Dining Out Editorial Scraper Tool
C 64 completed
Data Tool
unknown / python · tiny
30
Files
3,185
LOC
0
Frameworks
5
Languages
Pipeline State
completedRun ID
#305150Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
36.02Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #48843
Member of a group with 1 similar repo(s) — canonical #4056 view group →
Top concepts (1)
Web Backend
Repobility · code-quality intelligence platform · https://repobility.com
🧪 Code Distillation
Browse all specs →Sample distilled functions (click for full spec)
Storage.get_statsRetrieves key operational statistics from the underlying database connection. It accepts no inputs and returns a dictionary containing the total count of trend items, the total count of reports, and the run ID and timestamp of the most recent data collection. The function interacts with the database
Storage.cleanup_old_dataDeletes records from two database tables, trend_items and reports, based on a specified retention period. It accepts an optional integer argument, retention_days, which defaults to a predefined constant. The function connects to the underlying database, executes two separate DELETE queries using a c
Storage.save_reportPersists a generated report record into the database. It accepts a unique run identifier, the report's classification type, the HTML content, and an optional dictionary of associated metadata. The function writes the report details, along with the current UTC timestamp, into the reports table and re
AI Prompt
I need a Python tool to scrape editorial content specifically from dining out websites. The tool should be structured to handle configuration, perhaps using environment variables, and should include necessary setup and testing components. Please build the core scraping logic in `main.py` and ensure it's robust enough to process content found on these sites. I'm looking for a complete, runnable scraper setup.
python scraper web-scraping data-extraction content-scraping
Generated by gemma4:latest
Catalog Information
This project is a tool for scraping editorial content from dining out websites.
Description
The Dining-out-editorial-scraper-tool is a Python-based application that utilizes web scraping techniques to extract relevant information from online dining reviews and articles. It leverages libraries such as BeautifulSoup, Click, NumPy, and scikit-learn to efficiently gather data. The tool can be used by food bloggers, critics, or anyone interested in analyzing online dining content.
الوصف
هذا المشروع هو أداة لاستخراج المحتوى الإditorي من مواقع الأكل خارج المنزل. يعتمد هذا البرنامج على تقنيات استخراج البيانات من الإنترنت لجمع المعلومات ذات الصلة من المراجعات والمقالات حول الأكل. يستخدم هذا الأداة مكتبات بيرثيفول سوب، كليك، نومباي، وسكيت-لرن لجمع البيانات بفعالية. يمكن استخدام هذه الأداة من قبل مدونين للأكل، النقاد، أو أي شخص مهتم بتحليل المحتوى الإلكتروني حول الأكل.
Novelty
5/10Tags
web-scraping data-extraction dining-reviews editorial-content food-analysis
Technologies
beautifulsoup click numpy scikit-learn
Quality Score
C
64.4/100
Structure
55
Code Quality
83
Documentation
20
Testing
50
Practices
81
Security
100
Dependencies
90
Strengths
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
Weaknesses
- Missing README file \u2014 critical for project understanding
- No LICENSE file \u2014 legal ambiguity for contributors
- No CI/CD configuration \u2014 manual testing and deployment
Recommendations
- Add a comprehensive README.md explaining purpose, setup, usage, and architecture
- 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)
Security & Health
5.1h
Tech Debt (C)
High
DORA Rating
A
OWASP (100%)
Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot
PASS
Quality Gate
A
Risk (4)
Unknown
License
0.5%
Duplication
Languages
Frameworks
None detected
Symbols
method56
constant28
function26
variable24
class13
property1
Concepts (1)
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| Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Web Backend | web-backend | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/
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BinComp Dependency Hardening
All packages →4 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.