Repository Analysis

DataTalksClub/data-engineering-zoomcamp

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

11.1 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of DataTalksClub/data-engineering-zoomcamp, a Jupyter Notebook project with 43,555 GitHub stars. SynthScan v2.0 examined 31,936 lines of code across 316 source files, recording 177 pattern matches distributed across 14 syntactic categories. The overall adjusted score of 11.1 places this repository in the Low AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

11.1
Adjusted Score
11.1
Raw Score
100%
Time Factor
2026-06-10
Last Push
43.6K
Stars
Jupyter Notebook
Language
31.9K
Lines of Code
316
Files
177
Pattern Hits
2026-07-14
Scan Date
0.08
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 24MEDIUM 27LOW 126

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 177 distinct pattern matches across 14 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Cross-File Repetition23 hits · 115 pts
SeverityFileLineSnippetContext
HIGH…s/2023/week_6_stream_processing/streaming_confluent.py0take a spark streaming df and parse value col based on <schema>, return streaming df cols in schemaSTRING
HIGH…ing/extras/python/streams-example/pyspark/streaming.py0take a spark streaming df and parse value col based on <schema>, return streaming df cols in schemaSTRING
HIGH…ng/extras/python/streams-example/redpanda/streaming.py0take a spark streaming df and parse value col based on <schema>, return streaming df cols in schemaSTRING
HIGH07-streaming/workshop/README.md0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/live/src/job/pass_through_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/src/job/pass_through_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/README.md0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, pickuSTRING
HIGH07-streaming/workshop/live/src/job/pass_through_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, pickuSTRING
HIGH07-streaming/workshop/src/job/pass_through_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, pickuSTRING
HIGH07-streaming/workshop/README.md0insert into {postgres_sink} select pulocationid, dolocationid, trip_distance, total_amount, to_timestamp_ltz(tpep_pickupSTRING
HIGH07-streaming/workshop/live/src/job/pass_through_job.py0insert into {postgres_sink} select pulocationid, dolocationid, trip_distance, total_amount, to_timestamp_ltz(tpep_pickupSTRING
HIGH07-streaming/workshop/src/job/pass_through_job.py0insert into {postgres_sink} select pulocationid, dolocationid, trip_distance, total_amount, to_timestamp_ltz(tpep_pickupSTRING
HIGH07-streaming/workshop/README.md0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/live/src/job/aggregation_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/src/job/aggregation_job.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/src/job/aggregation_job_demo.py0create table {table_name} ( pulocationid integer, dolocationid integer, trip_distance double, total_amount double, tpep_STRING
HIGH07-streaming/workshop/README.md0create table {table_name} ( window_start timestamp(3), pulocationid int, num_trips bigint, total_revenue double, primarySTRING
HIGH07-streaming/workshop/live/src/job/aggregation_job.py0create table {table_name} ( window_start timestamp(3), pulocationid int, num_trips bigint, total_revenue double, primarySTRING
HIGH07-streaming/workshop/src/job/aggregation_job.py0create table {table_name} ( window_start timestamp(3), pulocationid int, num_trips bigint, total_revenue double, primarySTRING
HIGH07-streaming/workshop/src/job/aggregation_job_demo.py0create table {table_name} ( window_start timestamp(3), pulocationid int, num_trips bigint, total_revenue double, primarySTRING
HIGH07-streaming/workshop/README.md0insert into {aggregated_table} select window_start, pulocationid, count(*) as num_trips, sum(total_amount) as total_reveSTRING
HIGH07-streaming/workshop/live/src/job/aggregation_job.py0insert into {aggregated_table} select window_start, pulocationid, count(*) as num_trips, sum(total_amount) as total_reveSTRING
HIGH07-streaming/workshop/src/job/aggregation_job.py0insert into {aggregated_table} select window_start, pulocationid, count(*) as num_trips, sum(total_amount) as total_reveSTRING
Structural Annotation Overuse39 hits · 65 pts
SeverityFileLineSnippetContext
LOW04-analytics-engineering/setup/local_setup.md22## Step 1: Install DuckDBCOMMENT
LOW04-analytics-engineering/setup/local_setup.md29## Step 2: Install dbtCOMMENT
LOW04-analytics-engineering/setup/local_setup.md40## Step 3: Configure dbt ProfileCOMMENT
LOW04-analytics-engineering/setup/local_setup.md82## Step 4: Download and Ingest DataCOMMENT
LOW04-analytics-engineering/setup/local_setup.md161## Step 5: Test the dbt ConnectionSTRING
LOW04-analytics-engineering/setup/local_setup.md169## Step 6: Install dbt Power User Extension (VS Code Users)STRING
LOW…-analytics-engineering/setup/duckdb_troubleshooting.md52### Step 1: Adjust DuckDB memory settings in `profiles.yml`COMMENT
LOW…-analytics-engineering/setup/duckdb_troubleshooting.md60### Step 2: Use `dbt retry` after a failureCOMMENT
LOW…-analytics-engineering/setup/duckdb_troubleshooting.md70### Step 3: Build models selectively with `--select`COMMENT
LOW…-analytics-engineering/setup/duckdb_troubleshooting.md84### Step 4: Leverage incremental modelsCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md20## Step 1: Verify Your BigQuery SetupCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md108## Step 2: Sign Up for dbt PlatformCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md112## Step 3: Create a New dbt ProjectCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md123## Step 4: Configure BigQuery ConnectionCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md170## Step 5: Set Up Your RepositoryCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md179## Step 6: Verify Your Development EnvironmentCOMMENT
LOW04-analytics-engineering/setup/cloud_setup.md219## Step 7: Start DevelopingCOMMENT
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…2022/week_2_data_ingestion/airflow/docker-compose.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…eek_2_data_ingestion/airflow/docker-compose_2.3.4.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py82 # Step 1: Consume GREEN_TAXI_TOPIC and FHV_TAXI_TOPICCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py86 # Step 2: Publish green and fhv rides to RIDES_TOPICCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py90 # Step 3: Read RIDES_TOPIC and parse it in ALL_RIDE_SCHEMACOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py94 # Step 4: Apply Aggregation on the all_ridesCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py98 # Step 5: Sink Aggregation Streams to ConsoleCOMMENT
LOWcohorts/2026/workshops/dlt/README.md69### Step 1: Create a New Project FolderCOMMENT
LOWcohorts/2026/workshops/dlt/README.md78### Step 2: Add the dlt MCP Server ConfigCOMMENT
LOWcohorts/2026/workshops/dlt/README.md134### Step 3: Install dlt WorkspaceCOMMENT
LOWcohorts/2026/workshops/dlt/README.md140### Step 4: Initialize the dlt ProjectCOMMENT
LOWcohorts/2026/workshops/dlt/README.md150### Step 5: Prompt the Agent to Build and Run the PipelineCOMMENT
LOWcohorts/2026/workshops/dlt/README.md171### Step 6: Debug with the AgentCOMMENT
LOWcohorts/2026/workshops/dlt/README.md175### Step 7: Inspect Pipeline Data with the dlt DashboardCOMMENT
LOWcohorts/2026/workshops/dlt/README.md191### Step 8: Inspect the Pipeline via ChatCOMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md30### Step 1: Create a New Project (or Reuse Your Demo Project)COMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md41### Step 2: Set Up the dlt MCP Server (If Not Already Done)COMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md97### Step 3: Install dltCOMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md103### Step 4: Initialize the ProjectCOMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md115### Step 5: Prompt the AgentCOMMENT
LOWcohorts/2026/workshops/dlt/dlt_homework.md133### Step 6: Run and DebugCOMMENT
Modern AI Meta-Vocabulary14 hits · 44 pts
SeverityFileLineSnippetContext
MEDIUMREADME.md94### [Module 2: Workflow Orchestration](02-workflow-orchestration/)COMMENT
MEDIUMawesome-data-engineering.md53### Workflow orchestrationCOMMENT
MEDIUM02-workflow-orchestration/README.md14- [2.1 - Introduction to Workflow Orchestration](#21-introduction-to-workflow-orchestration)CODE
MEDIUM02-workflow-orchestration/README.md511### 2.5.4 Bonus: Retrieval Augmented Generation (RAG)COMMENT
MEDIUM02-workflow-orchestration/README.md515#### What is RAG?COMMENT
MEDIUM02-workflow-orchestration/README.md524#### How RAG Works in KestraCOMMENT
MEDIUM02-workflow-orchestration/README.md571#### RAG Best PracticesCOMMENT
MEDIUM02-workflow-orchestration/README.md665* 2024: [notes](../cohorts/2024/02-workflow-orchestration#community-notes) and [videos](../cohorts/2024/02-workflow-orchCOMMENT
MEDIUM02-workflow-orchestration/README.md666* 2025: [notes](../cohorts/2025/02-workflow-orchestration/README.md#community-notes) and [videos](../cohorts/2025/02-worCOMMENT
MEDIUMcohorts/2022/week_2_data_ingestion/README.md14### Introduction to Workflow orchestrationCOMMENT
MEDIUMcohorts/2025/02-workflow-orchestration/README.md450* 2024: [notes](../cohorts/2024/02-workflow-orchestration#community-notes) and [videos](../cohorts/2024/02-workflow-orchCOMMENT
MEDIUMcohorts/2024/02-workflow-orchestration/README.md14* [2.2.1 - 📯 Intro to Orchestration](#221----intro-to-orchestration)COMMENT
MEDIUMcohorts/2023/week_2_workflow_orchestration/README.md16### 1. Introduction to Workflow orchestrationCOMMENT
MEDIUMcohorts/2026/workshops/dlt/README.md47| [Windsurf](https://codeium.com/windsurf) | Alternative agentic IDE |CODE
Hyper-Verbose Identifiers27 hits · 22 pts
SeverityFileLineSnippetContext
LOW02-workflow-orchestration/flows/02_python.yaml18 def get_docker_image_downloads(image_name: str = "kestra/kestra"):CODE
LOW04-analytics-engineering/setup/local_setup.md93def download_and_convert_files(taxi_type):CODE
LOWcohorts/2022/week_2_data_ingestion/homework/solution.py45def donwload_parquetize_upload_dag(CODE
LOW…-data-warehouse/extras/web_to_gcs_with_progress_bar.py52def csv_to_parquet_with_progress(CODE
LOW…-data-warehouse/extras/web_to_gcs_with_progress_bar.py115def upload_to_gcs_with_progress(bucket: str, object_name: str, local_file: str):CODE
LOW07-streaming/workshop/README.md799def create_events_source_kafka(t_env):CODE
LOW07-streaming/workshop/README.md834def create_processed_events_sink_postgres(t_env):STRING
LOW07-streaming/workshop/README.md1042def create_events_source_kafka(t_env):STRING
LOW07-streaming/workshop/README.md1066def create_events_aggregated_sink(t_env):STRING
LOW07-streaming/workshop/live/src/job/aggregation_job.py5def create_events_source_kafka(t_env):CODE
LOW07-streaming/workshop/live/src/job/aggregation_job.py29def create_events_aggregated_sink(t_env):STRING
LOW07-streaming/workshop/live/src/job/pass_through_job.py6def create_events_source_kafka(t_env):CODE
LOW07-streaming/workshop/live/src/job/pass_through_job.py28def create_processed_events_sink_postgres(t_env):STRING
LOW07-streaming/workshop/src/job/aggregation_job.py5def create_events_aggregated_sink(t_env):CODE
LOW07-streaming/workshop/src/job/aggregation_job.py26def create_events_source_kafka(t_env):STRING
LOW07-streaming/workshop/src/job/pass_through_job.py5def create_processed_events_sink_postgres(t_env):CODE
LOW07-streaming/workshop/src/job/pass_through_job.py27def create_events_source_kafka(t_env):STRING
LOW07-streaming/workshop/src/job/aggregation_job_demo.py14def create_events_source_kafka(t_env):CODE
LOW07-streaming/workshop/src/job/aggregation_job_demo.py38def create_events_aggregated_sink(t_env):STRING
LOW…ing/extras/python/streams-example/pyspark/streaming.py20def parse_ride_from_kafka_message(df, schema):CODE
LOW…ng/extras/python/streams-example/redpanda/streaming.py20def parse_ride_from_kafka_message(df, schema):CODE
LOW07-streaming/extras/pyflink/src/job/aggregation_job.py6def create_events_aggregated_sink(t_env):CODE
LOW07-streaming/extras/pyflink/src/job/aggregation_job.py26def create_events_source_kafka(t_env):STRING
LOW07-streaming/extras/pyflink/src/job/start_job.py5def create_processed_events_sink_postgres(t_env):CODE
LOW07-streaming/extras/pyflink/src/job/start_job.py24def create_events_source_kafka(t_env):STRING
LOW07-streaming/extras/pyflink/src/job/taxi_job.py5def create_taxi_events_sink_postgres(t_env):CODE
LOW07-streaming/extras/pyflink/src/job/taxi_job.py42def create_events_source_kafka(t_env):STRING
Slop Phrases6 hits · 18 pts
SeverityFileLineSnippetContext
MEDIUM…2022/week_3_data_warehouse/airflow/docker-compose.yaml39# Feel free to modify this file to suit your needs.COMMENT
MEDIUM…2022/week_3_data_warehouse/airflow/docker-compose.yaml44 # In order to add custom dependencies or upgrade provider packages you can use your extended image.COMMENT
MEDIUM…2022/week_2_data_ingestion/airflow/docker-compose.yaml39# Feel free to modify this file to suit your needs.COMMENT
MEDIUM…2022/week_2_data_ingestion/airflow/docker-compose.yaml44 # In order to add custom dependencies or upgrade provider packages you can use your extended image.COMMENT
MEDIUM…eek_2_data_ingestion/airflow/docker-compose_2.3.4.yaml39# Feel free to modify this file to suit your needs.COMMENT
MEDIUM…eek_2_data_ingestion/airflow/docker-compose_2.3.4.yaml44 # In order to add custom dependencies or upgrade provider packages you can use your extended image.COMMENT
Unused Imports16 hits · 16 pts
SeverityFileLineSnippetContext
LOW…22/week_3_data_warehouse/airflow/dags/gcs_to_bq_dag.py2CODE
LOW…k_2_data_ingestion/airflow/dags_local/ingest_script.py1CODE
LOW…ingestion/airflow/extras/data_ingestion_gcs_dag_ex2.py2CODE
LOW…ingestion/airflow/extras/data_ingestion_gcs_dag_ex2.py7CODE
LOW…ingestion/airflow/extras/data_ingestion_gcs_dag_ex2.py8CODE
LOWcohorts/2025/workshops/dynamic_load_dlt.py1CODE
LOW06-batch/code/06_spark_sql.py6CODE
LOW06-batch/code/06_spark_sql_big_query.py6CODE
LOW07-streaming/workshop/src/producers/producer.py11CODE
LOW07-streaming/extras/python/redpanda_example/consumer.py1CODE
LOW07-streaming/extras/pyflink/src/job/aggregation_job.py2CODE
LOW07-streaming/extras/pyflink/src/job/aggregation_job.py2CODE
LOW07-streaming/extras/pyflink/src/job/start_job.py2CODE
LOW07-streaming/extras/pyflink/src/job/start_job.py2CODE
LOW07-streaming/extras/pyflink/src/job/taxi_job.py2CODE
LOW07-streaming/extras/pyflink/src/job/taxi_job.py2CODE
Over-Commented Block14 hits · 14 pts
SeverityFileLineSnippetContext
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml1# Licensed to the Apache Software Foundation (ASF) under oneCOMMENT
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml141# healthcheck:COMMENT
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml161# command: triggererCOMMENT
LOW…2022/week_3_data_warehouse/airflow/docker-compose.yaml261 - airflowCOMMENT
LOW…2022/week_2_data_ingestion/airflow/docker-compose.yaml1# Licensed to the Apache Software Foundation (ASF) under oneCOMMENT
LOW…2022/week_2_data_ingestion/airflow/docker-compose.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…eek_2_data_ingestion/airflow/docker-compose_2.3.4.yaml1# Licensed to the Apache Software Foundation (ASF) under oneCOMMENT
LOW…eek_2_data_ingestion/airflow/docker-compose_2.3.4.yaml21# WARNING: This configuration is for local development. Do not use it in a production deployment.COMMENT
LOW…ingestion/airflow/extras/data_ingestion_gcs_dag_ex2.py21 "depends_on_past": False,COMMENT
LOW…ingestion/airflow/extras/data_ingestion_gcs_dag_ex2.py61COMMENT
LOW03-data-warehouse/extras/web_to_gcs.py101# web_to_gcs("2020", "yellow")COMMENT
LOW07-streaming/workshop/live/README.md1# streaming-workshopCOMMENT
LOW…ing/extras/python/redpanda_example/docker-compose.yaml41 # command:COMMENT
Excessive Try-Catch Wrapping17 hits · 13 pts
SeverityFileLineSnippetContext
LOWcohorts/2025/workshops/dynamic_load_dlt.py107 except Exception as e:CODE
LOWcohorts/2025/03-data-warehouse/load_yellow_taxi_data.py40 except Exception as e:CODE
LOWcohorts/2025/03-data-warehouse/load_yellow_taxi_data.py96 except Exception as e:CODE
LOW…ts/2023/week_6_stream_processing/producer_confluent.py50 except Exception as e:CODE
LOWcohorts/2026/03-data-warehouse/load_yellow_taxi_data.py40 except Exception as e:CODE
LOWcohorts/2026/03-data-warehouse/load_yellow_taxi_data.py96 except Exception as e:CODE
LOW07-streaming/workshop/README.md1114 except Exception as e:STRING
LOW07-streaming/workshop/live/src/job/aggregation_job.py77 except Exception as e:STRING
LOW07-streaming/workshop/src/job/aggregation_job.py79 except Exception as e:STRING
LOW07-streaming/workshop/src/job/pass_through_job.py74 except Exception as e:STRING
LOW07-streaming/workshop/src/job/aggregation_job_demo.py88 except Exception as e:STRING
LOW07-streaming/extras/python/avro_example/producer.py69 except Exception as e:CODE
LOW…ming/extras/python/streams-example/pyspark/producer.py46 except Exception as e:CODE
LOW…ing/extras/python/streams-example/redpanda/producer.py46 except Exception as e:CODE
LOW07-streaming/extras/pyflink/src/job/aggregation_job.py85 except Exception as e:STRING
LOW07-streaming/extras/pyflink/src/job/start_job.py69 except Exception as e:STRING
LOW07-streaming/extras/pyflink/src/job/taxi_job.py104 except Exception as e:STRING
Decorative Section Separators4 hits · 12 pts
SeverityFileLineSnippetContext
MEDIUM…2022/week_3_data_warehouse/airflow/2_setup_nofrills.md113 # -----------------------------------COMMENT
MEDIUM…2022/week_3_data_warehouse/airflow/1_setup_official.md113 # -----------------------------------COMMENT
MEDIUM…2022/week_2_data_ingestion/airflow/2_setup_nofrills.md112 # -----------------------------------COMMENT
MEDIUM…2022/week_2_data_ingestion/airflow/1_setup_official.md111 # -----------------------------------COMMENT
Verbosity Indicators5 hits · 11 pts
SeverityFileLineSnippetContext
LOW…s/2023/week_6_stream_processing/streaming_confluent.py82 # Step 1: Consume GREEN_TAXI_TOPIC and FHV_TAXI_TOPICCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py86 # Step 2: Publish green and fhv rides to RIDES_TOPICCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py90 # Step 3: Read RIDES_TOPIC and parse it in ALL_RIDE_SCHEMACOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py94 # Step 4: Apply Aggregation on the all_ridesCOMMENT
LOW…s/2023/week_6_stream_processing/streaming_confluent.py98 # Step 5: Sink Aggregation Streams to ConsoleCOMMENT
Self-Referential Comments3 hits · 9 pts
SeverityFileLineSnippetContext
MEDIUM…22/week_3_data_warehouse/airflow/dags/gcs_to_bq_dag.py70 # Create a partitioned table from external tableCOMMENT
MEDIUMcohorts/2025/workshops/dynamic_load_dlt.py110# Create the pipelineCOMMENT
MEDIUM…reaming/extras/pyflink/src/producers/load_taxi_data.py6 # Create a Kafka producerCOMMENT
Deep Nesting6 hits · 6 pts
SeverityFileLineSnippetContext
LOWcohorts/2025/workshops/dynamic_load_dlt.py94CODE
LOW…-data-warehouse/extras/web_to_gcs_with_progress_bar.py30CODE
LOW07-streaming/extras/python/redpanda_example/consumer.py14CODE
LOW07-streaming/extras/python/json_example/consumer.py13CODE
LOW…ming/extras/python/streams-example/pyspark/consumer.py12CODE
LOW…ing/extras/python/streams-example/redpanda/consumer.py12CODE
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HIGH02-workflow-orchestration/README.md483export GEMINI_API_KEY="your-api-key-here"CODE
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LOWcohorts/2025/03-data-warehouse/load_yellow_taxi_data.py50 # Check if the bucket belongs to the current projectCOMMENT
LOWcohorts/2026/03-data-warehouse/load_yellow_taxi_data.py50 # Check if the bucket belongs to the current projectCOMMENT