Plisty
F 49 completed
Other
unknown / json · tiny
13
Files
6,916
LOC
0
Frameworks
3
Languages
Pipeline State
completedRun ID
#397131Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
32.42Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47296
Member of a group with 1 similar repo(s) — canonical #110080 view group →
Top concepts (1)
Architecture Description
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
🧪 Code Distillation
Browse all specs →AI Prompt
Create a basic project structure for a tool named "seosieve__Plisty". I need the project to support JSON, Python, and shell scripting. Since the repository seems related to SEO or plist files, please set up a foundational structure that might process or manage data using these formats. Include placeholder files or directories for these different language components.
json python shell scripting data-processing seo plist
Generated by gemma4:latest
Catalog Information
seosieve__Plisty
Novelty
3/10Tags
json python shell scripting data-processing seo plist
Claude Models
claude-opus-4-6
Quality Score
F
48.6/100
Structure
33
Code Quality
75
Documentation
22
Testing
0
Practices
66
Security
100
Dependencies
80
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 tests found \u2014 high risk of regressions
- No CI/CD configuration \u2014 manual testing and deployment
Recommendations
- Add a comprehensive README.md explaining purpose, setup, usage, and architecture
- 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)
Security & Health
4.1h
Tech Debt (B)
Medium
DORA Rating
A
OWASP (100%)
Same scanner, your repo: https://repobility.com — Repobility
FAIL
Quality Gate
A
Risk (13)
Unknown
License
23.5%
Duplication
Languages
Frameworks
None detected
Symbols
constant95
function27
method6
class2
Concepts (1)
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| ai_architecture | Architecture Description | # Architecture Overview: seosieve__Plisty ## 1. Executive Summary seosieve__Plisty is a lightweight utility repository that processes music metadata (JSON, LRC, SRT) and generates playlists, lyric previews, and other ancillary files. It serves content creators and music curators who need quick, reproducible transformations of raw lyric and tracklist data. The architecture follows a **script‑centric** style: shell wrappers invoke Python scripts that perform the core logic. The codebase is in an early maturity stage, with a single responsibility focus but lacking formal testing and documentation. A key strength is its minimal external dependencies; a key risk is the absence of automated validation or error handling, which can lead to silent failures. ## 2. System Architecture Diagram ```mermaid graph TD subgraph "Data Layer" JSON[JSON Files] -->|read| Python[Python Scripts] LRC[LRC Files] -->|read| Python SRT[SRT Files] -->|read| Python end subgraph "Application Layer" Python -->|output| Shell[Shell Scripts] Python -->|output| Console[Console] end subgraph "Presentation Layer" Shell -->|invoke| CLI[Command Line] end ``` The diagram shows that JSON, LRC, and SRT files are the primary data sources. Python scripts (`generate.py`, `lyrics.py`, `preview.py`) read these files, transform the data, and either write new files or print to stdout. Shell scripts (`playlist.sh`, `generate.py` in `scripts/`) act as thin wrappers that orchestrate the Python scripts and provide a CLI interface. ## 3. Architectural Layers | Layer | Responsibility | Key Files/Directories | Boundary Enforcement | Dependencies | |-------|----------------|-----------------------|----------------------|--------------| | **Data Layer** | Stores raw music metadata (JSON, LRC, SRT). | `SEOUL LABS/EP01_000000/lyrics/*.json`, `SEOUL LABS/EP02_000000/lyrics/*.lrc`, `SEOUL LABS/EP02_000000/lyrics/*.srt`, `무명 Mumyung/EP01_260309/tracklist.json` | Strict: only read by scripts; no writes except for generated outputs. | None | | **Application Layer** | Implements business logic: parsing, transformation, playlist generation. | `SEOUL LABS/scripts/*.py`, `무명 Mumyung/scripts/*.py` | Moderate: scripts import each other (e.g., `preview.py` imports `lyrics.py`). | Python standard library (`json`, `os`, `subprocess`). | | **Presentation Layer** | Exposes functionality to users via CLI. | `SEOUL LABS/scripts/playlist.sh`, `무명 Mumyung/scripts/playlist.sh` | Loose: shell scripts simply call Python scripts; no validation. | Bash, `python3`. | ## 4. Component Catalog | Component | Location | Responsibility | Public Interface | Dependencies | Dependents | |-----------|----------|----------------|------------------|--------------|------------| | **generate.py** | `SEOUL LABS/scripts/generate.py` | Orchestrates generation of playlists and lyric previews. | `main()`, `generate_playlist()`, `generate_preview()` | `lyrics.py`, `json`, `os` | `playlist.sh` | | **lyrics.py** | `SEOUL LABS/scripts/lyrics.py` | Parses lyric files (JSON, LRC, SRT) and formats them. | `parse_lyrics(file_path)`, `format_lyrics(data)` | `json`, `re` | `generate.py`, `preview.py` | | **preview.py** | `SEOUL LABS/scripts/preview.py` | Generates a short preview of lyrics for display. | `main()`, `create_preview()` | `lyrics.py`, `json` | `generate.py` | | **playlist.sh** | `SEOUL LABS/scripts/playlist.sh` | CLI wrapper that calls `generate.py` with arguments. | `./playlist.sh <options>` | Bash, `python3` | None | | **tracklist.json** | `무명 Mumyung/EP01_260309/tracklist.json` | Holds track metadata for a specific EP. | N/A | N/A | `generate.py` | ## 5. Component Interactions The primary interaction flow is: **CLI → Shell Script → Python Script → Data Files → Output**. ```mermaid sequenceDiagram participant User participant CLI as "playlist.sh" participant App as "generate.py" participant Parser as "lyrics.py" participant Data as "JSON/LRC/SRT files" User->>CLI: ./playlist.sh --ep EP01_000000 CLI->>App: python3 generate.py --ep EP01_000000 App->>Parser: parse_lyrics("SEOUL LABS/EP01_000000/lyrics/Soft Echoes on the Glass.json") Parser->>Data: read file Parser-->>App: parsed data App->>App: generate_playlist(parsed data) App->>CLI: print playlist to stdout CLI->>User: display playlist ``` ## 6. Data Flow 1. **Input Sources** - JSON lyric files (`*.json`) - LRC lyric files (`*.lrc`) - SRT lyric files (`*.srt`) - Tracklist JSON (`tracklist.json`) 2. **Transformation Steps** - `lyrics.py` reads and parses the raw files into Python dictionaries. - `generate.py` consumes these dictionaries to build playlist entries and preview snippets. - `preview.py` formats a short excerpt for console display. 3. **Storage Mechanisms** - Generated playlists are printed to stdout or written to temporary files (currently no persistent storage). - No database is used; all data remains in memory or in the file system. 4. **Output Destinations** - Console (standard output) - Optional output files (e.g., playlist files) if extended. ## 7. Technology Decisions & Rationale | Technology | Choice | Rationale | Alternatives | Risks | |------------|--------|-----------|--------------|-------| | **Python 3** | All scripts written in Python | Readable, cross‑platform, rich stdlib for JSON parsing | Node.js, Go, Rust | Requires Python runtime; limited performance for large datasets | | **Shell (Bash)** | CLI wrappers (`playlist.sh`) | Simple invocation, no extra dependencies | Makefile, Python CLI libraries (Click) | No argument validation; fragile to shell environment | | **JSON** | Primary data format | Human‑readable, native support in Python | YAML, TOML | Requires strict schema; no validation | | **LRC/SRT** | Lyric file formats | Common in music metadata | Plain text, custom JSON | Parsing complexity; no standard library support | ## 8. Scalability Considerations - **Bottlenecks**: File I/O is the main cost; scripts read entire files into memory. For very large lyric files, memory usage could spike. - **Horizontal Scaling**: Not applicable; the repository is a set of scripts, not a service. - **Stateful vs Stateless**: All components are stateless; each run processes input and exits. - **Caching**: None implemented; repeated runs re‑parse files each time. ## 9. Security Considerations - **Authentication/Authorization**: None; scripts are intended for local use. - **Input Validation**: Minimal; scripts assume well‑formed JSON/LRC/SRT. Malformed files could raise exceptions or produce incorrect output. - **Secret Management**: No secrets present. - **Known Risks**: - `playlist.sh` uses `python3 generate.py` without sanitizing arguments, potentially exposing to shell injection if arguments are derived from untrusted sources. - No error handling for missing files; could crash the script. ## 10. Testing Strategy Assessment - **Test Types Present**: None. - **Test Frameworks**: None. - **Estimated Coverage**: 0 %. - **Testing Gaps**: - No unit tests for parsing logic (`lyrics.py`). - No integration tests for end‑to‑end playlist generation. - No automated validation of JSON schema. ## 11. Technical Debt Assessment | Category | Description | Severity | Effort to Fix | |----------|-------------|----------|---------------| | **Error Handling** | Scripts lack try/except blocks; missing file checks. | High | Medium | | **Input Validation** | No schema validation for JSON/LRC/SRT. | Medium | Low | | **Documentation** | No README or usage guide. | Medium | Low | | **Testing** | No automated tests. | High | High | | **CLI Robustness** | Shell scripts do not sanitize arguments. | Medium | Low | ## 12. Recommendations for Improvement 1. **Add Unit Tests for `lyrics.py`** - *Rationale*: Validate parsing logic and catch regressions. - *Estimated Effort*: Medium (≈ 8 hrs). 2. **Implement JSON Schema Validation** - *Rationale*: Prevent silent failures on malformed input. - *Estimated Effort*: Low (≈ 4 hrs). 3. **Refactor Shell Scripts to Use `argparse` via a Python CLI** - *Rationale*: Centralize argument parsing, improve safety. - *Estimated Effort*: Medium (≈ 6 hrs). 4. **Add a Comprehensive README** - *Rationale*: Lower onboarding friction for new contributors. - *Estimated Effort*: Low (≈ 2 hrs). 5. **Introduce Logging** - *Rationale*: Easier debugging and monitoring of script runs. - *Estimated Effort*: Low (≈ 3 hrs). | 85% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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