Data Labeler#

A data processing and labeling toolkit for ingesting, transforming, querying, and managing data entries from the command line. All operations are logged with timestamps and stored locally.

Commands#

Data Operations#

Each data command works in two modes: run without arguments to view recent entries, or pass input to record a new entry.

CommandDescriptiondata-labeler ingest <input>Ingest data — record a new ingest entry or view recent onesdata-labeler transform <input>Transform data — record a transformation or view recent onesdata-labeler query <input>Query data — record a query or view recent onesdata-labeler filter <input>Filter data — record a filter operation or view recent onesdata-labeler aggregate <input>Aggregate data — record an aggregation or view recent onesdata-labeler visualize <input>Visualize data — record a visualization or view recent onesdata-labeler export <input>Export data — record an export entry or view recent onesdata-labeler sample <input>Sample data — record a sample or view recent onesdata-labeler schema <input>Schema management — record a schema entry or view recent onesdata-labeler validate <input>Validate data — record a validation or view recent onesdata-labeler pipeline <input>Pipeline management — record a pipeline step or view recent onesdata-labeler profile <input>Profile data — record a profile or view recent ones

Utility Commands#

CommandDescriptiondata-labeler statsShow summary statistics — entry counts per category, total entries, disk usagedata-labeler export <fmt>Export all data to a file (formats: json, csv, txt)data-labeler search <term>Search all log files for a term (case-insensitive)data-labeler recentShow last 20 entries from activity historydata-labeler statusHealth check — version, data directory, entry count, disk usage, last activitydata-labeler helpShow available commandsdata-labeler versionShow version (v2.0.0)

Data Storage#

All data is stored locally at ~/.local/share/data-labeler/:

• Each data command writes to its own log file (e.g., ingest.log, transform.log)
• Entries are stored as timestamp|value pairs (pipe-delimited)
• All actions are tracked in history.log with timestamps
• Export generates files in the data directory ( export.json, export.csv, or export.txt)

Requirements#

• Bash (with set -euo pipefail)
• Standard Unix utilities: date, wc, du, grep, tail, cat, sed
• No external dependencies or API keys required

When to Use#

• To log and track data processing operations (ingest, transform, query, etc.)
• To maintain a searchable history of data pipeline activities
• To export accumulated records in JSON, CSV, or plain text format
• As part of larger automation or data-pipeline workflows
• When you need a lightweight, local-only data operation tracker

Examples#

bash

# Record a new ingest entry
data-labeler ingest "loaded customer_data.csv 5000 rows"

# View recent transform entries
data-labeler transform

# Search across all logs
data-labeler search "customer"

# Export everything as JSON
data-labeler export json

# Check overall statistics
data-labeler stats

# View recent activity
data-labeler recent

# Health check
data-labeler status

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