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text/typescript
import { Route } from '@/types';
import cache from '@/utils/cache';
import ofetch from '@/utils/ofetch';
import { load } from 'cheerio';
import { parseDate } from '@/utils/parse-date';
import { art } from '@/utils/render';
import path from 'node:path';
export const handler = async (ctx) => {
const { tag } = ctx.req.param();
const limit = ctx.req.query('limit') ? Number.parseInt(ctx.req.query('limit'), 10) : 1;
const rootUrl = 'https://www.deeplearning.ai';
const currentUrl = new URL(`the-batch${tag ? `/tag/${tag.replace(/^tag\//, '').replace(/\/$/, '')}` : ''}/`, rootUrl).href;
const response = await ofetch(currentUrl);
const $ = load(response);
const language = $('html').prop('lang');
const data = JSON.parse($('script#__NEXT_DATA__').text());
const nextBuildId = data.buildId;
const posts = data.props?.pageProps?.posts ?? [];
let items = posts.slice(0, limit).map((item) => {
const title = item.title;
const description = art(path.join(__dirname, 'templates/description.art'), {
images: item.feature_image
? [
{
src: item.feature_image,
alt: item.feature_image_alt,
},
]
: undefined,
intro: item.excerpt ?? item.custom_excerpt,
});
const image = item.feature_image;
const guid = `the-batch-${item.slug}`;
return {
title,
description,
pubDate: parseDate(item.published_at),
link: new URL(`_next/data/${nextBuildId}/the-batch/${item.slug}.json`, rootUrl).href,
category: item.tags.map((t) => t.name),
guid,
id: guid,
content: {
html: description,
text: item.excerpt ?? item.custom_excerpt,
},
image,
banner: image,
language,
};
});
items = await Promise.all(
items.map((item) =>
cache.tryGet(item.link, async () => {
const detailResponse = await ofetch(item.link);
const post = detailResponse.pageProps?.post ?? undefined;
if (!post) {
return item;
}
const $$ = load(post.html);
$$('a').each((_, ele) => {
if (ele.attribs.href?.includes('utm_campaign')) {
const url = new URL(ele.attribs.href);
url.searchParams.delete('utm_campaign');
url.searchParams.delete('utm_source');
url.searchParams.delete('utm_medium');
url.searchParams.delete('_hsenc');
ele.attribs.href = url.href;
}
});
const title = post.title;
const description = art(path.join(__dirname, 'templates/description.art'), {
images: post.feature_image
? [
{
src: post.feature_image,
alt: post.feature_image_alt,
},
]
: undefined,
intro: post.excerpt ?? post.custom_excerpt,
description: $$.html(),
});
const guid = `the-batch-${post.slug}`;
const image = post.feature_image;
item.title = title;
item.description = description;
item.pubDate = parseDate(post.published_at);
item.link = new URL(`the-batch/${post.slug}`, rootUrl).href;
item.category = post.tags.map((t) => t.name);
item.author = post.authors.map((a) => a.name).join('/');
item.guid = guid;
item.id = guid;
item.content = {
html: description,
text: post.excerpt ?? post.custom_excerpt,
};
item.image = image;
item.banner = image;
item.updated = parseDate(post.updated_at);
item.language = language;
return item;
})
)
);
const image = new URL($('meta[property="og:image"]').prop('content'), rootUrl).href;
return {
title: $('title').text(),
description: $('meta[property="og:description"]').prop('content'),
link: currentUrl,
item: items,
allowEmpty: true,
image,
author: $('meta[property="og:site_name"]').prop('content'),
language,
};
};
export const route: Route = {
path: '/the-batch/:tag{.+}?',
name: 'The Batch',
url: 'www.deeplearning.ai',
maintainers: ['nczitzk', 'juvenn', 'TonyRL'],
handler,
example: '/deeplearning/the-batch',
parameters: { tag: 'Tag, Weekly Issues by default' },
description: `::: tip
If you subscribe to [Data Points](https://www.deeplearning.ai/the-batch/tag/data-points/)，where the URL is \`https://www.deeplearning.ai/the-batch/tag/data-points/\`, extract the part \`https://www.deeplearning.ai/the-batch/tag\` to the end, which is \`data-points\`, and use it as the parameter to fill in. Therefore, the route will be [\`/deeplearning/the-batch/data-points\`](https://rsshub.app/deeplearning/the-batch/data-points).
:::
| Tag | ID |
| ---------------------------------------------------------------------- | -------------------------------------------------------------------- |
| [Weekly Issues](https://www.deeplearning.ai/the-batch/) | [*null*](https://rsshub.app/deeplearning/the-batch) |
| [Andrew's Letters](https://www.deeplearning.ai/the-batch/tag/letters/) | [letters](https://rsshub.app/deeplearning/the-batch/letters) |
| [Data Points](https://www.deeplearning.ai/the-batch/tag/data-points/) | [data-points](https://rsshub.app/deeplearning/the-batch/data-points) |
| [ML Research](https://www.deeplearning.ai/the-batch/tag/research/) | [research](https://rsshub.app/deeplearning/the-batch/research) |
| [Business](https://www.deeplearning.ai/the-batch/tag/business/) | [business](https://rsshub.app/deeplearning/the-batch/business) |
| [Science](https://www.deeplearning.ai/the-batch/tag/science/) | [science](https://rsshub.app/deeplearning/the-batch/science) |
| [AI & Society](https://www.deeplearning.ai/the-batch/tag/ai-society/) | [ai-society](https://rsshub.app/deeplearning/the-batch/ai-society) |
| [Culture](https://www.deeplearning.ai/the-batch/tag/culture/) | [culture](https://rsshub.app/deeplearning/the-batch/culture) |
| [Hardware](https://www.deeplearning.ai/the-batch/tag/hardware/) | [hardware](https://rsshub.app/deeplearning/the-batch/hardware) |
| [AI Careers](https://www.deeplearning.ai/the-batch/tag/ai-careers/) | [ai-careers](https://rsshub.app/deeplearning/the-batch/ai-careers) |
#### [Letters from Andrew Ng](https://www.deeplearning.ai/the-batch/tag/letters/)
| Tag | ID |
| --------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- |
| [All](https://www.deeplearning.ai/the-batch/tag/letters/) | [letters](https://rsshub.app/deeplearning/the-batch/letters) |
| [Personal Insights](https://www.deeplearning.ai/the-batch/tag/personal-insights/) | [personal-insights](https://rsshub.app/deeplearning/the-batch/personal-insights) |
| [Technical Insights](https://www.deeplearning.ai/the-batch/tag/technical-insights/) | [technical-insights](https://rsshub.app/deeplearning/the-batch/technical-insights) |
| [Business Insights](https://www.deeplearning.ai/the-batch/tag/business-insights/) | [business-insights](https://rsshub.app/deeplearning/the-batch/business-insights) |
| [Tech & Society](https://www.deeplearning.ai/the-batch/tag/tech-society/) | [tech-society](https://rsshub.app/deeplearning/the-batch/tech-society) |
| [DeepLearning.AI News](https://www.deeplearning.ai/the-batch/tag/deeplearning-ai-news/) | [deeplearning-ai-news](https://rsshub.app/deeplearning/the-batch/deeplearning-ai-news) |
| [AI Careers](https://www.deeplearning.ai/the-batch/tag/ai-careers/) | [ai-careers](https://rsshub.app/deeplearning/the-batch/ai-careers) |
| [Just For Fun](https://www.deeplearning.ai/the-batch/tag/just-for-fun/) | [just-for-fun](https://rsshub.app/deeplearning/the-batch/just-for-fun) |
| [Learning & Education](https://www.deeplearning.ai/the-batch/tag/learning-education/) | [learning-education](https://rsshub.app/deeplearning/the-batch/learning-education) |
`,
categories: ['programming'],
features: {
requireConfig: false,
requirePuppeteer: false,
antiCrawler: false,
supportRadar: true,
supportBT: false,
supportPodcast: false,
supportScihub: false,
},
radar: [
{
source: ['www.deeplearning.ai/the-batch', 'www.deeplearning.ai/the-batch/tag/:tag/'],
target: (params) => {
const tag = params.tag;
return `/the-batch${tag ? `/${tag}` : ''}`;
},
},
{
title: 'Weekly Issues',
source: ['www.deeplearning.ai/the-batch/'],
target: '/the-batch',
},
{
title: "Andrew's Letters",
source: ['www.deeplearning.ai/the-batch/tag/letters/'],
target: '/the-batch/letters',
},
{
title: 'Data Points',
source: ['www.deeplearning.ai/the-batch/tag/data-points/'],
target: '/the-batch/data-points',
},
{
title: 'ML Research',
source: ['www.deeplearning.ai/the-batch/tag/research/'],
target: '/the-batch/research',
},
{
title: 'Business',
source: ['www.deeplearning.ai/the-batch/tag/business/'],
target: '/the-batch/business',
},
{
title: 'Science',
source: ['www.deeplearning.ai/the-batch/tag/science/'],
target: '/the-batch/science',
},
{
title: 'AI & Society',
source: ['www.deeplearning.ai/the-batch/tag/ai-society/'],
target: '/the-batch/ai-society',
},
{
title: 'Culture',
source: ['www.deeplearning.ai/the-batch/tag/culture/'],
target: '/the-batch/culture',
},
{
title: 'Hardware',
source: ['www.deeplearning.ai/the-batch/tag/hardware/'],
target: '/the-batch/hardware',
},
{
title: 'AI Careers',
source: ['www.deeplearning.ai/the-batch/tag/ai-careers/'],
target: '/the-batch/ai-careers',
},
{
title: 'Letters from Andrew Ng - All',
source: ['www.deeplearning.ai/the-batch/tag/letters/'],
target: '/the-batch/letters',
},
{
title: 'Letters from Andrew Ng - Personal Insights',
source: ['www.deeplearning.ai/the-batch/tag/personal-insights/'],
target: '/the-batch/personal-insights',
},
{
title: 'Letters from Andrew Ng - Technical Insights',
source: ['www.deeplearning.ai/the-batch/tag/technical-insights/'],
target: '/the-batch/technical-insights',
},
{
title: 'Letters from Andrew Ng - Business Insights',
source: ['www.deeplearning.ai/the-batch/tag/business-insights/'],
target: '/the-batch/business-insights',
},
{
title: 'Letters from Andrew Ng - Tech & Society',
source: ['www.deeplearning.ai/the-batch/tag/tech-society/'],
target: '/the-batch/tech-society',
},
{
title: 'Letters from Andrew Ng - DeepLearning.AI News',
source: ['www.deeplearning.ai/the-batch/tag/deeplearning-ai-news/'],
target: '/the-batch/deeplearning-ai-news',
},
{
title: 'Letters from Andrew Ng - AI Careers',
source: ['www.deeplearning.ai/the-batch/tag/ai-careers/'],
target: '/the-batch/ai-careers',
},
{
title: 'Letters from Andrew Ng - Just For Fun',
source: ['www.deeplearning.ai/the-batch/tag/just-for-fun/'],
target: '/the-batch/just-for-fun',
},
{
title: 'Letters from Andrew Ng - Learning & Education',
source: ['www.deeplearning.ai/the-batch/tag/learning-education/'],
target: '/the-batch/learning-education',
},
],
};