curl --request GET \
  --url https://api.clair.im/v1/jobs \
  --header 'Authorization: Bearer <token>'

import requests

url = "https://api.clair.im/v1/jobs"

headers = {"Authorization": "Bearer <token>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};

fetch('https://api.clair.im/v1/jobs', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.clair.im/v1/jobs",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.clair.im/v1/jobs"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Authorization", "Bearer <token>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://api.clair.im/v1/jobs")
  .header("Authorization", "Bearer <token>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.clair.im/v1/jobs")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'

response = http.request(request)
puts response.read_body

{
  "jobs": [
    {
      "posting_url": "<string>",
      "id": "fd6b984d-f7f4-4ca8-b68e-34b88a4ec299",
      "title": "Machine Learning Intern",
      "company": "Example Labs",
      "department": "Engineering",
      "team": "Applied AI",
      "location": "Berlin, Germany",
      "locations": [
        "<string>"
      ],
      "country": "DE",
      "workplace_type": "remote",
      "employment_type": "Intern",
      "apply_url": "<string>",
      "posted_at": "2023-11-07T05:31:56Z",
      "updated_at": "2023-11-07T05:31:56Z",
      "compensation": {
        "min": 25,
        "max": 35,
        "currency": "EUR",
        "interval": "hour",
        "summary": "<string>",
        "source": "ats"
      },
      "seniority": "intern",
      "track": "ic",
      "title_family": "machine-learning-engineer",
      "skills": [
        "Python",
        "PyTorch"
      ],
      "description_excerpt": "<string>",
      "description_available": true,
      "first_seen_at": "2023-11-07T05:31:56Z",
      "last_verified_at": "2023-11-07T05:31:56Z",
      "source": {
        "provider": "greenhouse",
        "board": "examplelabs",
        "external_id": "4512338005"
      }
    }
  ],
  "meta": {
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "generated_at": "2023-11-07T05:31:56Z",
    "count": 25,
    "limit": 25,
    "sort": "posted_at",
    "has_more": true,
    "next_cursor": "<string>",
    "total": 123,
    "total_is_exact": true,
    "index": {
      "status": "healthy",
      "as_of": "2023-11-07T05:31:56Z",
      "active_boards": 123,
      "stale_boards": 123
    }
  }
}

{
  "error": "bad_cursor",
  "detail": "<string>"
}

{
  "error": "bad_cursor",
  "detail": "<string>"
}

{
  "error": "bad_cursor",
  "detail": "<string>"
}

{
  "error": "bad_cursor",
  "detail": "<string>"
}

{
  "error": "bad_cursor",
  "detail": "<string>"
}