V2 #21
V2 #21
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Helm docker update See merge request geoglows/gsp_rest_api!4
build commit only on merge to master See merge request geoglows/gsp_rest_api!5
reversed ci triggers See merge request geoglows/gsp_rest_api!6
This reverts commit c71f3b1.
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Review Status
Actionable comments generated: 2
Configuration used: CodeRabbit UI
Files ignored due to path filters (1)
helm/gsprestapi/Chart.yamlis excluded by:!**/*.yaml
Files selected for processing (9)
- .gitignore (1 hunks)
- .gitlab-ci.yml (5 hunks)
- app/templates/base_template.html (5 hunks)
- app/templates/documentation.html (2 hunks)
- app/templates/license.html (3 hunks)
- app/v2/controllers_forecasts.py (5 hunks)
- app/v2/data.py (1 hunks)
- app/v2/utilities.py (8 hunks)
- check_helm_chart (1 hunks)
Files skipped from review as they are similar to previous changes (4)
- app/templates/base_template.html
- app/templates/documentation.html
- app/templates/license.html
- app/v2/data.py
Additional comments: 7
.gitignore (1)
- 185-190: The updates to
.gitignoreare beneficial for both security and developer experience:
- Excluding
.vscode/prevents the accidental inclusion of personal editor settings.- Including
/aws_config.jsonis crucial for avoiding the accidental commit of AWS credentials.Ensure these exclusions are consistently applied across all relevant branches and consider reviewing other potential sensitive files that should be excluded.
.gitlab-ci.yml (1)
- 5-12: The inclusion of external files for Helm checks and Kaniko builds enhances the modularity of the CI/CD pipeline. Ensure that the referenced external files (
/helm-check.ymland/kaniko-build.yml) are up-to-date and align with the project's current deployment requirements.app/v2/utilities.py (3)
- 1-18: The updates to imports and the shift towards using relative imports enhance the modularity and maintainability of the code. It's good practice to ensure that all new imports are used effectively and that the relative paths align with the project's directory structure.
- 13-39: The modifications to the
ALL_PRODUCTSdictionary and the introduction of new product types are significant for extending the functionality of the API. Ensure that these changes are well-documented and that any new product types are fully supported across the application.Verification successful
Given the grep output, it's evident that the
ALL_PRODUCTSdictionary is used for validation and error handling inapp/v2/blueprint.pyandapp/v2/utilities.py. However, this does not confirm the full support for the new product types in terms of functionality across the application. To further verify, we should look for specific instances where the new product types are handled or processed, which could involve searching for the usage of individual product names or mechanisms that dynamically handle products based on their presence in theALL_PRODUCTSdictionary.
The extensive search across the application's codebase for the usage of the new product types introduced in the
ALL_PRODUCTSdictionary reveals that these product types are indeed referenced and utilized in various parts of the application. The search results show that the product types such asforecast,forecaststats,forecastensembles,forecastrecords,forecastanomalies,forecastwarnings,hindcast,monthlyaverages,dailyaverages,returnperiods, andhydroviewerare mentioned in multiple files, including documentation (docs/index.html,docs/swagger_doc.yaml), JavaScript files (app/static/js/geoglows_esri_map.js), and Python files within both version 1 and version 2 of the application (app/v1/*,app/v2/*).These references are found in various contexts, including API endpoint definitions, data processing functions, and user interface components, indicating that the new product types are integrated into the application's functionality. The presence of these product types in the Swagger documentation (
docs/swagger_doc.yaml) and their handling in the application's backend (app/v1/*,app/v2/*) suggest that these product types are supported and exposed through the application's API, allowing users to interact with them.Given the evidence from the codebase, it can be concluded that the new product types introduced in the
ALL_PRODUCTSdictionary are indeed supported across the application, as they are referenced and utilized in multiple components of the application, including API endpoints, data processing functions, and user interface elements.* 49-86: > 📝 **NOTE** > This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [57-253]Scripts Executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify that new product types introduced in the ALL_PRODUCTS dictionary are supported across the application. grep -r "ALL_PRODUCTS" .Length of output: 535
Script:
#!/bin/bash # Search for instances where new product types are specifically handled or processed. grep -r "getreachid\|dates\|forecast\|forecaststats\|forecastensembles\|forecastrecords\|forecastanomalies\|forecastwarnings\|hindcast\|monthlyaverages\|dailyaverages\|returnperiods\|hydroviewer" .Length of output: 84105
Several functions have been updated or added, including
handle_request,get_forecast_dataset, anddataframe_to_csv_flask_response, among others. These changes aim to improve the handling of different product types, date formats, and file paths. However, there are placeholder comments indicating incomplete features. It's crucial to track these TODOs outside of the codebase to ensure they are addressed.Would you like me to open a GitHub issue to track the implementation of the commented functionality in these functions?
app/v2/controllers_forecasts.py (2)
- 10-18: The refactoring of import statements to use relative imports and the organization of the code into more readable and maintainable structures are commendable improvements. Ensure that all updated imports are correctly resolved and that the new structure aligns with the overall architecture of the application.
- 58-140: > 📝 NOTE
This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [24-228]
The restructuring and refactoring of functions such as
forecast,forecast_stats,forecast_ensembles, and others enhance the code's clarity and consistency. It's important to thoroughly test these changes to ensure they maintain the expected functionality and do not introduce regressions.
| RESULT=$(curl ${HELM_REPO_URL}/${HELM_REPO_CHANNEL}/charts/${LOCAL_PACKAGE} -so ${REMOTE_PACKAGE} -u ${ECCR_USER}:${ECCR_PASSWORD} -w '%{http_code}\n') | ||
| if [ ${RESULT} -eq 404 ]; then | ||
| echo "Chart not found on remote" >&2 | ||
| if [[ "$2" == "--upload" ]]; then | ||
| helm package ${CHARTDIR} --sign --key 'Aquaveo Chart Signing Key' --keyring ~/.gnupg/secring.gpg | ||
| echo "Uploading chart..." | ||
| curl -F "chart=@${LOCAL_PACKAGE}" -F "prov=@${LOCAL_PACKAGE}.prov" https://eccr.ecmwf.int/api/chartrepo/geoglows_api/charts -u ${ECCR_USER}:${ECCR_PASSWORD} | ||
| curl -F "chart=@${LOCAL_PACKAGE}" ${HELM_REPO_URL}/${HELM_REPO_CHANNEL}/charts -u ${ECCR_USER}:${ECCR_PASSWORD} |
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The script now dynamically interacts with a Helm repository using environment variables for the URL and channel. This is a positive change for flexibility. However, consider the following points:
- Security: The script uses basic authentication with
curl. Ensure that the environment variablesECCR_USERandECCR_PASSWORDare securely managed. - Error Handling: The script exits with a
-2code for any non-200 and non-404 HTTP response. It might be beneficial to log or handle different classes of HTTP errors more granularly. - Readability and Maintainability: The script is straightforward, but as it grows, consider structuring it into functions or adding comments for clarity.
| before_script: | ||
| - > | ||
| echo "{\"auths\":{ | ||
| \"$CI_REGISTRY\": {\"username\":\"$CI_REGISTRY_USER\", \"password\":\"$CI_REGISTRY_PASSWORD\"}, | ||
| \"eccr.ecmwf.int/harbor\": {\"username\":\"$ECCR_USER\", \"password\":\"$ECCR_PASSWORD\"} | ||
| }}" > /kaniko/.docker/config.json |
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The before_script section for Docker authentication is crucial for security. Ensure that the credentials used ($CI_REGISTRY_USER, $CI_REGISTRY_PASSWORD, $ECCR_USER, $ECCR_PASSWORD) are securely managed and not exposed in logs or other insecure channels.
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Review Status
Actionable comments generated: 0
Configuration used: CodeRabbit UI
Files selected for processing (2)
- app/templates/documentation.html (1 hunks)
- app/v2/data.py (1 hunks)
Files skipped from review as they are similar to previous changes (2)
- app/templates/documentation.html
- app/v2/data.py
There was a problem hiding this comment.
Review Status
Actionable comments generated: 0
Configuration used: CodeRabbit UI
Files selected for processing (2)
- app/templates/documentation.html (2 hunks)
- app/templates/license.html (3 hunks)
Files skipped from review as they are similar to previous changes (2)
- app/templates/documentation.html
- app/templates/license.html
There was a problem hiding this comment.
Review Status
Actionable comments generated: 0
Configuration used: CodeRabbit UI
Files selected for processing (2)
- app/v2/constants.py (1 hunks)
- app/v2/controllers_historical.py (1 hunks)
Additional comments: 2
app/v2/constants.py (1)
- 6-8: Consider externalizing sensitive or environment-specific information, such as
ODP_S3_BUCKET_CORE_URI,ODP_S3_BUCKET_RETROSPECTIVE, andODP_S3_BUCKET_REGION, to environment variables or a configuration file. This approach enhances security and flexibility, allowing for easier adjustments without code changes.app/v2/controllers_historical.py (1)
- 30-48: Ensure that all external data sources (e.g., S3 buckets) are accessible and that the data is correctly formatted for the expected use cases. Additionally, consider adding more detailed error handling for cases where data retrieval fails or the requested data is not available.
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Replaced by #22 |
Summary by CodeRabbit
.gitignore, Dockerfile, and supervisord configuration for better development and deployment practices.