|
10 | 10 | }, |
11 | 11 | { |
12 | 12 | "cell_type": "code", |
13 | | - "execution_count": 2, |
| 13 | + "execution_count": 1, |
14 | 14 | "metadata": {}, |
15 | 15 | "outputs": [], |
16 | 16 | "source": [ |
|
35 | 35 | }, |
36 | 36 | { |
37 | 37 | "cell_type": "code", |
38 | | - "execution_count": 3, |
| 38 | + "execution_count": 4, |
39 | 39 | "metadata": {}, |
40 | 40 | "outputs": [], |
41 | 41 | "source": [ |
|
293 | 293 | }, |
294 | 294 | { |
295 | 295 | "cell_type": "code", |
296 | | - "execution_count": null, |
| 296 | + "execution_count": 7, |
297 | 297 | "metadata": {}, |
298 | | - "outputs": [], |
| 298 | + "outputs": [ |
| 299 | + { |
| 300 | + "data": { |
| 301 | + "text/plain": [ |
| 302 | + "{'code': 200,\n", |
| 303 | + " 'message': 'Job edited',\n", |
| 304 | + " 'data': {'id': 1264450,\n", |
| 305 | + " 'key': '8cee3ead87a38cc1f7f3cf9298b7e58e16406e05',\n", |
| 306 | + " 'reference': 'my_custom_reference',\n", |
| 307 | + " 'board_key': '7fce016712fa373456ef279c297da5009a2020d9',\n", |
| 308 | + " 'board': {'key': '7fce016712fa373456ef279c297da5009a2020d9',\n", |
| 309 | + " 'name': 'vulcain_test',\n", |
| 310 | + " 'type': 'api',\n", |
| 311 | + " 'subtype': 'python',\n", |
| 312 | + " 'environment': 'production'},\n", |
| 313 | + " 'name': 'Data Engineer',\n", |
| 314 | + " 'url': 'https://www.pole-emploi.ai/jobs/data_engineer',\n", |
| 315 | + " 'picture': None,\n", |
| 316 | + " 'summary': 'As an engineer for the Data Engineering Infrastructure team, you will design, build, scale, and evolve our data engineering platform, services and tooling. Your work will have a critical impact on all areas of business:supporting detailed internal analytics, calculating customer usage, securing our platform, and much more.',\n", |
| 317 | + " 'location': {'text': 'Dampierre en Burly (45)',\n", |
| 318 | + " 'lat': None,\n", |
| 319 | + " 'lng': None,\n", |
| 320 | + " 'gmaps': None,\n", |
| 321 | + " 'fields': []},\n", |
| 322 | + " 'archive': None,\n", |
| 323 | + " 'archived_at': None,\n", |
| 324 | + " 'updated_at': '2023-06-21T15:54:45+0000',\n", |
| 325 | + " 'created_at': '2023-06-21T15:54:45+0000',\n", |
| 326 | + " 'sections': [{'name': 'section 1',\n", |
| 327 | + " 'title': 'title section 1',\n", |
| 328 | + " 'description': 'text section 1'}],\n", |
| 329 | + " 'culture': 'This is a New CULTURE 123!!',\n", |
| 330 | + " 'responsibilities': 'FILL THIS WITH A TEXT ABOUT THE RESPONSIBILITIES OF THE JOB',\n", |
| 331 | + " 'requirements': 'FILL THIS WITH A TEXT ABOUT THE REQUIREMENTS OF THE JOB',\n", |
| 332 | + " 'benefits': 'FILL THIS WITH A TEXT ABOUT THE BENEFITS OF THE JOB',\n", |
| 333 | + " 'interviews': 'FILL THIS WITH A TEXT ABOUT THE INTERVIEWS OF THE JOB',\n", |
| 334 | + " 'skills': [{'name': 'python', 'value': None, 'type': 'hard'},\n", |
| 335 | + " {'name': 'spark', 'value': 0.9, 'type': 'hard'}],\n", |
| 336 | + " 'languages': [{'name': 'english', 'value': None},\n", |
| 337 | + " {'name': 'french', 'value': None}],\n", |
| 338 | + " 'certifications': [],\n", |
| 339 | + " 'courses': [],\n", |
| 340 | + " 'tasks': [],\n", |
| 341 | + " 'tags': [{'name': 'company', 'value': 'Google'}],\n", |
| 342 | + " 'metadatas': [{'name': 'metadata example', 'value': 'metadata'}],\n", |
| 343 | + " 'ranges_float': [{'name': 'salary',\n", |
| 344 | + " 'value_min': 45000,\n", |
| 345 | + " 'value_max': 50000,\n", |
| 346 | + " 'unit': 'eur'}],\n", |
| 347 | + " 'ranges_date': [{'name': 'interview_dates',\n", |
| 348 | + " 'value_min': '2023-05-18T21:59',\n", |
| 349 | + " 'value_max': '2023-09-15T21:59'}]}}" |
| 350 | + ] |
| 351 | + }, |
| 352 | + "execution_count": 7, |
| 353 | + "metadata": {}, |
| 354 | + "output_type": "execute_result" |
| 355 | + } |
| 356 | + ], |
299 | 357 | "source": [ |
300 | 358 | "# Edit a job : edit is a Put not a Patch so you need to provide all the fields\n", |
301 | 359 | "\n", |
302 | 360 | "# let's get the job by reference\n", |
303 | | - "reference = \"a2n1j000000g0AAAAY\" # <-- Replace with your job reference\n", |
| 361 | + "reference = \"my_custom_reference\" # <-- Replace with your job reference\n", |
304 | 362 | "\n", |
305 | 363 | "response = client.job.storing.get(board_key=board_key, reference=reference)\n", |
306 | 364 | "\n", |
307 | 365 | "job = response['data']\n", |
308 | 366 | "\n", |
309 | 367 | "# edit a field or more \n", |
310 | | - "job['culture'] = \"This is a New CULTURE !!!\"\n", |
| 368 | + "job['culture'] = \"This is a New CULTURE 123!!\"\n", |
311 | 369 | "\n", |
312 | 370 | "# edit the job\n", |
313 | 371 | "response = client.job.storing.edit(board_key=board_key,\n", |
314 | | - " key=job['key'],\n", |
| 372 | + " # key=job['key'], # This is Optional, fand left for backward compatibility\n", |
315 | 373 | " job_json=job)\n", |
316 | 374 | "\n", |
317 | 375 | "response" |
318 | 376 | ] |
319 | 377 | }, |
| 378 | + { |
| 379 | + "cell_type": "code", |
| 380 | + "execution_count": 8, |
| 381 | + "metadata": {}, |
| 382 | + "outputs": [ |
| 383 | + { |
| 384 | + "data": { |
| 385 | + "text/plain": [ |
| 386 | + "'This is a New CULTURE !!'" |
| 387 | + ] |
| 388 | + }, |
| 389 | + "execution_count": 8, |
| 390 | + "metadata": {}, |
| 391 | + "output_type": "execute_result" |
| 392 | + } |
| 393 | + ], |
| 394 | + "source": [ |
| 395 | + "response[\"data\"][\"culture\"]" |
| 396 | + ] |
| 397 | + }, |
320 | 398 | { |
321 | 399 | "cell_type": "code", |
322 | 400 | "execution_count": null, |
|
341 | 419 | "name": "python", |
342 | 420 | "nbconvert_exporter": "python", |
343 | 421 | "pygments_lexer": "ipython3", |
344 | | - "version": "3.8.6" |
| 422 | + "version": "3.10.5" |
345 | 423 | }, |
346 | 424 | "orig_nbformat": 4 |
347 | 425 | }, |
|
0 commit comments