Whichticker

D 50 completed
Cli Tool
web_app / python · tiny
16
Files
2,586
LOC
1
Frameworks
8
Languages

Pipeline State

completed
Run ID
#354029
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
46.10
Framework unique
Isolation
Last stage change
2026-05-10 03:35:28
Deduplication group #56484
Member of a group with 4 similar repo(s) — canonical #29730 view group →
Top concepts (2)
Project DescriptionWeb Backend
Repobility — the code-quality scanner for AI-generated software · https://repobility.com

AI Prompt

I want to build a web application using Python and FastAPI that helps users compare and predict the performance of different stock tickers. The tool should analyze market data to provide insights. Please structure the project to handle the core logic for analysis and signal generation, and ensure it's set up as a functional web app.
python fastapi web-app stock finance prediction market-data
Generated by gemma4:latest

Catalog Information

This project provides a tool to compare and predict the performance of different stock tickers.

Description

Whichticker is a Python-based application that allows users to input multiple stock tickers and receive predictions on which one will outperform the others. The project utilizes various libraries such as numpy, pandas, and scipy for data analysis and manipulation. It does not require any database connection and can be run using uvicorn.

الوصف

هذا المشروع يقدم أداة لتحليل وتوقع أداء أسهم مختلفة. يمكن للمستخدمين إدخال عدة رموز سوقية وتلقي توقعات حول التي من بينها ستتجاوز الآخرات. يستخدم المشروع مكتبات مثل numpy, pandas, و scipy للتحليل والتعديل البياني، ولا يحتاج إلى اتصال قاعدة بيانات ويمكن تشغيله باستخدام uvicorn.

Novelty

5/10

Tags

stock-analysis prediction-model data-comparison financial-tools market-prediction investment-advice

Technologies

anthropic fastapi numpy pandas scipy uvicorn

Claude Models

claude-opus-4.6

Quality Score

D
50.2/100
Structure
41
Code Quality
60
Documentation
62
Testing
0
Practices
58
Security
90
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment
  • Potential hardcoded secrets in 1 files
  • 252 duplicate lines detected \u2014 consider DRY refactoring
  • 1 'god files' with >500 LOC need decomposition

Recommendations

  • Add a test suite \u2014 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
  • Add a LICENSE file (MIT recommended for open source)
  • Move hardcoded secrets to environment variables or a secrets manager

Security & Health

5.8h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (5)
Repobility · code-quality intelligence · https://repobility.com
Unknown
License
2.8%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
42.9%
javascript
34.9%
css
12.1%
html
8.8%
shell
0.7%
text
0.4%
toml
0.2%
markdown
0.0%

Frameworks

FastAPI

Concepts (2)

Scored by Repobility's multi-pass pipeline · https://repobility.com
CategoryNameDescriptionConfidence
Want fix-PRs on findings? Install Repobility's GitHub App · github.com/apps/repobility-bot
auto_descriptionProject DescriptionWhich ticker will outperform??80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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