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DataExpert-io/data-engineer-handbook

This is a repo with links to everything you'd ever want to learn about data engineering

4.3 Low pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for DataExpert-io/data-engineer-handbook, a Jupyter Notebook project with 44,425 GitHub stars. SynthScan examined 3,351 lines of code across 89 source files, recording 18 pattern matches distributed across 4 syntactic categories. The legacy adjusted pattern signal is 4.3 (Low pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

4.3
Adjusted Signal
4.3
Raw Pattern Score
100%
Time Factor
2026-08-03
Last Push
44.4K
Stars
Jupyter Notebook
Language
3.4K
Lines of Code
89
Files
18
Pattern Hits
2026-10-12
Scan Date
0.00
HC Hit Rate

Risk Review · v3

Use each vector to guide manual verification of the underlying findings.

Cognitive Ownership Risk 10.6/100 · LOW

Can maintainers explain intent, assumptions, and trade-offs? 10 finding(s).

Hallucinated Dependency & Supply Chain Risk 8.6/100 · LOW

Are imports declared and package/API names verified? 6 finding(s).

Agent Over-Engineering Ratio 9.9/100 · LOW

Are wrappers, guards, and repeated structures necessary? 11 finding(s).

PR Review Velocity Impact 23.6/100 · LOW

Which changes need focused human review? 18 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 0HIGH 0MEDIUM 0LOW 18

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 18 distinct pattern matches across 4 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. 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 configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Unused Imports6 hits · 6 pts
SeverityFileLineSnippetContext
LOW…-fundamentals/src/tests/test_monthly_user_site_hits.py1CODE
LOW…3-spark-fundamentals/src/tests/test_team_vertex_job.py1CODE
LOW…ials/3-spark-fundamentals/src/tests/test_player_scd.py1CODE
LOW…als/4-apache-flink-training/src/job/aggregation_job.py3CODE
LOW…als/4-apache-flink-training/src/job/aggregation_job.py3CODE
LOW…materials/4-apache-flink-training/src/job/start_job.py6CODE
Hyper-Verbose Identifiers9 hits · 6 pts
SeverityFileLineSnippetContext
LOW…rials/3-spark-fundamentals/src/jobs/team_vertex_job.py25def do_team_vertex_transformation(spark, dataframe):STRING
LOW…rials/3-spark-fundamentals/src/jobs/players_scd_job.py42def do_player_scd_transformation(spark, dataframe):STRING
LOW…rk-fundamentals/src/jobs/monthly_user_site_hits_job.py7def do_monthly_user_site_hits_transformation(spark, dataframe, ds):CODE
LOW…als/4-apache-flink-training/src/job/aggregation_job.py8def create_aggregated_events_sink_postgres(t_env):CODE
LOW…als/4-apache-flink-training/src/job/aggregation_job.py28def create_aggregated_events_referrer_sink_postgres(t_env):STRING
LOW…als/4-apache-flink-training/src/job/aggregation_job.py48def create_processed_events_source_kafka(t_env):STRING
LOW…materials/4-apache-flink-training/src/job/start_job.py7def create_processed_events_sink_kafka(t_env):CODE
LOW…materials/4-apache-flink-training/src/job/start_job.py36def create_processed_events_sink_postgres(t_env):STRING
LOW…materials/4-apache-flink-training/src/job/start_job.py83def create_events_source_kafka(t_env):STRING
Redundant / Tautological Comments1 hit · 2 pts
SeverityFileLineSnippetContext
LOW…terials/1-dimensional-data-modeling/scripts/init-db.sh13# Check if the path is a directory using the -d flag andCOMMENT
Excessive Try-Catch Wrapping2 hits · 1 pts
SeverityFileLineSnippetContext
LOW…als/4-apache-flink-training/src/job/aggregation_job.py126 except Exception as e:STRING
LOW…materials/4-apache-flink-training/src/job/start_job.py145 except Exception as e:STRING