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Structured data profiling for the analyser family

Project description

records-analyser

Profiles structured data files and returns row counts, column statistics, schema inference, missing value counts, and sample rows.

Part of the analyser family.

Install

pip install records-analyser

Requires Python 3.11+.

Usage

Python

from records_analyser import RecordsAnalyser

result = RecordsAnalyser().analyse("survey.csv")

profile = result["profile"]
print(f"Rows: {profile['rows']}, Columns: {profile['columns']}")
for col, info in profile["column_profiles"].items():
    print(f"  {col}: {info['type']}, missing={info['missing']}")

CLI

# Human-readable summary
records-analyser analyse data.csv

# SQLite — profiles all tables
records-analyser analyse results.db

# Machine-readable JSON
records-analyser analyse data.xlsx --json

# Start the HTTP server
records-analyser serve --port 8003

HTTP API

curl -X POST http://localhost:8003/analyse \
  -F "file=@data.csv"

Supported formats

Format Extensions
CSV / TSV .csv .tsv
Excel .xlsx .xls
Parquet .parquet
SQLite .sqlite .db .sqlite3
JSON .json
YAML .yaml .yml
XML .xml

JSON and YAML files that look like configuration objects (not arrays of records) include a warning suggesting document-analyser for prose content.

Output

{
  "format": "csv",
  "file_path": "/path/to/survey.csv",
  "file_size": 4096,
  "profile": {
    "rows": 150,
    "columns": 4,
    "column_profiles": {
      "age": {
        "type": "numeric",
        "min": 18.0, "max": 72.0, "mean": 34.2,
        "median": 32.0, "std": 11.4,
        "q25": 25.0, "q75": 42.0,
        "missing": 2, "missing_pct": 1.3
      },
      "country": {
        "type": "categorical",
        "unique": 12,
        "top_values": {"Australia": 45, "USA": 38},
        "missing": 0, "missing_pct": 0.0
      }
    },
    "sample": [{"age": 28, "country": "Australia"}]
  }
}

SQLite results include a tables key with one profile per table.

The analyser family

Low-level analysis tools. Each accepts files directly and returns structured JSON. Build your own UI or pipeline on top.

Package Handles
speech-analyser audio and video files — transcript and speech metrics
video-analyser video files — frames, scenes, and visual quality
document-analyser PDF, DOCX, PPTX, TXT — text and readability
code-analyser source code — style, complexity, and quality metrics
records-analyser CSV, Excel, SQLite, Parquet, JSON — data profiling
auto-analyser any file — detects format and routes to the right tool

Licence

MIT

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