datasette README

The project's README from github.com/simonw/datasette. As one markdown file: README.md.

Datasette

PyPI Changelog Python 3.x Tests Documentation Status License docker: datasette discord

An open source multi-tool for exploring and publishing data

Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API.

Datasette is aimed at data journalists, museum curators, archivists, local governments, scientists, researchers and anyone else who has data that they wish to share with the world.

Explore a demo, watch a video about the project or try it out on GitHub Codespaces.

Want to stay up-to-date with the project? Subscribe to the Datasette newsletter for tips, tricks and news on what's new in the Datasette ecosystem.

Installation

If you are on a Mac, Homebrew is the easiest way to install Datasette:

brew install datasette

You can also install it using pip or pipx:

pip install datasette

Datasette requires Python 3.8 or higher. We also have detailed installation instructions covering other options such as Docker.

Basic usage

datasette serve path/to/database.db

This will start a web server on port 8001 - visit http://localhost:8001/ to access the web interface.

serve is the default subcommand, you can omit it if you like.

Use Chrome on OS X? You can run datasette against your browser history like so:

 datasette ~/Library/Application\ Support/Google/Chrome/Default/History --nolock

Now visiting http://localhost:8001/History/downloads will show you a web interface to browse your downloads data:

Downloads table rendered by datasette

metadata.json

If you want to include licensing and source information in the generated datasette website you can do so using a JSON file that looks something like this:

{
    "title": "Five Thirty Eight",
    "license": "CC Attribution 4.0 License",
    "license_url": "http://creativecommons.org/licenses/by/4.0/",
    "source": "fivethirtyeight/data on GitHub",
    "source_url": "https://github.com/fivethirtyeight/data"
}

Save this in metadata.json and run Datasette like so:

datasette serve fivethirtyeight.db -m metadata.json

The license and source information will be displayed on the index page and in the footer. They will also be included in the JSON produced by the API.

datasette publish

If you have Heroku or Google Cloud Run configured, Datasette can deploy one or more SQLite databases to the internet with a single command:

datasette publish heroku database.db

Or:

datasette publish cloudrun database.db

This will create a docker image containing both the datasette application and the specified SQLite database files. It will then deploy that image to Heroku or Cloud Run and give you a URL to access the resulting website and API.

See Publishing data in the documentation for more details.

Datasette Lite

Datasette Lite is Datasette packaged using WebAssembly so that it runs entirely in your browser, no Python web application server required. Read more about that in the Datasette Lite documentation.

datasette (simonw/datasette)

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Datasette
这是什么？Datasette 是一个开源的多功能工具，用于探索和发布数据：只需指向一个 SQLite 数据库，它就能把数据变成可交互、可浏览的网站，并附带一个 JSON API。
这是命令行工具、网页应用，还是两者都是？它是一个在本地运行的命令行工具，执行 `datasette serve path/to/database.db` 后会启动一个 Web 服务器，为该数据库同时提供可浏览的界面和 JSON API。
我该如何安装并启动数据库？在 Mac 上可以运行 `brew install datasette`，其他系统则可用 `pip install datasette` 或 pipx 安装，然后执行 `datasette serve path/to/database.db`，即可在本地 Web 服务器上浏览数据。
我需要先安装 Python 吗？需要。如果通过 pip 或 pipx 安装，Datasette 要求 Python 3.8 或更高版本（通过 Homebrew 和 Docker 安装时已自动包含该环境）。
它支持任何数据库，还是只支持 SQLite？Datasette 是专门围绕 SQLite 数据库构建的，你需要指向 `.db` 文件，而不是连接 Postgres 或 MySQL 服务器。
它面向哪些人群？它面向数据新闻记者、博物馆策展人、档案管理人员、地方政府、科学家、研究人员，以及任何希望公开分享数据的人。
我怎样把数据发布到互联网上，而不只是在本地运行？`datasette publish` 命令可以把包含 Datasette 和你的 SQLite 文件的 Docker 镜像，只用一条命令部署到 Heroku 或 Google Cloud Run，并获得一个在线网址和 API。
什么是 Datasette Lite？它是编译为 WebAssembly 的 Datasette，可以完全在浏览器中运行，无需任何 Python 服务器。
如何为已发布的网站添加许可和来源署名？创建一个 metadata.json 文件，其中包含 title、license、licenseurl、source 和 sourceurl 字段，并通过 `-m metadata.json` 传入；这些信息会显示在网站的页脚以及 API 输出中。
我可以用自己已有的数据，比如浏览器历史记录，来试试吗？可以。例如，你可以运行 `datasette ~/Library/Application Support/Google/Chrome/Default/History --nolock`，把自己的 Chrome 浏览历史当作示例数据来浏览。
What are similar projects?nocodb, postgrest, duckdb, prediction-market-analysis, q, visidata, redash, capcut-mate
Which topics is it in?asgi, automatic-api, datasets, csv, wasm, sql, data-science, json, sqlite, rest-api, database, command-line-tool
Creator
simonw
Size
11.1 MB
Stars
11.5K
Updated
CommitOct 12Release0.65.5Sep 16
Age
8y
Commits · 90 Days