# linkme

Scrapes LinkedIn job listings into a local CSV. Run it daily, delete rows you've applied to.

## Usage

```bash
bun fetch
```

No setup needed. Results are appended to `jobs.csv` — reruns are safe, already-seen jobs are skipped by ID.

## Output

`jobs.csv` — one row per job:

| column | description |
|---|---|
| `date_found` | date you ran the fetch |
| `posted_at` | date the job was posted on LinkedIn |
| `search` | which search config matched it |
| `title` | job title |
| `company` | hiring company |
| `link` | canonical LinkedIn job URL |

Open in any spreadsheet app. Delete rows as you apply or dismiss.

## How it works

- **Paginated scraping** — fetches up to 6 pages per search (150 jobs) with a 400 ms delay between pages to avoid rate limiting
- **Card-boundary-safe parsing** — each job card is isolated before extracting fields, preventing content from adjacent cards bleeding into company or date values
- **Language filter** — drops German (`m/w/d`, umlauts, gender-marked vocabulary) and French (`H/F`, accented characters) job titles automatically
- **Software-role filter** — requires the title to contain a relevant term (software, developer, data, AI, backend, devops, platform, architect, etc.) — eliminates aviation, mechanical, and pharma-process roles that match "Engineer" broadly
- **Global deduplication** — job IDs are indexed from the existing CSV on startup; jobs you've already seen are never re-added, even if you delete and re-run
- **30-day recency** — only fetches jobs posted in the last month (`f_TPR=r2592000`)

## Configure searches

Edit `config.ts`:

```ts
const KEYWORDS = [
  "Software Engineer",
  "Full Stack Engineer",
  "Data Engineer",
  "AI Engineer",
  "Ruby on Rails",
  "Python",
  // add or remove freely
].join(" OR ");

export const searches: SearchConfig[] = [
  {
    label: "Basel (city)",
    keywords: KEYWORDS,
    geoId: "103383283",
    location: "Basel",
    workType: ["onsite", "hybrid"],
    timePosted: "month",
  },
];
```

`geoId` values for the Basel area:
- `103383283` — Basel (city)
- `90009885` — Basel Metropolitan Area
- `107117530` — Basel-Country

You can also paste any LinkedIn search URL directly as `url:` instead of building from filters.