The Journalism Library

A collection of TypeScript functions for journalistic projects.

The library is available on JSR and NPM. It's a collection of the following modules.

• journalism-ai: GitHub - JSR - Docs - NPM
• journalism-climate: GitHub - JSR - Docs - NPM
• journalism-dataviz: GitHub - JSR - Docs - NPM
• journalism-finance: GitHub - JSR - Docs - NPM
• journalism-format: GitHub - JSR - Docs - NPM
• journalism-geo: GitHub - JSR - Docs - NPM
• journalism-google: GitHub - JSR - Docs - NPM
• journalism-statistics: GitHub - JSR - Docs - NPM
• journalism-web: GitHub - JSR - Docs - NPM
• journalism-web-scraping: GitHub - JSR - Docs - NPM
• journalism-extras: GitHub - JSR - Docs - NPM

The documentation is also available as the markdown file llm.md, which can be passed as context to improve the use of the library by AI coding assistants or agents.

The library is maintained by Nael Shiab, computational journalist and senior data producer for CBC News.

Tip

To learn how to use this library and more, check out Code Like a Journalist, a free and open-source data analysis and data visualization course in TypeScript. You might also find the simple-data-analysis library interesting.

To install the library, you can use the following commands:

# Deno
deno add jsr:@nshiab/journalism

# Node
npm i @nshiab/journalism

# Bun
bun add @nshiab/journalism

To quickly set up a data project with essential folders, configurations, and documentation for AI agents, you can use @nshiab/setup-data-project.

# Deno
deno run -A jsr:@nshiab/setup-data-project

# Node
npx @nshiab/setup-data-project

# Bun
bunx @nshiab/setup-data-project

If you wish to contribute, please check the guidelines.