarr files. This can help in diagnosing issues more effectively.

[coderabbitai]

Tip

Codebase Verification

The geographic properties table is not accessible at the specified path (/mnt/configs/geoglows-v2-geographic-properties-table.parquet). This could potentially affect the functionality of the latlon_to_reach function, which relies on this table. It's important to ensure that the path is correct and accessible in the deployment environment.

Analysis chain

The latlon_to_reach function correctly finds the nearest reach ID to a given latitude and longitude. Verify that the path to the geographic properties table (/mnt/configs/geoglows-v2-geographic-properties-table.parquet) is accessible and correct in the deployment environment.

Scripts Executed

The following scripts were executed for the analysis:

---

Script:

#!/bin/bash
# Verify the accessibility of the geographic properties table
if [ -f "/mnt/configs/geoglows-v2-geographic-properties-table.parquet" ]; then
    echo "Geographic properties table is accessible."
else
    echo "Geographic properties table is not accessible. Check the path."
fi

Length of output: 208

[coderabbitai]

The retrospective function correctly handles unit conversion and date filtering. Consider adding input validation for units and return_format to ensure they match expected values.

+ # Validate units and return_format
+ if units not in ['cfs', 'cms']:
+     raise ValueError("Invalid units. Expected 'cfs' or 'cms'.")
+ if return_format not in ['csv', 'json']:
+     raise ValueError("Invalid return_format. Expected 'csv' or 'json'.")

---

Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change

	def retrospective(reach_id: int, units: str, return_format: str, start_date: str = None,
	end_date: str = None) -> pd.DataFrame:
	"""
	Controller for retrieving simulated historic data
	"""
	df = _get_retrospective_df(reach_id)
	if units == 'cfs':
	df *= M3_TO_FT3
	if start_date is not None:
	df = df.loc[df.index >= datetime.datetime.strptime(start_date, '%Y%m%d')]
	if end_date is not None:
	df = df.loc[df.index <= datetime.datetime.strptime(end_date, '%Y%m%d')]
	if return_format == 'csv':
	return df_to_csv_flask_response(df, f'retrospective_{reach_id}_{units}')
	if return_format == 'json':
	return df_to_jsonify_response(df=df, reach_id=reach_id, units=units)
	return df
	def retrospective(reach_id: int, units: str, return_format: str, start_date: str = None,
	end_date: str = None) -> pd.DataFrame:
	"""
	Controller for retrieving simulated historic data
	"""
	# Validate units and return_format
	if units not in ['cfs', 'cms']:
	raise ValueError("Invalid units. Expected 'cfs' or 'cms'.")
	if return_format not in ['csv', 'json']:
	raise ValueError("Invalid return_format. Expected 'csv' or 'json'.")
	df = _get_retrospective_df(reach_id)
	if units == 'cfs':
	df *= M3_TO_FT3
	if start_date is not None:
	df = df.loc[df.index >= datetime.datetime.strptime(start_date, '%Y%m%d')]
	if end_date is not None:
	df = df.loc[df.index <= datetime.datetime.strptime(end_date, '%Y%m%d')]
	if return_format == 'csv':
	return df_to_csv_flask_response(df, f'retrospective_{reach_id}_{units}')
	if return_format == 'json':
	return df_to_jsonify_response(df=df, reach_id=reach_id, units=units)
	return df

[coderabbitai]

The route definitions are comprehensive and cover a wide range of data products. Verify that all routes are documented and that their parameters are validated to prevent injection attacks or unexpected errors.

+ # Add parameter validation for all routes

---

Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change

	@app.route(f'/api/latest/<product>/', methods=['GET'])
	@app.route(f'/api/latest/<product>/<reach_id>', methods=['GET'])
	@app.route(f'/api/v2/<product>/', methods=['GET'])
	@app.route(f'/api/v2/<product>/<reach_id>', methods=['GET'])
	@cross_origin()
	def rest_endpoints_v2(product: str, reach_id: int = None):
	product, reach_id, format, units, date, ensemble, start_date, end_date = handle_request(
	request,
	product,
	reach_id,
	)
	log_request(version="v2",
	product=product,
	reach_id=request.args.get('reach_id', 0),
	return_format=format,
	source=request.args.get('source', 'other'), )
	# forecast data products
	if product == 'forecast':
	return forecast(reach_id, date, units, format)
	elif product in 'forecaststats':
	return forecast_stats(reach_id, date, units, format)
	elif product == 'forecastensembles':
	return forecast_ensembles(reach_id, date, units, format, ensemble)
	elif product == 'forecastrecords':
	return forecast_records(reach_id, start_date, end_date, units, format)
	elif product == 'forecastwarnings':
	return forecast_warnings(date, format)
	elif product == 'dates':
	return forecast_dates(return_format=format)
	# hindcast data products
	elif product == 'retrospective':
	return retrospective(reach_id, units, format)
	elif product == 'returnperiods':
	return return_periods(reach_id, units, format)
	elif product == 'dailyaverages':
	return daily_averages(reach_id, units, format)
	elif product == 'monthlyaverages':
	return monthly_averages(reach_id, units, format)
	elif product == 'annualaverages':
	return yearly_averages(reach_id, units, format)
	# data availability
	elif product == 'getreachid':
	return get_reach_id(request, format=format)
	elif product == "hydroviewer":
	return hydroviewer(reach_id, start_date, date, units, format)
	else:
	return jsonify({'error': f'data product "{product}" not available'}), 201
	@app.route(f'/api/latest/<product>/', methods=['GET'])
	@app.route(f'/api/latest/<product>/<reach_id>', methods=['GET'])
	@app.route(f'/api/v2/<product>/', methods=['GET'])
	@app.route(f'/api/v2/<product>/<reach_id>', methods=['GET'])
	@cross_origin()
	def rest_endpoints_v2(product: str, reach_id: int = None):
	# Add parameter validation for all routes
	product, reach_id, format, units, date, ensemble, start_date, end_date = handle_request(
	request,
	product,
	reach_id,
	)
	log_request(version="v2",
	product=product,
	reach_id=request.args.get('reach_id', 0),
	return_format=format,
	source=request.args.get('source', 'other'), )
	# forecast data products
	if product == 'forecast':
	return forecast(reach_id, date, units, format)
	elif product in 'forecaststats':
	return forecast_stats(reach_id, date, units, format)
	elif product == 'forecastensembles':
	return forecast_ensembles(reach_id, date, units, format, ensemble)
	elif product == 'forecastrecords':
	return forecast_records(reach_id, start_date, end_date, units, format)
	elif product == 'forecastwarnings':
	return forecast_warnings(date, format)
	elif product == 'dates':
	return forecast_dates(return_format=format)
	# hindcast data products
	elif product == 'retrospective':
	return retrospective(reach_id, units, format)
	elif product == 'returnperiods':
	return return_periods(reach_id, units, format)
	elif product == 'dailyaverages':
	return daily_averages(reach_id, units, format)
	elif product == 'monthlyaverages':
	return monthly_averages(reach_id, units, format)
	elif product == 'annualaverages':
	return yearly_averages(reach_id, units, format)
	# data availability
	elif product == 'getreachid':
	return get_reach_id(request, format=format)
	elif product == "hydroviewer":
	return hydroviewer(reach_id, start_date, date, units, format)
	else:
	return jsonify({'error': f'data product "{product}" not available'}), 201

[coderabbitai]

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Actionable comments generated: 0

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Commits

Files that changed from the base of the PR and between 00546b1 and f6a7923.

Files selected for processing (3)

• app/v2/constants.py (1 hunks)
• app/v2/controllers_historical.py (1 hunks)
• app/v2/data.py (1 hunks)

Files skipped from review as they are similar to previous changes (3)

• app/v2/constants.py
• app/v2/controllers_historical.py
• app/v2/data.py

[coderabbitai]

Review Status

Actionable comments generated: 0

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Commits

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Files selected for processing (2)

• app/v2/controllers_historical.py (1 hunks)
• app/v2/response_formatters.py (1 hunks)

Files skipped from review as they are similar to previous changes (2)

• app/v2/controllers_historical.py
• app/v2/response_formatters.py

[coderabbitai]

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Actionable comments generated: 0

Configuration used: CodeRabbit UI

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Files that changed from the base of the PR and between e32ab3d and 23cde35.

Files ignored due to path filters (1)

• docs/swagger_doc.yaml is excluded by: !**/*.yaml

Files selected for processing (1)

• README.md (1 hunks)

Additional comments: 2

README.md (2)

• 1-1: The project name casing correction from "GEOGloWS" to "GEOGLOWS" is accurate and aligns with the PR objectives for standardization.
• 3-3: While the static analysis tool flagged potential spelling mistakes and a missing article, these are largely false positives due to the technical nature of the content. However, it's always beneficial to have another set of eyes review technical documentation for clarity and correctness.