Dataview

DataView 是一个 Bash 命令行工具，通过 ingest、transform、query、filter 等命令把数据操作按时间戳记录到 ~/.local/share/dataview/ 下的本地日志，并用 stats、search、recent、status 查看与检索，可导出 JSON、CSV 或 TXT。它只记录文本条目，不实际解析或计算 CSV/JSON 内容，无需外部服务或密钥。

bytesagain-lab

热度 85.15

最近更新 2026-05-17 15:17:10

分类：效率依赖：代码执行 / 读写文件应用场景：数据处理 / 工作流 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add bytesagain-lab/dataview

Metadata

name: DataView
description: Explore CSV and JSON files with quick queries, filters, and aggregation. Use when inspecting data, running queries, filtering rows, aggregating.
version: 2.0.0
author: BytesAgain
homepage: https://bytesagain.com
source: https://github.com/bytesagain/ai-skills
tags: ["data","csv","json","analysis","statistics","viewer","explorer","developer"]
categories: ["Developer Tools","Data Analysis","Utility"]

DataView

A data processing 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.

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

Utility Commands

Command	Description
`dataview stats`	Show summary statistics — entry counts per category, total entries, disk usage
`dataview export <fmt>`	Export all data to a file (formats: `json`, `csv`, `txt`)
`dataview search <term>`	Search all log files for a term (case-insensitive)
`dataview recent`	Show last 20 entries from activity history
`dataview status`	Health check — version, data directory, entry count, disk usage, last activity
`dataview help`	Show available commands
`dataview version`	Show version (v2.0.0)

Data Storage

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

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 viewing and analysis activities
To export accumulated records in JSON, CSV, or plain text format
As part of larger automation or data inspection workflows
When you need a lightweight, local-only data operation tracker

Examples

# Record a new ingest entry
dataview ingest "loaded sales_report.csv 2500 rows"

# View recent transform entries
dataview transform

# Record a query
dataview query "top 10 products by revenue"

# Filter data
dataview filter "region=APAC"

# Search across all logs
dataview search "sales"

# Export everything as CSV
dataview export csv

# Check overall statistics
dataview stats

# View recent activity
dataview recent

# Health check
dataview status

Powered by BytesAgain | bytesagain.com | hello@bytesagain.com 💬 Feedback & Feature Requests: https://bytesagain.com/feedback