data-doctor-cli-1.0.4 is not a library.

DataDoctor CLI 🩺

DataDoctor CLI is your command-line companion for maintaining data health. It brings the power of the DataDoctor engine directly to your terminal, allowing you to validate, analyze, and repair JSON and CSV files instantly.

🚀 Installation

Option 1: Install from Crates.io (Recommended)

If you have Rust installed, this is the easiest way:

cargo install data-doctor-cli

This installs the data-doctor binary to your path.

Option 2: Build from Source

git clone https://github.com/jeevanms003/data-doctor.git

cd data-doctor

cargo install --path cli

🎮 How It Works

DataDoctor provides three primary modes of operation, designed for different workflows:

1. `validate` (The Checkup)

Best for: CI/CD pipelines, pre-commit hooks, or just checking file integrity.

This command scans your file and reports issues without modifying anything. It returns a non-zero exit code if errors are found, making it perfect for automated scripts.

data-doctor validate users.csv

2. `fix` (The Surgery)

Best for: Cleaning messy data dumps, fixing "broken" JSON from APIs.

This command actively repairs the file and saves the clean version to a new output path. It applies all available auto-fix strategies (e.g., adding missing quotes, padding columns).

data-doctor fix broken_data.json --out clean_data.json

3. `doctor` (The Full Treatment)

Best for: Interactive analysis and reporting.

This runs a validation pass, then an auto-fix pass, and generates a comprehensive report comparing the "before" and "after" states.

data-doctor doctor input.csv --out fixed.csv

📋 Command Reference

`validate`

data-doctor validate <INPUT> [OPTIONS]

Options:

--format <json|csv>: Force a specific file format (overrides extension detection).
--report-json: Print a machine-readable JSON object instead of the human-readable report.
--schema <FILE>: Validate against a custom schema definition.

`fix`

data-doctor fix <INPUT> --out <OUTPUT> [OPTIONS]

Options:

--out <FILE>: (Required) Where to save the fixed file.
--format <json|csv>: Force specific file format.

`doctor`

data-doctor doctor <INPUT> --out <OUTPUT> [OPTIONS]

Combines validate and fix functionalities with detailed logging.

🔍 What Can It Fix?

JSON Fixes (Advanced)

Issue	Example (Before)	Example (After)
Broken Structure	`[ { "a": 1 } }`	`[ { "a": 1 } ]` (Mismatched bracket fix)
Embedded Keys	`"desc": "val,"key": "v"`	`"desc": "val", "key": "v"`
Numeric Formats	`{"val": 0xFF, "oct": 0o77}`	`{"val": 255, "oct": 63}`
Invalid Booleans	`{"active": yes}`	`{"active": true}`
Leading Zeros	`{"id": 030}`	`{"id": 30}`
Trailing Commas	`{"a": 1,}`	`{"a": 1}`
Missing Commas	`{"a": 1 "b": 2}`	`{"a": 1, "b": 2}`
Unquoted Keys	`{name: "John"}`	`{"name": "John"}`
Single Quotes	`{'name': 'John'}`	`{"name": "John"}`
Unclosed Brackets	`[1, 2, 3`	`[1, 2, 3]`

CSV Fixes

Issue	Before	After
Padding Columns	`A,B,C1,2`	`A,B,C1,2,` (Empty added)
Trimming Cols	`A,B1,2,3,4`	`A,B1,2` (Extras removed)
Booleans	`Yes, No`	`true, false`
Whitespace	`Value`	`Value`

📊 JSON Reports

For integration with other tools (like dashboards), use --report-json.

Command:

data-doctor validate data.csv --report-json

Output:

{
  "success": false,
  "total_records": 100,
  "invalid_records": 5,
  "issues": [
    {
      "severity": "Error",
      "code": "CSV_TYPE_MISMATCH",
      "message": "Invalid Integer value",
      "row": 42,
      "column": 2
    }
  ]
}

📄 License

This project is licensed under the MIT License.

data-doctor-cli 1.0.4