Neckr0ik Etl Builder

Build data pipelines for ETL (Extract, Transform, Load). Connect databases, APIs, files, and cloud storage. Transform and sync data automatically. Use when y...

Data Pipeline Builder

Build ETL pipelines without code.

What This Does

• Extract — Pull data from databases, APIs, files, cloud storage
• Transform — Clean, filter, aggregate, join, enrich
• Load — Push to databases, APIs, files, cloud storage
• Schedule — Run pipelines on cron schedules
• Monitor — Track pipeline health and performance

Quick Start

# Create a pipeline
neckr0ik-etl-builder create --name "sync-users" --source postgres --destination sheets

# Add transformations
neckr0ik-etl-builder transform --pipeline sync-users --type filter --field "active" --value true

# Run pipeline
neckr0ik-etl-builder run --name sync-users

# Schedule pipeline
neckr0ik-etl-builder schedule --name sync-users --cron "0 * * * *"

Supported Sources

Source	Type	Auth
PostgreSQL	Database	Connection string
MySQL	Database	Connection string
MongoDB	Database	Connection string
SQLite	Database	File path
Google Sheets	Cloud	OAuth / API Key
Airtable	Cloud	API Key
Notion	Cloud	API Key
REST API	API	Bearer / API Key
GraphQL	API	Bearer / API Key
CSV	File	File path
JSON	File	File path
S3	Cloud	Access Key
GCS	Cloud	Service Account

Supported Destinations

Same as sources, plus:

• Webhooks
• Email
• Slack
• Discord

Commands

create

Create a new pipeline.

neckr0ik-etl-builder create --name <name> [options]

Options:
  --source <type>      Source type (postgres, mysql, api, csv...)
  --destination <type> Destination type
  --config <file>      Configuration file

extract

Configure extraction step.

neckr0ik-etl-builder extract --pipeline <name> [options]

Options:
  --table <name>       Table to extract (for databases)
  --query <sql>        Custom query
  --endpoint <url>     API endpoint
  --file <path>        File path

transform

Add transformation step.

neckr0ik-etl-builder transform --pipeline <name> [options]

Transform Types:
  filter       Filter rows by condition
  map          Map field values
  aggregate    Aggregate data (sum, count, avg...)
  join         Join with another source
  enrich       Enrich with external data
  clean        Clean nulls, trim strings
  validate     Validate data quality

load

Configure load step.

neckr0ik-etl-builder load --pipeline <name> [options]

Options:
  --mode <mode>        Load mode (append, replace, upsert)
  --table <name>       Target table
  --mapping <file>     Field mapping

run

Execute pipeline.

neckr0ik-etl-builder run --name <name> [options]

Options:
  --dry-run            Preview without executing
  --limit <n>          Process only N records
  --parallel           Run stages in parallel

schedule

Schedule pipeline.

neckr0ik-etl-builder schedule --name <name> --cron "<expression>"

status

Check pipeline status.

neckr0ik-etl-builder status --name <name>

Example Pipelines

1. Sync PostgreSQL to Google Sheets

# Create pipeline
neckr0ik-etl-builder create --name user-sync --source postgres --destination sheets

# Configure extraction
neckr0ik-etl-builder extract --pipeline user-sync \
  --query "SELECT * FROM users WHERE updated_at > NOW() - INTERVAL '1 day'"

# Add transforms
neckr0ik-etl-builder transform --pipeline user-sync --type clean
neckr0ik-etl-builder transform --pipeline user-sync --type filter --field active --value true

# Schedule hourly
neckr0ik-etl-builder schedule --name user-sync --cron "0 * * * *"

2. API to Database

# Create pipeline
neckr0ik-etl-builder create --name api-sync --source api --destination postgres

# Configure extraction
neckr0ik-etl-builder extract --pipeline api-sync \
  --endpoint "https://api.example.com/users" \
  --auth bearer \
  --token "$API_TOKEN"

# Transform
neckr0ik-etl-builder transform --pipeline api-sync --type map --field "id" --to "user_id"
neckr0ik-etl-builder transform --pipeline api-sync --type clean

# Load
neckr0ik-etl-builder load --pipeline api-sync --table api_users --mode upsert

3. CSV to Airtable

# Create pipeline
neckr0ik-etl-builder create --name csv-import --source csv --destination airtable

# Configure
neckr0ik-etl-builder extract --pipeline csv-import --file ./data.csv
neckr0ik-etl-builder transform --pipeline csv-import --type clean
neckr0ik-etl-builder load --pipeline csv-import --table "Imports" --mapping ./mapping.json

Pipeline Configuration

Pipelines are stored as JSON:

{
  "name": "user-sync",
  "source": {
    "type": "postgres",
    "connection": "postgresql://...",
    "query": "SELECT * FROM users"
  },
  "transformations": [
    {"type": "filter", "field": "active", "value": true},
    {"type": "clean"},
    {"type": "map", "from": "id", "to": "user_id"}
  ],
  "destination": {
    "type": "google_sheets",
    "spreadsheet_id": "...",
    "range": "Sheet1!A1"
  },
  "schedule": "0 * * * *"
}

Monitoring

# View pipeline history
neckr0ik-etl-builder history --name user-sync --limit 10

# View failed runs
neckr0ik-etl-builder failures --name user-sync

# Export logs
neckr0ik-etl-builder logs --name user-sync --output ./logs.json

See Also

• references/connectors.md — Source/destination connectors
• references/transforms.md — Transformation functions
• scripts/pipeline.py — Main implementation