Districtpilot Ai

F 48 completed
Other
unknown / sql · tiny
35
Files
6,964
LOC
0
Frameworks
4
Languages

Pipeline State

completed
Run ID
#1357930
Phase
done
Progress
0%
Started
2026-04-16 03:08:14
Finished
2026-04-16 03:08:14
LLM tokens
0
Previous runs
Findings curated by Repobility · https://repobility.com
#StatusPhaseStartedFinished
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
#1357929completed2026-04-16 03:08:132026-04-16 03:08:13
#1357928completed2026-04-16 03:08:122026-04-16 03:08:12
#1357921completed2026-04-16 03:08:122026-04-16 03:08:12

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
37.31
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47876
Member of a group with 57 similar repo(s) — canonical #186778 view group →
Repobility · code-quality intelligence · https://repobility.com

AI Prompt

I want to build a data analysis and demonstration tool based on the provided SQL scripts and Python logic. The core functionality should involve connecting to a data source, perhaps using Snowflake credentials defined in a YAML file. I need a Streamlit application that can process data using Python, potentially integrating ML or search agent logic demonstrated in the SQL files like `cortex_search_agent.sql`. Please structure the project to allow for running a demo script and visualizing the results, keeping the data transformation logic contained within the various SQL files.
sql python streamlit data-analysis snowflake ml data-pipeline database
Generated by gemma4:latest

Catalog Information

I want to build a data analysis and demonstration tool based on the provided SQL scripts and Python logic. The core functionality should involve connecting to a data source, perhaps using Snowflake credentials defined in a YAML file. I need a Streamlit application that can process data using Python, potentially integrating ML or search agent logic demonstrated in the SQL files like cortex_search_agent.sql. Please structure the project to allow for running a demo script and visualizing the resu

Tags

sql python streamlit data-analysis snowflake ml data-pipeline database

Quality Score

F
47.7/100
Structure
45
Code Quality
53
Documentation
56
Testing
0
Practices
57
Security
84
Dependencies
50

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices — no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found — high risk of regressions
  • No CI/CD configuration — manual testing and deployment
  • 770 duplicate lines detected — consider DRY refactoring
  • 2 'god files' with >500 LOC need decomposition

Recommendations

  • Add a test suite — start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency
  • Address 86 TODO/FIXME items — consider tracking them as issues

Languages

sql
56.2%
python
34.9%
markdown
8.7%
yaml
0.2%

Frameworks

None detected

Symbols

variable132
function70
constant66

Quality Timeline

3 quality scores recorded.

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Repobility (the analyzer behind this table) · https://repobility.com

BinComp Dependency Hardening

All packages →
1 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Fpandas3.0.2 · 6,381 gadgets · risk 0.0