How googlecloudplatform/training-data-analyst works
This repository is a collection of Google Cloud training and blog examples, not one integrated application. The sampled runtime workflows include running batch or streaming TensorFlow inference, processing radar archives into detections, and streaming traffic records into BigQuery. The graph keeps those examples separate and includes the vendored Flask/OAuth/Werkzeug runtime represented by the source index. Evidence is partial: unsampled implementations and the broader collection’s workflows are not inferred.
Main entry points: run_pipeline.py Inference runner · APPipeline.java Radar pipeline · streaming_minute_traffic_pipeline.py Traffic pipeline · json.py Flask JSON
Components 21
ML Serving
- Inference runner
blogs/tf_dataflow_serving/run_pipeline.py - Batch inference
blogs/tf_dataflow_serving/pipelines - Stream inference
blogs/tf_dataflow_serving/pipelines - Beam execution
blogs/tf_dataflow_serving/run_pipeline.py
Radar Processing
- Radar pipeline
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/APPipeline.java - Archive listing
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/GcsNexradL2List.java - Archive reading
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/GcsNexradL2Read.java - AP detection
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/APDetector.java
Traffic Analytics
- Traffic pipeline
quests/dataflow_python/5_Streaming_Analytics/solution/streaming_minute_traffic_pipeline.py
Web Runtime
- Flask framework
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask - Flask JSON
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/json.py - Flask logging
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/logging.py - Werkzeug utilities
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/werkzeug - HTTP utilities
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/werkzeug/http.py - WSGI server
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/werkzeug/serving.py - OAuth client
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/oauth2client/client.py - OAuth helpers
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/oauth2client/_helpers.py - Service account
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/oauth2client/service_account.py
Other components
- Pipeline operator
- Pub/Sub
- BigQuery
Connections 14
- Pipeline operator → Inference runner: runs
blogs/tf_dataflow_serving/run_pipeline.py - Inference runner → Batch inference: dispatches batch
blogs/tf_dataflow_serving/run_pipeline.py - Inference runner → Stream inference: dispatches stream
blogs/tf_dataflow_serving/run_pipeline.py - Inference runner → Beam execution: configures job
blogs/tf_dataflow_serving/run_pipeline.py - Radar pipeline → Archive listing: references
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/APPipeline.java - Radar pipeline → Archive reading: references
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/APPipeline.java - Radar pipeline → AP detection: references
blogs/nexrad2/src/com/google/cloud/public_datasets/nexrad2/APPipeline.java - Traffic pipeline → Pub/Sub: reads messages
quests/dataflow_python/5_Streaming_Analytics/solution/streaming_minute_traffic_pipeline.py - Traffic pipeline → BigQuery: writes rows
quests/dataflow_python/5_Streaming_Analytics/solution/streaming_minute_traffic_pipeline.py - Flask JSON → Flask framework: uses context
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/json.py - Flask logging → Flask framework: uses request context
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/logging.py - Flask JSON → HTTP utilities: uses HTTP helpers
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/json.py - Flask logging → Werkzeug utilities: uses local proxy
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/flask/logging.py - OAuth client → OAuth helpers: uses helpers
courses/machine_learning/deepdive2/structured/labs/serving/application/lib/oauth2client/client.py