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7
.pre-commit-config.yaml
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7
.pre-commit-config.yaml
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@@ -0,0 +1,7 @@
|
|||||||
|
repos:
|
||||||
|
- repo: https://github.com/psf/black
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||||||
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rev: 24.2.0
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||||||
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hooks:
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||||||
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- id: black
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||||||
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language_version: python
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||||||
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args: [--line-length=88, --quiet]
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134
README.md
134
README.md
@@ -11,17 +11,14 @@ work with us.*
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|||||||
|
|
||||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
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- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
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||||||
- Aggregates the job postings in a Pandas DataFrame
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- Aggregates the job postings in a Pandas DataFrame
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||||||
- Proxy support (HTTP/S, SOCKS)
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- Proxies support
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||||||
|
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||||||
[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
|
|
||||||
Updated for release v1.1.3
|
|
||||||
|
|
||||||

|

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|
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### Installation
|
### Installation
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|
|
||||||
```
|
```
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||||||
pip install python-jobspy
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pip install -U python-jobspy
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||||||
```
|
```
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||||||
|
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_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
|
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
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||||||
@@ -37,18 +34,22 @@ jobs = scrape_jobs(
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search_term="software engineer",
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search_term="software engineer",
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location="Dallas, TX",
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location="Dallas, TX",
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results_wanted=20,
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results_wanted=20,
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||||||
hours_old=72, # (only linkedin is hour specific, others round up to days old)
|
hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
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country_indeed='USA' # only needed for indeed / glassdoor
|
country_indeed='USA', # only needed for indeed / glassdoor
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||||||
|
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||||||
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# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
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||||||
|
# proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
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||||||
|
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||||||
)
|
)
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||||||
print(f"Found {len(jobs)} jobs")
|
print(f"Found {len(jobs)} jobs")
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print(jobs.head())
|
print(jobs.head())
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jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
|
jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_excel
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||||||
```
|
```
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||||||
|
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### Output
|
### Output
|
||||||
|
|
||||||
```
|
```
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||||||
SITE TITLE COMPANY_NAME CITY STATE JOB_TYPE INTERVAL MIN_AMOUNT MAX_AMOUNT JOB_URL DESCRIPTION
|
SITE TITLE COMPANY CITY STATE JOB_TYPE INTERVAL MIN_AMOUNT MAX_AMOUNT JOB_URL DESCRIPTION
|
||||||
indeed Software Engineer AMERICAN SYSTEMS Arlington VA None yearly 200000 150000 https://www.indeed.com/viewjob?jk=5e409e577046... THIS POSITION COMES WITH A 10K SIGNING BONUS!...
|
indeed Software Engineer AMERICAN SYSTEMS Arlington VA None yearly 200000 150000 https://www.indeed.com/viewjob?jk=5e409e577046... THIS POSITION COMES WITH A 10K SIGNING BONUS!...
|
||||||
indeed Senior Software Engineer TherapyNotes.com Philadelphia PA fulltime yearly 135000 110000 https://www.indeed.com/viewjob?jk=da39574a40cb... About Us TherapyNotes is the national leader i...
|
indeed Senior Software Engineer TherapyNotes.com Philadelphia PA fulltime yearly 135000 110000 https://www.indeed.com/viewjob?jk=da39574a40cb... About Us TherapyNotes is the national leader i...
|
||||||
linkedin Software Engineer - Early Career Lockheed Martin Sunnyvale CA fulltime yearly None None https://www.linkedin.com/jobs/view/3693012711 Description:By bringing together people that u...
|
linkedin Software Engineer - Early Career Lockheed Martin Sunnyvale CA fulltime yearly None None https://www.linkedin.com/jobs/view/3693012711 Description:By bringing together people that u...
|
||||||
@@ -60,24 +61,71 @@ zip_recruiter Software Developer TEKsystems Phoenix
|
|||||||
### Parameters for `scrape_jobs()`
|
### Parameters for `scrape_jobs()`
|
||||||
|
|
||||||
```plaintext
|
```plaintext
|
||||||
Required
|
|
||||||
├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
|
|
||||||
└── search_term (str)
|
|
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Optional
|
Optional
|
||||||
├── location (int)
|
├── site_name (list|str):
|
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├── distance (int): in miles
|
| linkedin, zip_recruiter, indeed, glassdoor
|
||||||
├── job_type (enum): fulltime, parttime, internship, contract
|
| (default is all four)
|
||||||
├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
|
│
|
||||||
|
├── search_term (str)
|
||||||
|
│
|
||||||
|
├── location (str)
|
||||||
|
│
|
||||||
|
├── distance (int):
|
||||||
|
| in miles, default 50
|
||||||
|
│
|
||||||
|
├── job_type (str):
|
||||||
|
| fulltime, parttime, internship, contract
|
||||||
|
│
|
||||||
|
├── proxies ():
|
||||||
|
| in format ['user:pass@host:port', 'localhost']
|
||||||
|
| each job board will round robin through the proxies
|
||||||
|
│
|
||||||
├── is_remote (bool)
|
├── is_remote (bool)
|
||||||
├── full_description (bool): fetches full description for LinkedIn (slower)
|
│
|
||||||
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
|
├── results_wanted (int):
|
||||||
├── easy_apply (bool): filters for jobs that are hosted on the job board site
|
| number of job results to retrieve for each site specified in 'site_name'
|
||||||
├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
|
│
|
||||||
├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
|
├── easy_apply (bool):
|
||||||
├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
|
| filters for jobs that are hosted on the job board site
|
||||||
├── hours_old (int): filters jobs by the number of hours since the job was posted (all but LinkedIn rounds up to next day)
|
│
|
||||||
|
├── description_format (str):
|
||||||
|
| markdown, html (Format type of the job descriptions. Default is markdown.)
|
||||||
|
│
|
||||||
|
├── offset (int):
|
||||||
|
| starts the search from an offset (e.g. 25 will start the search from the 25th result)
|
||||||
|
│
|
||||||
|
├── hours_old (int):
|
||||||
|
| filters jobs by the number of hours since the job was posted
|
||||||
|
| (ZipRecruiter and Glassdoor round up to next day.)
|
||||||
|
│
|
||||||
|
├── verbose (int) {0, 1, 2}:
|
||||||
|
| Controls the verbosity of the runtime printouts
|
||||||
|
| (0 prints only errors, 1 is errors+warnings, 2 is all logs. Default is 2.)
|
||||||
|
|
||||||
|
├── linkedin_fetch_description (bool):
|
||||||
|
| fetches full description and direct job url for LinkedIn (Increases requests by O(n))
|
||||||
|
│
|
||||||
|
├── linkedin_company_ids (list[int]):
|
||||||
|
| searches for linkedin jobs with specific company ids
|
||||||
|
|
|
||||||
|
├── country_indeed (str):
|
||||||
|
| filters the country on Indeed & Glassdoor (see below for correct spelling)
|
||||||
```
|
```
|
||||||
|
|
||||||
|
```
|
||||||
|
├── Indeed limitations:
|
||||||
|
| Only one from this list can be used in a search:
|
||||||
|
| - hours_old
|
||||||
|
| - job_type & is_remote
|
||||||
|
| - easy_apply
|
||||||
|
│
|
||||||
|
└── LinkedIn limitations:
|
||||||
|
| Only one from this list can be used in a search:
|
||||||
|
| - hours_old
|
||||||
|
| - easy_apply
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
### JobPost Schema
|
### JobPost Schema
|
||||||
|
|
||||||
```plaintext
|
```plaintext
|
||||||
@@ -99,24 +147,26 @@ JobPost
|
|||||||
│ └── currency (enum)
|
│ └── currency (enum)
|
||||||
└── date_posted (date)
|
└── date_posted (date)
|
||||||
└── emails (str)
|
└── emails (str)
|
||||||
└── num_urgent_words (int)
|
|
||||||
└── is_remote (bool)
|
└── is_remote (bool)
|
||||||
|
|
||||||
|
Indeed specific
|
||||||
|
├── company_country (str)
|
||||||
|
└── company_addresses (str)
|
||||||
|
└── company_industry (str)
|
||||||
|
└── company_employees_label (str)
|
||||||
|
└── company_revenue_label (str)
|
||||||
|
└── company_description (str)
|
||||||
|
└── ceo_name (str)
|
||||||
|
└── ceo_photo_url (str)
|
||||||
|
└── logo_photo_url (str)
|
||||||
|
└── banner_photo_url (str)
|
||||||
```
|
```
|
||||||
|
|
||||||
### Exceptions
|
|
||||||
|
|
||||||
The following exceptions may be raised when using JobSpy:
|
|
||||||
|
|
||||||
* `LinkedInException`
|
|
||||||
* `IndeedException`
|
|
||||||
* `ZipRecruiterException`
|
|
||||||
* `GlassdoorException`
|
|
||||||
|
|
||||||
## Supported Countries for Job Searching
|
## Supported Countries for Job Searching
|
||||||
|
|
||||||
### **LinkedIn**
|
### **LinkedIn**
|
||||||
|
|
||||||
LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
|
LinkedIn searches globally & uses only the `location` parameter.
|
||||||
|
|
||||||
### **ZipRecruiter**
|
### **ZipRecruiter**
|
||||||
|
|
||||||
@@ -146,10 +196,14 @@ You can specify the following countries when searching on Indeed (use the exact
|
|||||||
| South Korea | Spain* | Sweden | Switzerland* |
|
| South Korea | Spain* | Sweden | Switzerland* |
|
||||||
| Taiwan | Thailand | Turkey | Ukraine |
|
| Taiwan | Thailand | Turkey | Ukraine |
|
||||||
| United Arab Emirates | UK* | USA* | Uruguay |
|
| United Arab Emirates | UK* | USA* | Uruguay |
|
||||||
| Venezuela | Vietnam | | |
|
| Venezuela | Vietnam* | | |
|
||||||
|
|
||||||
|
|
||||||
Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
|
## Notes
|
||||||
|
* Indeed is the best scraper currently with no rate limiting.
|
||||||
|
* All the job board endpoints are capped at around 1000 jobs on a given search.
|
||||||
|
* LinkedIn is the most restrictive and usually rate limits around the 10th page with one ip. Proxies are a must basically.
|
||||||
|
|
||||||
## Frequently Asked Questions
|
## Frequently Asked Questions
|
||||||
|
|
||||||
---
|
---
|
||||||
@@ -163,11 +217,7 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
|
|||||||
**Q: Received a response code 429?**
|
**Q: Received a response code 429?**
|
||||||
**A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:
|
**A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:
|
||||||
|
|
||||||
- Waiting some time between scrapes (site-dependent).
|
- Wait some time between scrapes (site-dependent).
|
||||||
- Trying a VPN or proxy to change your IP address.
|
- Try using the proxies param to change your IP address.
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
@@ -1,30 +0,0 @@
|
|||||||
from jobspy import scrape_jobs
|
|
||||||
import pandas as pd
|
|
||||||
|
|
||||||
jobs: pd.DataFrame = scrape_jobs(
|
|
||||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
|
|
||||||
search_term="software engineer",
|
|
||||||
location="Dallas, TX",
|
|
||||||
results_wanted=25, # be wary the higher it is, the more likey you'll get blocked (rotating proxy can help tho)
|
|
||||||
country_indeed="USA",
|
|
||||||
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
|
|
||||||
)
|
|
||||||
|
|
||||||
# formatting for pandas
|
|
||||||
pd.set_option("display.max_columns", None)
|
|
||||||
pd.set_option("display.max_rows", None)
|
|
||||||
pd.set_option("display.width", None)
|
|
||||||
pd.set_option("display.max_colwidth", 50) # set to 0 to see full job url / desc
|
|
||||||
|
|
||||||
# 1: output to console
|
|
||||||
print(jobs)
|
|
||||||
|
|
||||||
# 2: output to .csv
|
|
||||||
jobs.to_csv("./jobs.csv", index=False)
|
|
||||||
print("outputted to jobs.csv")
|
|
||||||
|
|
||||||
# 3: output to .xlsx
|
|
||||||
# jobs.to_xlsx('jobs.xlsx', index=False)
|
|
||||||
|
|
||||||
# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
|
|
||||||
# display(jobs)
|
|
||||||
@@ -1,167 +0,0 @@
|
|||||||
{
|
|
||||||
"cells": [
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "00a94b47-f47b-420f-ba7e-714ef219c006",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"from jobspy import scrape_jobs\n",
|
|
||||||
"import pandas as pd\n",
|
|
||||||
"from IPython.display import display, HTML"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "9f773e6c-d9fc-42cc-b0ef-63b739e78435",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"pd.set_option('display.max_columns', None)\n",
|
|
||||||
"pd.set_option('display.max_rows', None)\n",
|
|
||||||
"pd.set_option('display.width', None)\n",
|
|
||||||
"pd.set_option('display.max_colwidth', 50)"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "1253c1f8-9437-492e-9dd3-e7fe51099420",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# example 1 (no hyperlinks, USA)\n",
|
|
||||||
"jobs = scrape_jobs(\n",
|
|
||||||
" site_name=[\"linkedin\"],\n",
|
|
||||||
" location='san francisco',\n",
|
|
||||||
" search_term=\"engineer\",\n",
|
|
||||||
" results_wanted=5,\n",
|
|
||||||
"\n",
|
|
||||||
" # use if you want to use a proxy\n",
|
|
||||||
" # proxy=\"socks5://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
|
|
||||||
" proxy=\"http://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
|
|
||||||
" #proxy=\"https://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
|
|
||||||
")\n",
|
|
||||||
"display(jobs)"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "6a581b2d-f7da-4fac-868d-9efe143ee20a",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# example 2 - remote USA & hyperlinks\n",
|
|
||||||
"jobs = scrape_jobs(\n",
|
|
||||||
" site_name=[\"linkedin\", \"zip_recruiter\", \"indeed\"],\n",
|
|
||||||
" # location='san francisco',\n",
|
|
||||||
" search_term=\"software engineer\",\n",
|
|
||||||
" country_indeed=\"USA\",\n",
|
|
||||||
" hyperlinks=True,\n",
|
|
||||||
" is_remote=True,\n",
|
|
||||||
" results_wanted=5, \n",
|
|
||||||
")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "fe8289bc-5b64-4202-9a64-7c117c83fd9a",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# use if hyperlinks=True\n",
|
|
||||||
"html = jobs.to_html(escape=False)\n",
|
|
||||||
"# change max-width: 200px to show more or less of the content\n",
|
|
||||||
"truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
|
|
||||||
"display(HTML(truncate_width))"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "951c2fe1-52ff-407d-8bb1-068049b36777",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# example 3 - with hyperlinks, international - linkedin (no zip_recruiter)\n",
|
|
||||||
"jobs = scrape_jobs(\n",
|
|
||||||
" site_name=[\"linkedin\"],\n",
|
|
||||||
" location='berlin',\n",
|
|
||||||
" search_term=\"engineer\",\n",
|
|
||||||
" hyperlinks=True,\n",
|
|
||||||
" results_wanted=5,\n",
|
|
||||||
" easy_apply=True\n",
|
|
||||||
")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "1e37a521-caef-441c-8fc2-2eb5b2e7da62",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# use if hyperlinks=True\n",
|
|
||||||
"html = jobs.to_html(escape=False)\n",
|
|
||||||
"# change max-width: 200px to show more or less of the content\n",
|
|
||||||
"truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
|
|
||||||
"display(HTML(truncate_width))"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "0650e608-0b58-4bf5-ae86-68348035b16a",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# example 4 - international indeed (no zip_recruiter)\n",
|
|
||||||
"jobs = scrape_jobs(\n",
|
|
||||||
" site_name=[\"indeed\"],\n",
|
|
||||||
" search_term=\"engineer\",\n",
|
|
||||||
" country_indeed = \"China\",\n",
|
|
||||||
" hyperlinks=True\n",
|
|
||||||
")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"id": "40913ac8-3f8a-4d7e-ac47-afb88316432b",
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# use if hyperlinks=True\n",
|
|
||||||
"html = jobs.to_html(escape=False)\n",
|
|
||||||
"# change max-width: 200px to show more or less of the content\n",
|
|
||||||
"truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
|
|
||||||
"display(HTML(truncate_width))"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"metadata": {
|
|
||||||
"kernelspec": {
|
|
||||||
"display_name": "Python 3 (ipykernel)",
|
|
||||||
"language": "python",
|
|
||||||
"name": "python3"
|
|
||||||
},
|
|
||||||
"language_info": {
|
|
||||||
"codemirror_mode": {
|
|
||||||
"name": "ipython",
|
|
||||||
"version": 3
|
|
||||||
},
|
|
||||||
"file_extension": ".py",
|
|
||||||
"mimetype": "text/x-python",
|
|
||||||
"name": "python",
|
|
||||||
"nbconvert_exporter": "python",
|
|
||||||
"pygments_lexer": "ipython3",
|
|
||||||
"version": "3.11.5"
|
|
||||||
}
|
|
||||||
},
|
|
||||||
"nbformat": 4,
|
|
||||||
"nbformat_minor": 5
|
|
||||||
}
|
|
||||||
@@ -1,77 +0,0 @@
|
|||||||
from jobspy import scrape_jobs
|
|
||||||
import pandas as pd
|
|
||||||
import os
|
|
||||||
import time
|
|
||||||
|
|
||||||
# creates csv a new filename if the jobs.csv already exists.
|
|
||||||
csv_filename = "jobs.csv"
|
|
||||||
counter = 1
|
|
||||||
while os.path.exists(csv_filename):
|
|
||||||
csv_filename = f"jobs_{counter}.csv"
|
|
||||||
counter += 1
|
|
||||||
|
|
||||||
# results wanted and offset
|
|
||||||
results_wanted = 1000
|
|
||||||
offset = 0
|
|
||||||
|
|
||||||
all_jobs = []
|
|
||||||
|
|
||||||
# max retries
|
|
||||||
max_retries = 3
|
|
||||||
|
|
||||||
# nuumber of results at each iteration
|
|
||||||
results_in_each_iteration = 30
|
|
||||||
|
|
||||||
while len(all_jobs) < results_wanted:
|
|
||||||
retry_count = 0
|
|
||||||
while retry_count < max_retries:
|
|
||||||
print("Doing from", offset, "to", offset + results_in_each_iteration, "jobs")
|
|
||||||
try:
|
|
||||||
jobs = scrape_jobs(
|
|
||||||
site_name=["indeed"],
|
|
||||||
search_term="software engineer",
|
|
||||||
# New York, NY
|
|
||||||
# Dallas, TX
|
|
||||||
|
|
||||||
# Los Angeles, CA
|
|
||||||
location="Los Angeles, CA",
|
|
||||||
results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
|
|
||||||
country_indeed="USA",
|
|
||||||
offset=offset,
|
|
||||||
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
|
|
||||||
)
|
|
||||||
|
|
||||||
# Add the scraped jobs to the list
|
|
||||||
all_jobs.extend(jobs.to_dict('records'))
|
|
||||||
|
|
||||||
# Increment the offset for the next page of results
|
|
||||||
offset += results_in_each_iteration
|
|
||||||
|
|
||||||
# Add a delay to avoid rate limiting (you can adjust the delay time as needed)
|
|
||||||
print(f"Scraped {len(all_jobs)} jobs")
|
|
||||||
print("Sleeping secs", 100 * (retry_count + 1))
|
|
||||||
time.sleep(100 * (retry_count + 1)) # Sleep for 2 seconds between requests
|
|
||||||
|
|
||||||
break # Break out of the retry loop if successful
|
|
||||||
except Exception as e:
|
|
||||||
print(f"Error: {e}")
|
|
||||||
retry_count += 1
|
|
||||||
print("Sleeping secs before retry", 100 * (retry_count + 1))
|
|
||||||
time.sleep(100 * (retry_count + 1))
|
|
||||||
if retry_count >= max_retries:
|
|
||||||
print("Max retries reached. Exiting.")
|
|
||||||
break
|
|
||||||
|
|
||||||
# DataFrame from the collected job data
|
|
||||||
jobs_df = pd.DataFrame(all_jobs)
|
|
||||||
|
|
||||||
# Formatting
|
|
||||||
pd.set_option("display.max_columns", None)
|
|
||||||
pd.set_option("display.max_rows", None)
|
|
||||||
pd.set_option("display.width", None)
|
|
||||||
pd.set_option("display.max_colwidth", 50)
|
|
||||||
|
|
||||||
print(jobs_df)
|
|
||||||
|
|
||||||
jobs_df.to_csv(csv_filename, index=False)
|
|
||||||
print(f"Outputted to {csv_filename}")
|
|
||||||
2205
poetry.lock
generated
2205
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -1,6 +1,6 @@
|
|||||||
[tool.poetry]
|
[tool.poetry]
|
||||||
name = "python-jobspy"
|
name = "python-jobspy"
|
||||||
version = "1.1.43"
|
version = "1.1.55"
|
||||||
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
|
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
|
||||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
||||||
homepage = "https://github.com/Bunsly/JobSpy"
|
homepage = "https://github.com/Bunsly/JobSpy"
|
||||||
@@ -13,17 +13,24 @@ packages = [
|
|||||||
[tool.poetry.dependencies]
|
[tool.poetry.dependencies]
|
||||||
python = "^3.10"
|
python = "^3.10"
|
||||||
requests = "^2.31.0"
|
requests = "^2.31.0"
|
||||||
tls-client = "*"
|
|
||||||
beautifulsoup4 = "^4.12.2"
|
beautifulsoup4 = "^4.12.2"
|
||||||
pandas = "^2.1.0"
|
pandas = "^2.1.0"
|
||||||
NUMPY = "1.24.2"
|
NUMPY = "1.24.2"
|
||||||
pydantic = "^2.3.0"
|
pydantic = "^2.3.0"
|
||||||
|
tls-client = "^1.0.1"
|
||||||
|
markdownify = "^0.11.6"
|
||||||
|
regex = "^2024.4.28"
|
||||||
|
|
||||||
|
|
||||||
[tool.poetry.group.dev.dependencies]
|
[tool.poetry.group.dev.dependencies]
|
||||||
pytest = "^7.4.1"
|
pytest = "^7.4.1"
|
||||||
jupyter = "^1.0.0"
|
jupyter = "^1.0.0"
|
||||||
|
black = "*"
|
||||||
|
pre-commit = "*"
|
||||||
|
|
||||||
[build-system]
|
[build-system]
|
||||||
requires = ["poetry-core"]
|
requires = ["poetry-core"]
|
||||||
build-backend = "poetry.core.masonry.api"
|
build-backend = "poetry.core.masonry.api"
|
||||||
|
|
||||||
|
[tool.black]
|
||||||
|
line-length = 88
|
||||||
|
|||||||
@@ -1,8 +1,11 @@
|
|||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
import pandas as pd
|
import pandas as pd
|
||||||
from typing import Tuple
|
from typing import Tuple
|
||||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||||
|
|
||||||
from .jobs import JobType, Location
|
from .jobs import JobType, Location
|
||||||
|
from .scrapers.utils import logger, set_logger_level
|
||||||
from .scrapers.indeed import IndeedScraper
|
from .scrapers.indeed import IndeedScraper
|
||||||
from .scrapers.ziprecruiter import ZipRecruiterScraper
|
from .scrapers.ziprecruiter import ZipRecruiterScraper
|
||||||
from .scrapers.glassdoor import GlassdoorScraper
|
from .scrapers.glassdoor import GlassdoorScraper
|
||||||
@@ -15,40 +18,41 @@ from .scrapers.exceptions import (
|
|||||||
GlassdoorException,
|
GlassdoorException,
|
||||||
)
|
)
|
||||||
|
|
||||||
SCRAPER_MAPPING = {
|
|
||||||
Site.LINKEDIN: LinkedInScraper,
|
|
||||||
Site.INDEED: IndeedScraper,
|
|
||||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
|
||||||
Site.GLASSDOOR: GlassdoorScraper,
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
def _map_str_to_site(site_name: str) -> Site:
|
|
||||||
return Site[site_name.upper()]
|
|
||||||
|
|
||||||
|
|
||||||
def scrape_jobs(
|
def scrape_jobs(
|
||||||
site_name: str | list[str] | Site | list[Site] | None = None,
|
site_name: str | list[str] | Site | list[Site] | None = None,
|
||||||
search_term: str | None = None,
|
search_term: str | None = None,
|
||||||
location: str | None = None,
|
location: str | None = None,
|
||||||
distance: int | None = None,
|
distance: int | None = 50,
|
||||||
is_remote: bool = False,
|
is_remote: bool = False,
|
||||||
job_type: str | None = None,
|
job_type: str | None = None,
|
||||||
easy_apply: bool | None = None,
|
easy_apply: bool | None = None,
|
||||||
results_wanted: int = 15,
|
results_wanted: int = 15,
|
||||||
country_indeed: str = "usa",
|
country_indeed: str = "usa",
|
||||||
hyperlinks: bool = False,
|
hyperlinks: bool = False,
|
||||||
proxy: str | None = None,
|
proxies: list[str] | str | None = None,
|
||||||
full_description: bool | None = False,
|
description_format: str = "markdown",
|
||||||
|
linkedin_fetch_description: bool | None = False,
|
||||||
linkedin_company_ids: list[int] | None = None,
|
linkedin_company_ids: list[int] | None = None,
|
||||||
offset: int | None = 0,
|
offset: int | None = 0,
|
||||||
hours_old: int = None,
|
hours_old: int = None,
|
||||||
|
verbose: int = 2,
|
||||||
**kwargs,
|
**kwargs,
|
||||||
) -> pd.DataFrame:
|
) -> pd.DataFrame:
|
||||||
"""
|
"""
|
||||||
Simultaneously scrapes job data from multiple job sites.
|
Simultaneously scrapes job data from multiple job sites.
|
||||||
:return: results_wanted: pandas dataframe containing job data
|
:return: pandas dataframe containing job data
|
||||||
"""
|
"""
|
||||||
|
SCRAPER_MAPPING = {
|
||||||
|
Site.LINKEDIN: LinkedInScraper,
|
||||||
|
Site.INDEED: IndeedScraper,
|
||||||
|
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||||
|
Site.GLASSDOOR: GlassdoorScraper,
|
||||||
|
}
|
||||||
|
set_logger_level(verbose)
|
||||||
|
|
||||||
|
def map_str_to_site(site_name: str) -> Site:
|
||||||
|
return Site[site_name.upper()]
|
||||||
|
|
||||||
def get_enum_from_value(value_str):
|
def get_enum_from_value(value_str):
|
||||||
for job_type in JobType:
|
for job_type in JobType:
|
||||||
@@ -61,12 +65,12 @@ def scrape_jobs(
|
|||||||
def get_site_type():
|
def get_site_type():
|
||||||
site_types = list(Site)
|
site_types = list(Site)
|
||||||
if isinstance(site_name, str):
|
if isinstance(site_name, str):
|
||||||
site_types = [_map_str_to_site(site_name)]
|
site_types = [map_str_to_site(site_name)]
|
||||||
elif isinstance(site_name, Site):
|
elif isinstance(site_name, Site):
|
||||||
site_types = [site_name]
|
site_types = [site_name]
|
||||||
elif isinstance(site_name, list):
|
elif isinstance(site_name, list):
|
||||||
site_types = [
|
site_types = [
|
||||||
_map_str_to_site(site) if isinstance(site, str) else site
|
map_str_to_site(site) if isinstance(site, str) else site
|
||||||
for site in site_name
|
for site in site_name
|
||||||
]
|
]
|
||||||
return site_types
|
return site_types
|
||||||
@@ -82,32 +86,21 @@ def scrape_jobs(
|
|||||||
is_remote=is_remote,
|
is_remote=is_remote,
|
||||||
job_type=job_type,
|
job_type=job_type,
|
||||||
easy_apply=easy_apply,
|
easy_apply=easy_apply,
|
||||||
full_description=full_description,
|
description_format=description_format,
|
||||||
|
linkedin_fetch_description=linkedin_fetch_description,
|
||||||
results_wanted=results_wanted,
|
results_wanted=results_wanted,
|
||||||
linkedin_company_ids=linkedin_company_ids,
|
linkedin_company_ids=linkedin_company_ids,
|
||||||
offset=offset,
|
offset=offset,
|
||||||
hours_old=hours_old
|
hours_old=hours_old,
|
||||||
)
|
)
|
||||||
|
|
||||||
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
|
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
|
||||||
scraper_class = SCRAPER_MAPPING[site]
|
scraper_class = SCRAPER_MAPPING[site]
|
||||||
scraper = scraper_class(proxy=proxy)
|
scraper = scraper_class(proxies=proxies)
|
||||||
|
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
||||||
try:
|
cap_name = site.value.capitalize()
|
||||||
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
|
||||||
except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
|
logger.info(f"{site_name} finished scraping")
|
||||||
raise lie
|
|
||||||
except Exception as e:
|
|
||||||
if site == Site.LINKEDIN:
|
|
||||||
raise LinkedInException(str(e))
|
|
||||||
if site == Site.INDEED:
|
|
||||||
raise IndeedException(str(e))
|
|
||||||
if site == Site.ZIP_RECRUITER:
|
|
||||||
raise ZipRecruiterException(str(e))
|
|
||||||
if site == Site.GLASSDOOR:
|
|
||||||
raise GlassdoorException(str(e))
|
|
||||||
else:
|
|
||||||
raise e
|
|
||||||
return site.value, scraped_data
|
return site.value, scraped_data
|
||||||
|
|
||||||
site_to_jobs_dict = {}
|
site_to_jobs_dict = {}
|
||||||
@@ -130,9 +123,8 @@ def scrape_jobs(
|
|||||||
for site, job_response in site_to_jobs_dict.items():
|
for site, job_response in site_to_jobs_dict.items():
|
||||||
for job in job_response.jobs:
|
for job in job_response.jobs:
|
||||||
job_data = job.dict()
|
job_data = job.dict()
|
||||||
job_data[
|
job_url = job_data["job_url"]
|
||||||
"job_url_hyper"
|
job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
|
||||||
] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
|
|
||||||
job_data["site"] = site
|
job_data["site"] = site
|
||||||
job_data["company"] = job_data["company_name"]
|
job_data["company"] = job_data["company_name"]
|
||||||
job_data["job_type"] = (
|
job_data["job_type"] = (
|
||||||
@@ -168,13 +160,20 @@ def scrape_jobs(
|
|||||||
jobs_dfs.append(job_df)
|
jobs_dfs.append(job_df)
|
||||||
|
|
||||||
if jobs_dfs:
|
if jobs_dfs:
|
||||||
jobs_df = pd.concat(jobs_dfs, ignore_index=True)
|
# Step 1: Filter out all-NA columns from each DataFrame before concatenation
|
||||||
desired_order: list[str] = [
|
filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
|
||||||
"job_url_hyper" if hyperlinks else "job_url",
|
|
||||||
|
# Step 2: Concatenate the filtered DataFrames
|
||||||
|
jobs_df = pd.concat(filtered_dfs, ignore_index=True)
|
||||||
|
|
||||||
|
# Desired column order
|
||||||
|
desired_order = [
|
||||||
|
"id",
|
||||||
"site",
|
"site",
|
||||||
|
"job_url_hyper" if hyperlinks else "job_url",
|
||||||
|
"job_url_direct",
|
||||||
"title",
|
"title",
|
||||||
"company",
|
"company",
|
||||||
"company_url",
|
|
||||||
"location",
|
"location",
|
||||||
"job_type",
|
"job_type",
|
||||||
"date_posted",
|
"date_posted",
|
||||||
@@ -183,13 +182,31 @@ def scrape_jobs(
|
|||||||
"max_amount",
|
"max_amount",
|
||||||
"currency",
|
"currency",
|
||||||
"is_remote",
|
"is_remote",
|
||||||
"num_urgent_words",
|
"job_function",
|
||||||
"benefits",
|
|
||||||
"emails",
|
"emails",
|
||||||
"description",
|
"description",
|
||||||
|
"company_url",
|
||||||
|
"company_url_direct",
|
||||||
|
"company_addresses",
|
||||||
|
"company_industry",
|
||||||
|
"company_num_employees",
|
||||||
|
"company_revenue",
|
||||||
|
"company_description",
|
||||||
|
"logo_photo_url",
|
||||||
|
"banner_photo_url",
|
||||||
|
"ceo_name",
|
||||||
|
"ceo_photo_url",
|
||||||
]
|
]
|
||||||
jobs_formatted_df = jobs_df[desired_order]
|
|
||||||
else:
|
|
||||||
jobs_formatted_df = pd.DataFrame()
|
|
||||||
|
|
||||||
return jobs_formatted_df.sort_values(by='date_posted', ascending=False)
|
# Step 3: Ensure all desired columns are present, adding missing ones as empty
|
||||||
|
for column in desired_order:
|
||||||
|
if column not in jobs_df.columns:
|
||||||
|
jobs_df[column] = None # Add missing columns as empty
|
||||||
|
|
||||||
|
# Reorder the DataFrame according to the desired order
|
||||||
|
jobs_df = jobs_df[desired_order]
|
||||||
|
|
||||||
|
# Step 4: Sort the DataFrame as required
|
||||||
|
return jobs_df.sort_values(by=["site", "date_posted"], ascending=[True, False])
|
||||||
|
else:
|
||||||
|
return pd.DataFrame()
|
||||||
|
|||||||
@@ -1,3 +1,5 @@
|
|||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
from typing import Optional
|
from typing import Optional
|
||||||
from datetime import date
|
from datetime import date
|
||||||
from enum import Enum
|
from enum import Enum
|
||||||
@@ -57,7 +59,7 @@ class JobType(Enum):
|
|||||||
class Country(Enum):
|
class Country(Enum):
|
||||||
"""
|
"""
|
||||||
Gets the subdomain for Indeed and Glassdoor.
|
Gets the subdomain for Indeed and Glassdoor.
|
||||||
The second item in the tuple is the subdomain for Indeed
|
The second item in the tuple is the subdomain (and API country code if there's a ':' separator) for Indeed
|
||||||
The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
|
The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
|
||||||
"""
|
"""
|
||||||
|
|
||||||
@@ -118,11 +120,11 @@ class Country(Enum):
|
|||||||
TURKEY = ("turkey", "tr")
|
TURKEY = ("turkey", "tr")
|
||||||
UKRAINE = ("ukraine", "ua")
|
UKRAINE = ("ukraine", "ua")
|
||||||
UNITEDARABEMIRATES = ("united arab emirates", "ae")
|
UNITEDARABEMIRATES = ("united arab emirates", "ae")
|
||||||
UK = ("uk,united kingdom", "uk", "co.uk")
|
UK = ("uk,united kingdom", "uk:gb", "co.uk")
|
||||||
USA = ("usa,us,united states", "www", "com")
|
USA = ("usa,us,united states", "www:us", "com")
|
||||||
URUGUAY = ("uruguay", "uy")
|
URUGUAY = ("uruguay", "uy")
|
||||||
VENEZUELA = ("venezuela", "ve")
|
VENEZUELA = ("venezuela", "ve")
|
||||||
VIETNAM = ("vietnam", "vn")
|
VIETNAM = ("vietnam", "vn", "com")
|
||||||
|
|
||||||
# internal for ziprecruiter
|
# internal for ziprecruiter
|
||||||
US_CANADA = ("usa/ca", "www")
|
US_CANADA = ("usa/ca", "www")
|
||||||
@@ -132,7 +134,10 @@ class Country(Enum):
|
|||||||
|
|
||||||
@property
|
@property
|
||||||
def indeed_domain_value(self):
|
def indeed_domain_value(self):
|
||||||
return self.value[1]
|
subdomain, _, api_country_code = self.value[1].partition(":")
|
||||||
|
if subdomain and api_country_code:
|
||||||
|
return subdomain, api_country_code.upper()
|
||||||
|
return self.value[1], self.value[1].upper()
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def glassdoor_domain_value(self):
|
def glassdoor_domain_value(self):
|
||||||
@@ -145,7 +150,7 @@ class Country(Enum):
|
|||||||
else:
|
else:
|
||||||
raise Exception(f"Glassdoor is not available for {self.name}")
|
raise Exception(f"Glassdoor is not available for {self.name}")
|
||||||
|
|
||||||
def get_url(self):
|
def get_glassdoor_url(self):
|
||||||
return f"https://{self.glassdoor_domain_value}/"
|
return f"https://{self.glassdoor_domain_value}/"
|
||||||
|
|
||||||
@classmethod
|
@classmethod
|
||||||
@@ -153,7 +158,7 @@ class Country(Enum):
|
|||||||
"""Convert a string to the corresponding Country enum."""
|
"""Convert a string to the corresponding Country enum."""
|
||||||
country_str = country_str.strip().lower()
|
country_str = country_str.strip().lower()
|
||||||
for country in cls:
|
for country in cls:
|
||||||
country_names = country.value[0].split(',')
|
country_names = country.value[0].split(",")
|
||||||
if country_str in country_names:
|
if country_str in country_names:
|
||||||
return country
|
return country
|
||||||
valid_countries = [country.value for country in cls]
|
valid_countries = [country.value for country in cls]
|
||||||
@@ -163,7 +168,7 @@ class Country(Enum):
|
|||||||
|
|
||||||
|
|
||||||
class Location(BaseModel):
|
class Location(BaseModel):
|
||||||
country: Country | None = None
|
country: Country | str | None = None
|
||||||
city: Optional[str] = None
|
city: Optional[str] = None
|
||||||
state: Optional[str] = None
|
state: Optional[str] = None
|
||||||
|
|
||||||
@@ -173,7 +178,12 @@ class Location(BaseModel):
|
|||||||
location_parts.append(self.city)
|
location_parts.append(self.city)
|
||||||
if self.state:
|
if self.state:
|
||||||
location_parts.append(self.state)
|
location_parts.append(self.state)
|
||||||
if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
|
if isinstance(self.country, str):
|
||||||
|
location_parts.append(self.country)
|
||||||
|
elif self.country and self.country not in (
|
||||||
|
Country.US_CANADA,
|
||||||
|
Country.WORLDWIDE,
|
||||||
|
):
|
||||||
country_name = self.country.value[0]
|
country_name = self.country.value[0]
|
||||||
if "," in country_name:
|
if "," in country_name:
|
||||||
country_name = country_name.split(",")[0]
|
country_name = country_name.split(",")[0]
|
||||||
@@ -210,23 +220,42 @@ class Compensation(BaseModel):
|
|||||||
currency: Optional[str] = "USD"
|
currency: Optional[str] = "USD"
|
||||||
|
|
||||||
|
|
||||||
|
class DescriptionFormat(Enum):
|
||||||
|
MARKDOWN = "markdown"
|
||||||
|
HTML = "html"
|
||||||
|
|
||||||
|
|
||||||
class JobPost(BaseModel):
|
class JobPost(BaseModel):
|
||||||
|
id: str | None = None
|
||||||
title: str
|
title: str
|
||||||
company_name: str
|
company_name: str | None
|
||||||
job_url: str
|
job_url: str
|
||||||
|
job_url_direct: str | None = None
|
||||||
location: Optional[Location]
|
location: Optional[Location]
|
||||||
|
|
||||||
description: str | None = None
|
description: str | None = None
|
||||||
company_url: str | None = None
|
company_url: str | None = None
|
||||||
|
company_url_direct: str | None = None
|
||||||
|
|
||||||
job_type: list[JobType] | None = None
|
job_type: list[JobType] | None = None
|
||||||
compensation: Compensation | None = None
|
compensation: Compensation | None = None
|
||||||
date_posted: date | None = None
|
date_posted: date | None = None
|
||||||
benefits: str | None = None
|
|
||||||
emails: list[str] | None = None
|
emails: list[str] | None = None
|
||||||
num_urgent_words: int | None = None
|
|
||||||
is_remote: bool | None = None
|
is_remote: bool | None = None
|
||||||
# company_industry: str | None = None
|
|
||||||
|
# indeed specific
|
||||||
|
company_addresses: str | None = None
|
||||||
|
company_industry: str | None = None
|
||||||
|
company_num_employees: str | None = None
|
||||||
|
company_revenue: str | None = None
|
||||||
|
company_description: str | None = None
|
||||||
|
ceo_name: str | None = None
|
||||||
|
ceo_photo_url: str | None = None
|
||||||
|
logo_photo_url: str | None = None
|
||||||
|
banner_photo_url: str | None = None
|
||||||
|
|
||||||
|
# linkedin only atm
|
||||||
|
job_function: str | None = None
|
||||||
|
|
||||||
|
|
||||||
class JobResponse(BaseModel):
|
class JobResponse(BaseModel):
|
||||||
|
|||||||
@@ -1,4 +1,15 @@
|
|||||||
from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
|
from __future__ import annotations
|
||||||
|
|
||||||
|
from abc import ABC, abstractmethod
|
||||||
|
|
||||||
|
from ..jobs import (
|
||||||
|
Enum,
|
||||||
|
BaseModel,
|
||||||
|
JobType,
|
||||||
|
JobResponse,
|
||||||
|
Country,
|
||||||
|
DescriptionFormat,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
class Site(Enum):
|
class Site(Enum):
|
||||||
@@ -18,17 +29,19 @@ class ScraperInput(BaseModel):
|
|||||||
is_remote: bool = False
|
is_remote: bool = False
|
||||||
job_type: JobType | None = None
|
job_type: JobType | None = None
|
||||||
easy_apply: bool | None = None
|
easy_apply: bool | None = None
|
||||||
full_description: bool = False
|
|
||||||
offset: int = 0
|
offset: int = 0
|
||||||
|
linkedin_fetch_description: bool = False
|
||||||
linkedin_company_ids: list[int] | None = None
|
linkedin_company_ids: list[int] | None = None
|
||||||
|
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
|
||||||
|
|
||||||
results_wanted: int = 15
|
results_wanted: int = 15
|
||||||
hours_old: int | None = None
|
hours_old: int | None = None
|
||||||
|
|
||||||
|
|
||||||
class Scraper:
|
class Scraper(ABC):
|
||||||
def __init__(self, site: Site, proxy: list[str] | None = None):
|
def __init__(self, site: Site, proxies: list[str] | None = None):
|
||||||
|
self.proxies = proxies
|
||||||
self.site = site
|
self.site = site
|
||||||
self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
|
|
||||||
|
|
||||||
|
@abstractmethod
|
||||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
|
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
|
||||||
|
|||||||
@@ -4,17 +4,24 @@ jobspy.scrapers.glassdoor
|
|||||||
|
|
||||||
This module contains routines to scrape Glassdoor.
|
This module contains routines to scrape Glassdoor.
|
||||||
"""
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import re
|
||||||
import json
|
import json
|
||||||
import requests
|
import requests
|
||||||
from bs4 import BeautifulSoup
|
from typing import Optional, Tuple
|
||||||
from typing import Optional
|
|
||||||
from datetime import datetime, timedelta
|
from datetime import datetime, timedelta
|
||||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||||
from ..utils import count_urgent_words, extract_emails_from_text
|
|
||||||
|
|
||||||
from .. import Scraper, ScraperInput, Site
|
from .. import Scraper, ScraperInput, Site
|
||||||
|
from ..utils import extract_emails_from_text
|
||||||
from ..exceptions import GlassdoorException
|
from ..exceptions import GlassdoorException
|
||||||
from ..utils import create_session, modify_and_get_description
|
from ..utils import (
|
||||||
|
create_session,
|
||||||
|
markdown_converter,
|
||||||
|
logger,
|
||||||
|
)
|
||||||
from ...jobs import (
|
from ...jobs import (
|
||||||
JobPost,
|
JobPost,
|
||||||
Compensation,
|
Compensation,
|
||||||
@@ -22,85 +29,154 @@ from ...jobs import (
|
|||||||
Location,
|
Location,
|
||||||
JobResponse,
|
JobResponse,
|
||||||
JobType,
|
JobType,
|
||||||
|
DescriptionFormat,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
class GlassdoorScraper(Scraper):
|
class GlassdoorScraper(Scraper):
|
||||||
def __init__(self, proxy: Optional[str] = None):
|
def __init__(self, proxies: list[str] | str | None = None):
|
||||||
"""
|
"""
|
||||||
Initializes GlassdoorScraper with the Glassdoor job search url
|
Initializes GlassdoorScraper with the Glassdoor job search url
|
||||||
"""
|
"""
|
||||||
site = Site(Site.GLASSDOOR)
|
site = Site(Site.GLASSDOOR)
|
||||||
super().__init__(site, proxy=proxy)
|
super().__init__(site, proxies=proxies)
|
||||||
|
|
||||||
self.url = None
|
self.base_url = None
|
||||||
self.country = None
|
self.country = None
|
||||||
|
self.session = None
|
||||||
|
self.scraper_input = None
|
||||||
self.jobs_per_page = 30
|
self.jobs_per_page = 30
|
||||||
|
self.max_pages = 30
|
||||||
self.seen_urls = set()
|
self.seen_urls = set()
|
||||||
|
|
||||||
def fetch_jobs_page(
|
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||||
|
"""
|
||||||
|
Scrapes Glassdoor for jobs with scraper_input criteria.
|
||||||
|
:param scraper_input: Information about job search criteria.
|
||||||
|
:return: JobResponse containing a list of jobs.
|
||||||
|
"""
|
||||||
|
self.scraper_input = scraper_input
|
||||||
|
self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
|
||||||
|
self.base_url = self.scraper_input.country.get_glassdoor_url()
|
||||||
|
|
||||||
|
self.session = create_session(proxies=self.proxies, is_tls=True, has_retry=True)
|
||||||
|
token = self._get_csrf_token()
|
||||||
|
self.headers["gd-csrf-token"] = token if token else self.fallback_token
|
||||||
|
|
||||||
|
location_id, location_type = self._get_location(
|
||||||
|
scraper_input.location, scraper_input.is_remote
|
||||||
|
)
|
||||||
|
if location_type is None:
|
||||||
|
logger.error("Glassdoor: location not parsed")
|
||||||
|
return JobResponse(jobs=[])
|
||||||
|
all_jobs: list[JobPost] = []
|
||||||
|
cursor = None
|
||||||
|
|
||||||
|
range_start = 1 + (scraper_input.offset // self.jobs_per_page)
|
||||||
|
tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
|
||||||
|
range_end = min(tot_pages, self.max_pages + 1)
|
||||||
|
for page in range(range_start, range_end):
|
||||||
|
logger.info(f"Glassdoor search page: {page}")
|
||||||
|
try:
|
||||||
|
jobs, cursor = self._fetch_jobs_page(
|
||||||
|
scraper_input, location_id, location_type, page, cursor
|
||||||
|
)
|
||||||
|
all_jobs.extend(jobs)
|
||||||
|
if not jobs or len(all_jobs) >= scraper_input.results_wanted:
|
||||||
|
all_jobs = all_jobs[: scraper_input.results_wanted]
|
||||||
|
break
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"Glassdoor: {str(e)}")
|
||||||
|
break
|
||||||
|
return JobResponse(jobs=all_jobs)
|
||||||
|
|
||||||
|
def _fetch_jobs_page(
|
||||||
self,
|
self,
|
||||||
scraper_input: ScraperInput,
|
scraper_input: ScraperInput,
|
||||||
location_id: int,
|
location_id: int,
|
||||||
location_type: str,
|
location_type: str,
|
||||||
page_num: int,
|
page_num: int,
|
||||||
cursor: str | None,
|
cursor: str | None,
|
||||||
) -> (list[JobPost], str | None):
|
) -> Tuple[list[JobPost], str | None]:
|
||||||
"""
|
"""
|
||||||
Scrapes a page of Glassdoor for jobs with scraper_input criteria
|
Scrapes a page of Glassdoor for jobs with scraper_input criteria
|
||||||
"""
|
"""
|
||||||
|
jobs = []
|
||||||
|
self.scraper_input = scraper_input
|
||||||
try:
|
try:
|
||||||
payload = self.add_payload(
|
payload = self._add_payload(location_id, location_type, page_num, cursor)
|
||||||
scraper_input, location_id, location_type, page_num, cursor
|
response = self.session.post(
|
||||||
)
|
f"{self.base_url}/graph",
|
||||||
session = create_session(self.proxy, is_tls=False, has_retry=True)
|
headers=self.headers,
|
||||||
response = session.post(
|
timeout_seconds=15,
|
||||||
f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
|
data=payload,
|
||||||
)
|
)
|
||||||
if response.status_code != 200:
|
if response.status_code != 200:
|
||||||
raise GlassdoorException(
|
exc_msg = f"bad response status code: {response.status_code}"
|
||||||
f"bad response status code: {response.status_code}"
|
raise GlassdoorException(exc_msg)
|
||||||
)
|
|
||||||
res_json = response.json()[0]
|
res_json = response.json()[0]
|
||||||
if "errors" in res_json:
|
if "errors" in res_json:
|
||||||
raise ValueError("Error encountered in API response")
|
raise ValueError("Error encountered in API response")
|
||||||
except Exception as e:
|
except (
|
||||||
raise GlassdoorException(str(e))
|
requests.exceptions.ReadTimeout,
|
||||||
|
GlassdoorException,
|
||||||
|
ValueError,
|
||||||
|
Exception,
|
||||||
|
) as e:
|
||||||
|
logger.error(f"Glassdoor: {str(e)}")
|
||||||
|
return jobs, None
|
||||||
|
|
||||||
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
||||||
|
|
||||||
jobs = []
|
|
||||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||||
future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
|
future_to_job_data = {
|
||||||
|
executor.submit(self._process_job, job): job for job in jobs_data
|
||||||
|
}
|
||||||
for future in as_completed(future_to_job_data):
|
for future in as_completed(future_to_job_data):
|
||||||
job_data = future_to_job_data[future]
|
|
||||||
try:
|
try:
|
||||||
job_post = future.result()
|
job_post = future.result()
|
||||||
if job_post:
|
if job_post:
|
||||||
jobs.append(job_post)
|
jobs.append(job_post)
|
||||||
except Exception as exc:
|
except Exception as exc:
|
||||||
raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
|
raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
|
||||||
|
|
||||||
return jobs, self.get_cursor_for_page(
|
return jobs, self.get_cursor_for_page(
|
||||||
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
|
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
|
||||||
)
|
)
|
||||||
|
|
||||||
def process_job(self, job_data):
|
def _get_csrf_token(self):
|
||||||
"""Processes a single job and fetches its description."""
|
"""
|
||||||
|
Fetches csrf token needed for API by visiting a generic page
|
||||||
|
"""
|
||||||
|
res = self.session.get(
|
||||||
|
f"{self.base_url}/Job/computer-science-jobs.htm", headers=self.headers
|
||||||
|
)
|
||||||
|
pattern = r'"token":\s*"([^"]+)"'
|
||||||
|
matches = re.findall(pattern, res.text)
|
||||||
|
token = None
|
||||||
|
if matches:
|
||||||
|
token = matches[0]
|
||||||
|
return token
|
||||||
|
|
||||||
|
def _process_job(self, job_data):
|
||||||
|
"""
|
||||||
|
Processes a single job and fetches its description.
|
||||||
|
"""
|
||||||
job_id = job_data["jobview"]["job"]["listingId"]
|
job_id = job_data["jobview"]["job"]["listingId"]
|
||||||
job_url = f'{self.url}job-listing/j?jl={job_id}'
|
job_url = f"{self.base_url}job-listing/j?jl={job_id}"
|
||||||
if job_url in self.seen_urls:
|
if job_url in self.seen_urls:
|
||||||
return None
|
return None
|
||||||
self.seen_urls.add(job_url)
|
self.seen_urls.add(job_url)
|
||||||
job = job_data["jobview"]
|
job = job_data["jobview"]
|
||||||
title = job["job"]["jobTitleText"]
|
title = job["job"]["jobTitleText"]
|
||||||
company_name = job["header"]["employerNameFromSearch"]
|
company_name = job["header"]["employerNameFromSearch"]
|
||||||
company_id = job_data['jobview']['header']['employer']['id']
|
company_id = job_data["jobview"]["header"]["employer"]["id"]
|
||||||
location_name = job["header"].get("locationName", "")
|
location_name = job["header"].get("locationName", "")
|
||||||
location_type = job["header"].get("locationType", "")
|
location_type = job["header"].get("locationType", "")
|
||||||
age_in_days = job["header"].get("ageInDays")
|
age_in_days = job["header"].get("ageInDays")
|
||||||
is_remote, location = False, None
|
is_remote, location = False, None
|
||||||
date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None
|
date_diff = (datetime.now() - timedelta(days=age_in_days)).date()
|
||||||
|
date_posted = date_diff if age_in_days is not None else None
|
||||||
|
|
||||||
if location_type == "S":
|
if location_type == "S":
|
||||||
is_remote = True
|
is_remote = True
|
||||||
@@ -108,15 +184,15 @@ class GlassdoorScraper(Scraper):
|
|||||||
location = self.parse_location(location_name)
|
location = self.parse_location(location_name)
|
||||||
|
|
||||||
compensation = self.parse_compensation(job["header"])
|
compensation = self.parse_compensation(job["header"])
|
||||||
|
|
||||||
try:
|
try:
|
||||||
description = self.fetch_job_description(job_id)
|
description = self._fetch_job_description(job_id)
|
||||||
except Exception as e :
|
except:
|
||||||
description = None
|
description = None
|
||||||
|
company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
|
||||||
job_post = JobPost(
|
return JobPost(
|
||||||
|
id=str(job_id),
|
||||||
title=title,
|
title=title,
|
||||||
company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
|
company_url=company_url if company_id else None,
|
||||||
company_name=company_name,
|
company_name=company_name,
|
||||||
date_posted=date_posted,
|
date_posted=date_posted,
|
||||||
job_url=job_url,
|
job_url=job_url,
|
||||||
@@ -125,60 +201,20 @@ class GlassdoorScraper(Scraper):
|
|||||||
is_remote=is_remote,
|
is_remote=is_remote,
|
||||||
description=description,
|
description=description,
|
||||||
emails=extract_emails_from_text(description) if description else None,
|
emails=extract_emails_from_text(description) if description else None,
|
||||||
num_urgent_words=count_urgent_words(description) if description else None,
|
|
||||||
)
|
)
|
||||||
return job_post
|
|
||||||
|
|
||||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
def _fetch_job_description(self, job_id):
|
||||||
"""
|
"""
|
||||||
Scrapes Glassdoor for jobs with scraper_input criteria.
|
Fetches the job description for a single job ID.
|
||||||
:param scraper_input: Information about job search criteria.
|
|
||||||
:return: JobResponse containing a list of jobs.
|
|
||||||
"""
|
"""
|
||||||
scraper_input.results_wanted = min(900, scraper_input.results_wanted)
|
url = f"{self.base_url}/graph"
|
||||||
self.country = scraper_input.country
|
|
||||||
self.url = self.country.get_url()
|
|
||||||
|
|
||||||
location_id, location_type = self.get_location(
|
|
||||||
scraper_input.location, scraper_input.is_remote
|
|
||||||
)
|
|
||||||
all_jobs: list[JobPost] = []
|
|
||||||
cursor = None
|
|
||||||
max_pages = 30
|
|
||||||
|
|
||||||
try:
|
|
||||||
for page in range(
|
|
||||||
1 + (scraper_input.offset // self.jobs_per_page),
|
|
||||||
min(
|
|
||||||
(scraper_input.results_wanted // self.jobs_per_page) + 2,
|
|
||||||
max_pages + 1,
|
|
||||||
),
|
|
||||||
):
|
|
||||||
try:
|
|
||||||
jobs, cursor = self.fetch_jobs_page(
|
|
||||||
scraper_input, location_id, location_type, page, cursor
|
|
||||||
)
|
|
||||||
all_jobs.extend(jobs)
|
|
||||||
if len(all_jobs) >= scraper_input.results_wanted:
|
|
||||||
all_jobs = all_jobs[: scraper_input.results_wanted]
|
|
||||||
break
|
|
||||||
except Exception as e:
|
|
||||||
raise GlassdoorException(str(e))
|
|
||||||
except Exception as e:
|
|
||||||
raise GlassdoorException(str(e))
|
|
||||||
|
|
||||||
return JobResponse(jobs=all_jobs)
|
|
||||||
|
|
||||||
def fetch_job_description(self, job_id):
|
|
||||||
"""Fetches the job description for a single job ID."""
|
|
||||||
url = f"{self.url}/graph"
|
|
||||||
body = [
|
body = [
|
||||||
{
|
{
|
||||||
"operationName": "JobDetailQuery",
|
"operationName": "JobDetailQuery",
|
||||||
"variables": {
|
"variables": {
|
||||||
"jl": job_id,
|
"jl": job_id,
|
||||||
"queryString": "q",
|
"queryString": "q",
|
||||||
"pageTypeEnum": "SERP"
|
"pageTypeEnum": "SERP",
|
||||||
},
|
},
|
||||||
"query": """
|
"query": """
|
||||||
query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
|
query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
|
||||||
@@ -193,23 +229,89 @@ class GlassdoorScraper(Scraper):
|
|||||||
__typename
|
__typename
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
"""
|
""",
|
||||||
}
|
}
|
||||||
]
|
]
|
||||||
response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
|
res = requests.post(url, json=body, headers=self.headers)
|
||||||
if response.status_code != 200:
|
if res.status_code != 200:
|
||||||
return None
|
return None
|
||||||
data = response.json()[0]
|
data = res.json()[0]
|
||||||
desc = data['data']['jobview']['job']['description']
|
desc = data["data"]["jobview"]["job"]["description"]
|
||||||
soup = BeautifulSoup(desc, 'html.parser')
|
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||||
return modify_and_get_description(soup)
|
desc = markdown_converter(desc)
|
||||||
|
return desc
|
||||||
|
|
||||||
|
def _get_location(self, location: str, is_remote: bool) -> (int, str):
|
||||||
|
if not location or is_remote:
|
||||||
|
return "11047", "STATE" # remote options
|
||||||
|
url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
|
||||||
|
res = self.session.get(url, headers=self.headers)
|
||||||
|
if res.status_code != 200:
|
||||||
|
if res.status_code == 429:
|
||||||
|
err = f"429 Response - Blocked by Glassdoor for too many requests"
|
||||||
|
logger.error(err)
|
||||||
|
return None, None
|
||||||
|
else:
|
||||||
|
err = f"Glassdoor response status code {res.status_code}"
|
||||||
|
err += f" - {res.text}"
|
||||||
|
logger.error(f"Glassdoor response status code {res.status_code}")
|
||||||
|
return None, None
|
||||||
|
items = res.json()
|
||||||
|
|
||||||
|
if not items:
|
||||||
|
raise ValueError(f"Location '{location}' not found on Glassdoor")
|
||||||
|
location_type = items[0]["locationType"]
|
||||||
|
if location_type == "C":
|
||||||
|
location_type = "CITY"
|
||||||
|
elif location_type == "S":
|
||||||
|
location_type = "STATE"
|
||||||
|
elif location_type == "N":
|
||||||
|
location_type = "COUNTRY"
|
||||||
|
return int(items[0]["locationId"]), location_type
|
||||||
|
|
||||||
|
def _add_payload(
|
||||||
|
self,
|
||||||
|
location_id: int,
|
||||||
|
location_type: str,
|
||||||
|
page_num: int,
|
||||||
|
cursor: str | None = None,
|
||||||
|
) -> str:
|
||||||
|
fromage = None
|
||||||
|
if self.scraper_input.hours_old:
|
||||||
|
fromage = max(self.scraper_input.hours_old // 24, 1)
|
||||||
|
filter_params = []
|
||||||
|
if self.scraper_input.easy_apply:
|
||||||
|
filter_params.append({"filterKey": "applicationType", "values": "1"})
|
||||||
|
if fromage:
|
||||||
|
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
|
||||||
|
payload = {
|
||||||
|
"operationName": "JobSearchResultsQuery",
|
||||||
|
"variables": {
|
||||||
|
"excludeJobListingIds": [],
|
||||||
|
"filterParams": filter_params,
|
||||||
|
"keyword": self.scraper_input.search_term,
|
||||||
|
"numJobsToShow": 30,
|
||||||
|
"locationType": location_type,
|
||||||
|
"locationId": int(location_id),
|
||||||
|
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
|
||||||
|
"pageNumber": page_num,
|
||||||
|
"pageCursor": cursor,
|
||||||
|
"fromage": fromage,
|
||||||
|
"sort": "date",
|
||||||
|
},
|
||||||
|
"query": self.query_template,
|
||||||
|
}
|
||||||
|
if self.scraper_input.job_type:
|
||||||
|
payload["variables"]["filterParams"].append(
|
||||||
|
{"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
|
||||||
|
)
|
||||||
|
return json.dumps([payload])
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def parse_compensation(data: dict) -> Optional[Compensation]:
|
def parse_compensation(data: dict) -> Optional[Compensation]:
|
||||||
pay_period = data.get("payPeriod")
|
pay_period = data.get("payPeriod")
|
||||||
adjusted_pay = data.get("payPeriodAdjustedPay")
|
adjusted_pay = data.get("payPeriodAdjustedPay")
|
||||||
currency = data.get("payCurrency", "USD")
|
currency = data.get("payCurrency", "USD")
|
||||||
|
|
||||||
if not pay_period or not adjusted_pay:
|
if not pay_period or not adjusted_pay:
|
||||||
return None
|
return None
|
||||||
|
|
||||||
@@ -220,7 +322,6 @@ class GlassdoorScraper(Scraper):
|
|||||||
interval = CompensationInterval.get_interval(pay_period)
|
interval = CompensationInterval.get_interval(pay_period)
|
||||||
min_amount = int(adjusted_pay.get("p10") // 1)
|
min_amount = int(adjusted_pay.get("p10") // 1)
|
||||||
max_amount = int(adjusted_pay.get("p90") // 1)
|
max_amount = int(adjusted_pay.get("p90") // 1)
|
||||||
|
|
||||||
return Compensation(
|
return Compensation(
|
||||||
interval=interval,
|
interval=interval,
|
||||||
min_amount=min_amount,
|
min_amount=min_amount,
|
||||||
@@ -228,77 +329,6 @@ class GlassdoorScraper(Scraper):
|
|||||||
currency=currency,
|
currency=currency,
|
||||||
)
|
)
|
||||||
|
|
||||||
def get_location(self, location: str, is_remote: bool) -> (int, str):
|
|
||||||
if not location or is_remote:
|
|
||||||
return "11047", "STATE" # remote options
|
|
||||||
url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
|
|
||||||
session = create_session(self.proxy, has_retry=True)
|
|
||||||
response = session.get(url)
|
|
||||||
if response.status_code != 200:
|
|
||||||
raise GlassdoorException(
|
|
||||||
f"bad response status code: {response.status_code}"
|
|
||||||
)
|
|
||||||
items = response.json()
|
|
||||||
if not items:
|
|
||||||
raise ValueError(f"Location '{location}' not found on Glassdoor")
|
|
||||||
location_type = items[0]["locationType"]
|
|
||||||
if location_type == "C":
|
|
||||||
location_type = "CITY"
|
|
||||||
elif location_type == "S":
|
|
||||||
location_type = "STATE"
|
|
||||||
elif location_type == 'N':
|
|
||||||
location_type = "COUNTRY"
|
|
||||||
return int(items[0]["locationId"]), location_type
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def add_payload(
|
|
||||||
scraper_input,
|
|
||||||
location_id: int,
|
|
||||||
location_type: str,
|
|
||||||
page_num: int,
|
|
||||||
cursor: str | None = None,
|
|
||||||
) -> str:
|
|
||||||
# `fromage` is the posting time filter in days
|
|
||||||
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
|
|
||||||
filter_params = []
|
|
||||||
if scraper_input.easy_apply:
|
|
||||||
filter_params.append({"filterKey": "applicationType", "values": "1"})
|
|
||||||
if fromage:
|
|
||||||
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
|
|
||||||
payload = {
|
|
||||||
"operationName": "JobSearchResultsQuery",
|
|
||||||
|
|
||||||
"variables": {
|
|
||||||
"excludeJobListingIds": [],
|
|
||||||
"filterParams": filter_params,
|
|
||||||
"keyword": scraper_input.search_term,
|
|
||||||
"numJobsToShow": 30,
|
|
||||||
"locationType": location_type,
|
|
||||||
"locationId": int(location_id),
|
|
||||||
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
|
|
||||||
"pageNumber": page_num,
|
|
||||||
"pageCursor": cursor,
|
|
||||||
"fromage": fromage,
|
|
||||||
"sort": "date"
|
|
||||||
},
|
|
||||||
"query": "query JobSearchResultsQuery($excludeJobListingIds: [Long!], $keyword: String, $locationId: Int, $locationType: LocationTypeEnum, $numJobsToShow: Int!, $pageCursor: String, $pageNumber: Int, $filterParams: [FilterParams], $originalPageUrl: String, $seoFriendlyUrlInput: String, $parameterUrlInput: String, $seoUrl: Boolean) {\n jobListings(\n contextHolder: {searchParams: {excludeJobListingIds: $excludeJobListingIds, keyword: $keyword, locationId: $locationId, locationType: $locationType, numPerPage: $numJobsToShow, pageCursor: $pageCursor, pageNumber: $pageNumber, filterParams: $filterParams, originalPageUrl: $originalPageUrl, seoFriendlyUrlInput: $seoFriendlyUrlInput, parameterUrlInput: $parameterUrlInput, seoUrl: $seoUrl, searchType: SR}}\n ) {\n companyFilterOptions {\n id\n shortName\n __typename\n }\n filterOptions\n indeedCtk\n jobListings {\n ...JobView\n __typename\n }\n jobListingSeoLinks {\n linkItems {\n position\n url\n __typename\n }\n __typename\n }\n jobSearchTrackingKey\n jobsPageSeoData {\n pageMetaDescription\n pageTitle\n __typename\n }\n paginationCursors {\n cursor\n pageNumber\n __typename\n }\n indexablePageForSeo\n searchResultsMetadata {\n searchCriteria {\n implicitLocation {\n id\n localizedDisplayName\n type\n __typename\n }\n keyword\n location {\n id\n shortName\n localizedShortName\n localizedDisplayName\n type\n __typename\n }\n __typename\n }\n footerVO {\n countryMenu {\n childNavigationLinks {\n id\n link\n textKey\n __typename\n }\n __typename\n }\n __typename\n }\n helpCenterDomain\n helpCenterLocale\n jobAlert {\n jobAlertExists\n __typename\n }\n jobSerpFaq {\n questions {\n answer\n question\n __typename\n }\n __typename\n }\n jobSerpJobOutlook {\n occupation\n paragraph\n __typename\n }\n showMachineReadableJobs\n __typename\n }\n serpSeoLinksVO {\n relatedJobTitlesResults\n searchedJobTitle\n searchedKeyword\n searchedLocationIdAsString\n searchedLocationSeoName\n searchedLocationType\n topCityIdsToNameResults {\n key\n value\n __typename\n }\n topEmployerIdsToNameResults {\n key\n value\n __typename\n }\n topEmployerNameResults\n topOccupationResults\n __typename\n }\n totalJobsCount\n __typename\n }\n}\n\nfragment JobView on JobListingSearchResult {\n jobview {\n header {\n adOrderId\n advertiserType\n adOrderSponsorshipLevel\n ageInDays\n divisionEmployerName\n easyApply\n employer {\n id\n name\n shortName\n __typename\n }\n employerNameFromSearch\n goc\n gocConfidence\n gocId\n jobCountryId\n jobLink\n jobResultTrackingKey\n jobTitleText\n locationName\n locationType\n locId\n needsCommission\n payCurrency\n payPeriod\n payPeriodAdjustedPay {\n p10\n p50\n p90\n __typename\n }\n rating\n salarySource\n savedJobId\n sponsored\n __typename\n }\n job {\n descriptionFragments\n importConfigId\n jobTitleId\n jobTitleText\n listingId\n __typename\n }\n jobListingAdminDetails {\n cpcVal\n importConfigId\n jobListingId\n jobSourceId\n userEligibleForAdminJobDetails\n __typename\n }\n overview {\n shortName\n squareLogoUrl\n __typename\n }\n __typename\n }\n __typename\n}\n",
|
|
||||||
}
|
|
||||||
|
|
||||||
job_type_filters = {
|
|
||||||
JobType.FULL_TIME: "fulltime",
|
|
||||||
JobType.PART_TIME: "parttime",
|
|
||||||
JobType.CONTRACT: "contract",
|
|
||||||
JobType.INTERNSHIP: "internship",
|
|
||||||
JobType.TEMPORARY: "temporary",
|
|
||||||
}
|
|
||||||
|
|
||||||
if scraper_input.job_type in job_type_filters:
|
|
||||||
filter_value = job_type_filters[scraper_input.job_type]
|
|
||||||
payload["variables"]["filterParams"].append(
|
|
||||||
{"filterKey": "jobType", "values": filter_value}
|
|
||||||
)
|
|
||||||
return json.dumps([payload])
|
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||||
for job_type in JobType:
|
for job_type in JobType:
|
||||||
@@ -318,28 +348,187 @@ class GlassdoorScraper(Scraper):
|
|||||||
if cursor_data["pageNumber"] == page_num:
|
if cursor_data["pageNumber"] == page_num:
|
||||||
return cursor_data["cursor"]
|
return cursor_data["cursor"]
|
||||||
|
|
||||||
@staticmethod
|
fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
|
||||||
def headers() -> dict:
|
headers = {
|
||||||
"""
|
"authority": "www.glassdoor.com",
|
||||||
Returns headers needed for requests
|
"accept": "*/*",
|
||||||
:return: dict - Dictionary containing headers
|
"accept-language": "en-US,en;q=0.9",
|
||||||
"""
|
"apollographql-client-name": "job-search-next",
|
||||||
return {
|
"apollographql-client-version": "4.65.5",
|
||||||
"authority": "www.glassdoor.com",
|
"content-type": "application/json",
|
||||||
"accept": "*/*",
|
"origin": "https://www.glassdoor.com",
|
||||||
"accept-language": "en-US,en;q=0.9",
|
"referer": "https://www.glassdoor.com/",
|
||||||
"apollographql-client-name": "job-search-next",
|
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
|
||||||
"apollographql-client-version": "4.65.5",
|
"sec-ch-ua-mobile": "?0",
|
||||||
"content-type": "application/json",
|
"sec-ch-ua-platform": '"macOS"',
|
||||||
"cookie": 'gdId=91e2dfc4-c8b5-4fa7-83d0-11512b80262c; G_ENABLED_IDPS=google; trs=https%3A%2F%2Fwww.redhat.com%2F:referral:referral:2023-07-05+09%3A50%3A14.862:undefined:undefined; g_state={"i_p":1688587331651,"i_l":1}; _cfuvid=.7llazxhYFZWi6EISSPdVjtqF0NMVwzxr_E.cB1jgLs-1697828392979-0-604800000; GSESSIONID=undefined; JSESSIONID=F03DD1B5EE02DB6D842FE42B142F88F3; cass=1; jobsClicked=true; indeedCtk=1hd77b301k79i801; asst=1697829114.2; G_AUTHUSER_H=0; uc=8013A8318C98C517FE6DD0024636DFDEF978FC33266D93A2FAFEF364EACA608949D8B8FA2DC243D62DE271D733EB189D809ABE5B08D7B1AE865D217BD4EEBB97C282F5DA5FEFE79C937E3F6110B2A3A0ADBBA3B4B6DF5A996FEE00516100A65FCB11DA26817BE8D1C1BF6CFE36B5B68A3FDC2CFEC83AB797F7841FBB157C202332FC7E077B56BD39B167BDF3D9866E3B; AWSALB=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; AWSALBCORS=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; gdsid=1697828393025:1697830776351:668396EDB9E6A832022D34414128093D; at=HkH8Hnqi9uaMC7eu0okqyIwqp07ht9hBvE1_St7E_hRqPvkO9pUeJ1Jcpds4F3g6LL5ADaCNlxrPn0o6DumGMfog8qI1-zxaV_jpiFs3pugntw6WpVyYWdfioIZ1IDKupyteeLQEM1AO4zhGjY_rPZynpsiZBPO_B1au94sKv64rv23yvP56OiWKKfI-8_9hhLACEwWvM-Az7X-4aE2QdFt93VJbXbbGVf07bdDZfimsIkTtgJCLSRhU1V0kEM1Efyu66vo3m77gFFaMW7lxyYnb36I5PdDtEXBm3aL-zR7-qa5ywd94ISEivgqQOA4FPItNhqIlX4XrfD1lxVz6rfPaoTIDi4DI6UMCUjwyPsuv8mn0rYqDfRnmJpZ97fJ5AnhrknAd_6ZWN5v1OrxJczHzcXd8LO820QPoqxzzG13bmSTXLwGSxMUCtSrVsq05hicimQ3jpRt0c1dA4OkTNqF7_770B9JfcHcM8cr8-C4IL56dnOjr9KBGfN1Q2IvZM2cOBRbV7okiNOzKVZ3qJ24AE34WA2F3U6Whiu6H8nIuGG5hSNkVygY6CtglNZfFF9p8pJAZm79PngrrBv-CXFBZmhYLFo46lmFetDkiJ6mirtez4tKpzTIYjIp4_JAkiZFwbLJ2QGH4mK8kyyW0lZiX1DTuQec50N_5wvRo0Gt7nlKxzLsApMnaNhuQeH5ygh_pa381ORo9mQGi0EYF9zk00pa2--z4PtjfQ8KFq36GgpxKy5-o4qgqygZj8F01L8r-FiX2G4C7PREMIpAyHX2A4-_JxA1IS2j12EyqKTLqE9VcP06qm2Z-YuIW3ctmpMxy5G9_KiEiGv17weizhSFnl6SbpAEY-2VSmQ5V6jm3hoMp2jemkuGCRkZeFstLDEPxlzFN7WM; __cf_bm=zGaVjIJw4irf40_7UVw54B6Ohm271RUX4Tc8KVScrbs-1697830777-0-AYv2GnKTnnCU+cY9xHbJunO0DwlLDO6SIBnC/s/qldpKsGK0rRAjD6y8lbyATT/KlS7g29OZaN4fbd0lrJg0KmWbIybZIzfWVLHSYePVuOhu; asst=1697829114.2; at=dFhXf64wsf2TlnWy41xLs7skJkuxgKToEGcjGtDfUvW4oEAJ4tTIR5dKQ8wbwT75aIaGgdCfvcb-da7vwrCGWscCncmfLFQpJ9l-LLwoRfk-pMsxHhd77wvf-W7I0HSm7-Q5lQJqI9WyNGRxOa-RpzBTf4L8_Et4-3FzjPaAoYY5pY1FhuwXbN5asGOAMW-p8cjpbfn3PumlIYuckguWnjrcY2F31YJ_1noeoHM9tCGpymANbqGXRkG6aXY7yCfVXtdgZU1K5SMeaSPZIuF_iLUxjc_corzpNiH6qq7BIAmh-e5Aa-g7cwpZcln1fmwTVw4uTMZf1eLIMTa9WzgqZNkvG-sGaq_XxKA_Wai6xTTkOHfRgm4632Ba2963wdJvkGmUUa3tb_L4_wTgk3eFnHp5JhghLfT2Pe3KidP-yX__vx8JOsqe3fndCkKXgVz7xQKe1Dur-sMNlGwi4LXfguTT2YUI8C5Miq3pj2IHc7dC97eyyAiAM4HvyGWfaXWZcei6oIGrOwMvYgy0AcwFry6SIP2SxLT5TrxinRRuem1r1IcOTJsMJyUPp1QsZ7bOyq9G_0060B4CPyovw5523hEuqLTM-R5e5yavY6C_1DHUyE15C3mrh7kdvmlGZeflnHqkFTEKwwOftm-Mv-CKD5Db9ABFGNxKB2FH7nDH67hfOvm4tGNMzceBPKYJ3wciTt9jK3wy39_7cOYVywfrZ-oLhw_XtsbGSSeGn3HytrfgSADAh2sT0Gg6eCC9Xy1vh-Za337SVLUDXZ73W2xJxxUHBkFzZs8L_Xndo5DsbpWhVs9IYUGyraJdqB3SLgDbAppIBCJl4fx6_DG8-xOQPBvuFMlTROe1JVdHOzXI1GElwFDTuH1pjkg4I2G0NhAbE06Y-1illQE; gdsid=1697828393025:1697831731408:99C30D94108AC3030D61C736DDCDF11C',
|
"sec-fetch-dest": "empty",
|
||||||
"gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
|
"sec-fetch-mode": "cors",
|
||||||
"origin": "https://www.glassdoor.com",
|
"sec-fetch-site": "same-origin",
|
||||||
"referer": "https://www.glassdoor.com/",
|
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
|
||||||
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
|
}
|
||||||
"sec-ch-ua-mobile": "?0",
|
query_template = """
|
||||||
"sec-ch-ua-platform": '"macOS"',
|
query JobSearchResultsQuery(
|
||||||
"sec-fetch-dest": "empty",
|
$excludeJobListingIds: [Long!],
|
||||||
"sec-fetch-mode": "cors",
|
$keyword: String,
|
||||||
"sec-fetch-site": "same-origin",
|
$locationId: Int,
|
||||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
|
$locationType: LocationTypeEnum,
|
||||||
}
|
$numJobsToShow: Int!,
|
||||||
|
$pageCursor: String,
|
||||||
|
$pageNumber: Int,
|
||||||
|
$filterParams: [FilterParams],
|
||||||
|
$originalPageUrl: String,
|
||||||
|
$seoFriendlyUrlInput: String,
|
||||||
|
$parameterUrlInput: String,
|
||||||
|
$seoUrl: Boolean
|
||||||
|
) {
|
||||||
|
jobListings(
|
||||||
|
contextHolder: {
|
||||||
|
searchParams: {
|
||||||
|
excludeJobListingIds: $excludeJobListingIds,
|
||||||
|
keyword: $keyword,
|
||||||
|
locationId: $locationId,
|
||||||
|
locationType: $locationType,
|
||||||
|
numPerPage: $numJobsToShow,
|
||||||
|
pageCursor: $pageCursor,
|
||||||
|
pageNumber: $pageNumber,
|
||||||
|
filterParams: $filterParams,
|
||||||
|
originalPageUrl: $originalPageUrl,
|
||||||
|
seoFriendlyUrlInput: $seoFriendlyUrlInput,
|
||||||
|
parameterUrlInput: $parameterUrlInput,
|
||||||
|
seoUrl: $seoUrl,
|
||||||
|
searchType: SR
|
||||||
|
}
|
||||||
|
}
|
||||||
|
) {
|
||||||
|
companyFilterOptions {
|
||||||
|
id
|
||||||
|
shortName
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
filterOptions
|
||||||
|
indeedCtk
|
||||||
|
jobListings {
|
||||||
|
...JobView
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
jobListingSeoLinks {
|
||||||
|
linkItems {
|
||||||
|
position
|
||||||
|
url
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
jobSearchTrackingKey
|
||||||
|
jobsPageSeoData {
|
||||||
|
pageMetaDescription
|
||||||
|
pageTitle
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
paginationCursors {
|
||||||
|
cursor
|
||||||
|
pageNumber
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
indexablePageForSeo
|
||||||
|
searchResultsMetadata {
|
||||||
|
searchCriteria {
|
||||||
|
implicitLocation {
|
||||||
|
id
|
||||||
|
localizedDisplayName
|
||||||
|
type
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
keyword
|
||||||
|
location {
|
||||||
|
id
|
||||||
|
shortName
|
||||||
|
localizedShortName
|
||||||
|
localizedDisplayName
|
||||||
|
type
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
helpCenterDomain
|
||||||
|
helpCenterLocale
|
||||||
|
jobSerpJobOutlook {
|
||||||
|
occupation
|
||||||
|
paragraph
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
showMachineReadableJobs
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
totalJobsCount
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fragment JobView on JobListingSearchResult {
|
||||||
|
jobview {
|
||||||
|
header {
|
||||||
|
adOrderId
|
||||||
|
advertiserType
|
||||||
|
adOrderSponsorshipLevel
|
||||||
|
ageInDays
|
||||||
|
divisionEmployerName
|
||||||
|
easyApply
|
||||||
|
employer {
|
||||||
|
id
|
||||||
|
name
|
||||||
|
shortName
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
employerNameFromSearch
|
||||||
|
goc
|
||||||
|
gocConfidence
|
||||||
|
gocId
|
||||||
|
jobCountryId
|
||||||
|
jobLink
|
||||||
|
jobResultTrackingKey
|
||||||
|
jobTitleText
|
||||||
|
locationName
|
||||||
|
locationType
|
||||||
|
locId
|
||||||
|
needsCommission
|
||||||
|
payCurrency
|
||||||
|
payPeriod
|
||||||
|
payPeriodAdjustedPay {
|
||||||
|
p10
|
||||||
|
p50
|
||||||
|
p90
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
rating
|
||||||
|
salarySource
|
||||||
|
savedJobId
|
||||||
|
sponsored
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
job {
|
||||||
|
description
|
||||||
|
importConfigId
|
||||||
|
jobTitleId
|
||||||
|
jobTitleText
|
||||||
|
listingId
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
jobListingAdminDetails {
|
||||||
|
cpcVal
|
||||||
|
importConfigId
|
||||||
|
jobListingId
|
||||||
|
jobSourceId
|
||||||
|
userEligibleForAdminJobDetails
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
overview {
|
||||||
|
shortName
|
||||||
|
squareLogoUrl
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
__typename
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
|||||||
@@ -4,25 +4,21 @@ jobspy.scrapers.indeed
|
|||||||
|
|
||||||
This module contains routines to scrape Indeed.
|
This module contains routines to scrape Indeed.
|
||||||
"""
|
"""
|
||||||
import re
|
|
||||||
import math
|
|
||||||
import json
|
|
||||||
import requests
|
|
||||||
from typing import Any
|
|
||||||
from datetime import datetime
|
|
||||||
|
|
||||||
import urllib.parse
|
from __future__ import annotations
|
||||||
from bs4 import BeautifulSoup
|
|
||||||
from bs4.element import Tag
|
import math
|
||||||
|
from typing import Tuple
|
||||||
|
from datetime import datetime
|
||||||
from concurrent.futures import ThreadPoolExecutor, Future
|
from concurrent.futures import ThreadPoolExecutor, Future
|
||||||
|
|
||||||
from ..exceptions import IndeedException
|
from .. import Scraper, ScraperInput, Site
|
||||||
from ..utils import (
|
from ..utils import (
|
||||||
count_urgent_words,
|
|
||||||
extract_emails_from_text,
|
extract_emails_from_text,
|
||||||
create_session,
|
|
||||||
get_enum_from_job_type,
|
get_enum_from_job_type,
|
||||||
modify_and_get_description
|
markdown_converter,
|
||||||
|
logger,
|
||||||
|
create_session,
|
||||||
)
|
)
|
||||||
from ...jobs import (
|
from ...jobs import (
|
||||||
JobPost,
|
JobPost,
|
||||||
@@ -31,121 +27,26 @@ from ...jobs import (
|
|||||||
Location,
|
Location,
|
||||||
JobResponse,
|
JobResponse,
|
||||||
JobType,
|
JobType,
|
||||||
|
DescriptionFormat,
|
||||||
)
|
)
|
||||||
from .. import Scraper, ScraperInput, Site
|
|
||||||
|
|
||||||
|
|
||||||
class IndeedScraper(Scraper):
|
class IndeedScraper(Scraper):
|
||||||
def __init__(self, proxy: str | None = None):
|
def __init__(self, proxies: list[str] | str | None = None):
|
||||||
"""
|
"""
|
||||||
Initializes IndeedScraper with the Indeed job search url
|
Initializes IndeedScraper with the Indeed API url
|
||||||
"""
|
"""
|
||||||
self.url = None
|
super().__init__(Site.INDEED, proxies=proxies)
|
||||||
self.country = None
|
|
||||||
site = Site(Site.INDEED)
|
|
||||||
super().__init__(site, proxy=proxy)
|
|
||||||
|
|
||||||
self.jobs_per_page = 25
|
self.session = create_session(proxies=self.proxies, is_tls=False)
|
||||||
|
self.scraper_input = None
|
||||||
|
self.jobs_per_page = 100
|
||||||
|
self.num_workers = 10
|
||||||
self.seen_urls = set()
|
self.seen_urls = set()
|
||||||
|
self.headers = None
|
||||||
def scrape_page(
|
self.api_country_code = None
|
||||||
self, scraper_input: ScraperInput, page: int
|
self.base_url = None
|
||||||
) -> tuple[list[JobPost], int]:
|
self.api_url = "https://apis.indeed.com/graphql"
|
||||||
"""
|
|
||||||
Scrapes a page of Indeed for jobs with scraper_input criteria
|
|
||||||
:param scraper_input:
|
|
||||||
:param page:
|
|
||||||
:return: jobs found on page, total number of jobs found for search
|
|
||||||
"""
|
|
||||||
self.country = scraper_input.country
|
|
||||||
domain = self.country.indeed_domain_value
|
|
||||||
self.url = f"https://{domain}.indeed.com"
|
|
||||||
|
|
||||||
try:
|
|
||||||
session = create_session(self.proxy)
|
|
||||||
response = session.get(
|
|
||||||
f"{self.url}/m/jobs",
|
|
||||||
headers=self.get_headers(),
|
|
||||||
params=self.add_params(scraper_input, page),
|
|
||||||
allow_redirects=True,
|
|
||||||
timeout_seconds=10,
|
|
||||||
)
|
|
||||||
if response.status_code not in range(200, 400):
|
|
||||||
raise IndeedException(
|
|
||||||
f"bad response with status code: {response.status_code}"
|
|
||||||
)
|
|
||||||
except Exception as e:
|
|
||||||
if "Proxy responded with" in str(e):
|
|
||||||
raise IndeedException("bad proxy")
|
|
||||||
raise IndeedException(str(e))
|
|
||||||
|
|
||||||
soup = BeautifulSoup(response.content, "html.parser")
|
|
||||||
job_list = []
|
|
||||||
total_num_jobs = IndeedScraper.total_jobs(soup)
|
|
||||||
if "did not match any jobs" in response.text:
|
|
||||||
return job_list, total_num_jobs
|
|
||||||
|
|
||||||
jobs = IndeedScraper.parse_jobs(
|
|
||||||
soup
|
|
||||||
) #: can raise exception, handled by main scrape function
|
|
||||||
|
|
||||||
if (
|
|
||||||
not jobs.get("metaData", {})
|
|
||||||
.get("mosaicProviderJobCardsModel", {})
|
|
||||||
.get("results")
|
|
||||||
):
|
|
||||||
raise IndeedException("No jobs found.")
|
|
||||||
|
|
||||||
def process_job(job: dict, job_detailed: dict) -> JobPost | None:
|
|
||||||
job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
|
|
||||||
job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
|
|
||||||
if job_url in self.seen_urls:
|
|
||||||
return None
|
|
||||||
self.seen_urls.add(job_url)
|
|
||||||
description = job_detailed['description']['html']
|
|
||||||
|
|
||||||
|
|
||||||
job_type = IndeedScraper.get_job_type(job)
|
|
||||||
timestamp_seconds = job["pubDate"] / 1000
|
|
||||||
date_posted = datetime.fromtimestamp(timestamp_seconds)
|
|
||||||
date_posted = date_posted.strftime("%Y-%m-%d")
|
|
||||||
|
|
||||||
job_post = JobPost(
|
|
||||||
title=job["normTitle"],
|
|
||||||
description=description,
|
|
||||||
company_name=job["company"],
|
|
||||||
company_url=f"{self.url}{job_detailed['employer']['relativeCompanyPageUrl']}" if job_detailed['employer'] else None,
|
|
||||||
location=Location(
|
|
||||||
city=job.get("jobLocationCity"),
|
|
||||||
state=job.get("jobLocationState"),
|
|
||||||
country=self.country,
|
|
||||||
),
|
|
||||||
job_type=job_type,
|
|
||||||
compensation=self.get_compensation(job, job_detailed),
|
|
||||||
date_posted=date_posted,
|
|
||||||
job_url=job_url_client,
|
|
||||||
emails=extract_emails_from_text(description) if description else None,
|
|
||||||
num_urgent_words=count_urgent_words(description)
|
|
||||||
if description
|
|
||||||
else None,
|
|
||||||
is_remote=IndeedScraper.is_job_remote(job, job_detailed, description)
|
|
||||||
|
|
||||||
)
|
|
||||||
return job_post
|
|
||||||
|
|
||||||
workers = 10
|
|
||||||
jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
|
|
||||||
job_keys = [job['jobkey'] for job in jobs]
|
|
||||||
jobs_detailed = self.get_job_details(job_keys)
|
|
||||||
|
|
||||||
with ThreadPoolExecutor(max_workers=workers) as executor:
|
|
||||||
job_results: list[Future] = [
|
|
||||||
executor.submit(process_job, job, job_detailed['job']) for job, job_detailed in zip(jobs, jobs_detailed)
|
|
||||||
]
|
|
||||||
|
|
||||||
job_list = [result.result() for result in job_results if result.result()]
|
|
||||||
|
|
||||||
return job_list, total_num_jobs
|
|
||||||
|
|
||||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||||
"""
|
"""
|
||||||
@@ -153,350 +54,381 @@ class IndeedScraper(Scraper):
|
|||||||
:param scraper_input:
|
:param scraper_input:
|
||||||
:return: job_response
|
:return: job_response
|
||||||
"""
|
"""
|
||||||
job_list, total_results = self.scrape_page(scraper_input, 0)
|
self.scraper_input = scraper_input
|
||||||
pages_processed = 1
|
domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
|
||||||
|
self.base_url = f"https://{domain}.indeed.com"
|
||||||
|
self.headers = self.api_headers.copy()
|
||||||
|
self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
|
||||||
|
job_list = []
|
||||||
|
page = 1
|
||||||
|
|
||||||
while len(self.seen_urls) < scraper_input.results_wanted:
|
cursor = None
|
||||||
pages_to_process = math.ceil((scraper_input.results_wanted - len(self.seen_urls)) / self.jobs_per_page)
|
offset_pages = math.ceil(self.scraper_input.offset / 100)
|
||||||
new_jobs = False
|
for _ in range(offset_pages):
|
||||||
|
logger.info(f"Indeed skipping search page: {page}")
|
||||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
__, cursor = self._scrape_page(cursor)
|
||||||
futures: list[Future] = [
|
if not __:
|
||||||
executor.submit(self.scrape_page, scraper_input, page + pages_processed)
|
logger.info(f"Indeed found no jobs on page: {page}")
|
||||||
for page in range(pages_to_process)
|
|
||||||
]
|
|
||||||
|
|
||||||
for future in futures:
|
|
||||||
jobs, _ = future.result()
|
|
||||||
if jobs:
|
|
||||||
job_list += jobs
|
|
||||||
new_jobs = True
|
|
||||||
if len(self.seen_urls) >= scraper_input.results_wanted:
|
|
||||||
break
|
|
||||||
|
|
||||||
pages_processed += pages_to_process
|
|
||||||
if not new_jobs:
|
|
||||||
break
|
break
|
||||||
|
|
||||||
|
while len(self.seen_urls) < scraper_input.results_wanted:
|
||||||
|
logger.info(f"Indeed search page: {page}")
|
||||||
|
jobs, cursor = self._scrape_page(cursor)
|
||||||
|
if not jobs:
|
||||||
|
logger.info(f"Indeed found no jobs on page: {page}")
|
||||||
|
break
|
||||||
|
job_list += jobs
|
||||||
|
page += 1
|
||||||
|
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||||
|
|
||||||
if len(self.seen_urls) > scraper_input.results_wanted:
|
def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
|
||||||
job_list = job_list[:scraper_input.results_wanted]
|
"""
|
||||||
|
Scrapes a page of Indeed for jobs with scraper_input criteria
|
||||||
job_response = JobResponse(
|
:param cursor:
|
||||||
jobs=job_list,
|
:return: jobs found on page, next page cursor
|
||||||
total_results=total_results,
|
"""
|
||||||
|
jobs = []
|
||||||
|
new_cursor = None
|
||||||
|
filters = self._build_filters()
|
||||||
|
search_term = (
|
||||||
|
self.scraper_input.search_term.replace('"', '\\"')
|
||||||
|
if self.scraper_input.search_term
|
||||||
|
else ""
|
||||||
)
|
)
|
||||||
return job_response
|
query = self.job_search_query.format(
|
||||||
|
what=(f'what: "{search_term}"' if search_term else ""),
|
||||||
def get_description(self, job_page_url: str) -> str | None:
|
location=(
|
||||||
"""
|
f'location: {{where: "{self.scraper_input.location}", radius: {self.scraper_input.distance}, radiusUnit: MILES}}'
|
||||||
Retrieves job description by going to the job page url
|
if self.scraper_input.location
|
||||||
:param job_page_url:
|
else ""
|
||||||
:return: description
|
),
|
||||||
"""
|
dateOnIndeed=self.scraper_input.hours_old,
|
||||||
parsed_url = urllib.parse.urlparse(job_page_url)
|
cursor=f'cursor: "{cursor}"' if cursor else "",
|
||||||
params = urllib.parse.parse_qs(parsed_url.query)
|
filters=filters,
|
||||||
jk_value = params.get("jk", [None])[0]
|
)
|
||||||
formatted_url = f"{self.url}/m/viewjob?jk={jk_value}&spa=1"
|
payload = {
|
||||||
session = create_session(self.proxy)
|
"query": query,
|
||||||
|
}
|
||||||
try:
|
api_headers = self.api_headers.copy()
|
||||||
response = session.get(
|
api_headers["indeed-co"] = self.api_country_code
|
||||||
formatted_url,
|
response = self.session.post(
|
||||||
headers=self.get_headers(),
|
self.api_url,
|
||||||
allow_redirects=True,
|
headers=api_headers,
|
||||||
timeout_seconds=5,
|
json=payload,
|
||||||
|
timeout=10,
|
||||||
|
)
|
||||||
|
if response.status_code != 200:
|
||||||
|
logger.info(
|
||||||
|
f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
|
||||||
)
|
)
|
||||||
except Exception as e:
|
return jobs, new_cursor
|
||||||
return None
|
data = response.json()
|
||||||
|
jobs = data["data"]["jobSearch"]["results"]
|
||||||
|
new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
|
||||||
|
|
||||||
if response.status_code not in range(200, 400):
|
with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
|
||||||
return None
|
job_results: list[Future] = [
|
||||||
|
executor.submit(self._process_job, job["job"]) for job in jobs
|
||||||
|
]
|
||||||
|
job_list = [result.result() for result in job_results if result.result()]
|
||||||
|
return job_list, new_cursor
|
||||||
|
|
||||||
try:
|
def _build_filters(self):
|
||||||
soup = BeautifulSoup(response.text, 'html.parser')
|
"""
|
||||||
script_tags = soup.find_all('script')
|
Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
|
||||||
|
IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
|
||||||
|
"""
|
||||||
|
filters_str = ""
|
||||||
|
if self.scraper_input.hours_old:
|
||||||
|
filters_str = """
|
||||||
|
filters: {{
|
||||||
|
date: {{
|
||||||
|
field: "dateOnIndeed",
|
||||||
|
start: "{start}h"
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
""".format(
|
||||||
|
start=self.scraper_input.hours_old
|
||||||
|
)
|
||||||
|
elif self.scraper_input.easy_apply:
|
||||||
|
filters_str = """
|
||||||
|
filters: {
|
||||||
|
keyword: {
|
||||||
|
field: "indeedApplyScope",
|
||||||
|
keys: ["DESKTOP"]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
elif self.scraper_input.job_type or self.scraper_input.is_remote:
|
||||||
|
job_type_key_mapping = {
|
||||||
|
JobType.FULL_TIME: "CF3CP",
|
||||||
|
JobType.PART_TIME: "75GKK",
|
||||||
|
JobType.CONTRACT: "NJXCK",
|
||||||
|
JobType.INTERNSHIP: "VDTG7",
|
||||||
|
}
|
||||||
|
|
||||||
job_description = ''
|
keys = []
|
||||||
for tag in script_tags:
|
if self.scraper_input.job_type:
|
||||||
if 'window._initialData' in tag.text:
|
key = job_type_key_mapping[self.scraper_input.job_type]
|
||||||
json_str = tag.text
|
keys.append(key)
|
||||||
json_str = json_str.split('window._initialData=')[1]
|
|
||||||
json_str = json_str.rsplit(';', 1)[0]
|
|
||||||
data = json.loads(json_str)
|
|
||||||
job_description = data["jobInfoWrapperModel"]["jobInfoModel"]["sanitizedJobDescription"]
|
|
||||||
break
|
|
||||||
except (KeyError, TypeError, IndexError):
|
|
||||||
return None
|
|
||||||
|
|
||||||
soup = BeautifulSoup(job_description, "html.parser")
|
if self.scraper_input.is_remote:
|
||||||
return modify_and_get_description(soup)
|
keys.append("DSQF7")
|
||||||
|
|
||||||
|
if keys:
|
||||||
|
keys_str = '", "'.join(keys) # Prepare your keys string
|
||||||
|
filters_str = f"""
|
||||||
|
filters: {{
|
||||||
|
composite: {{
|
||||||
|
filters: [{{
|
||||||
|
keyword: {{
|
||||||
|
field: "attributes",
|
||||||
|
keys: ["{keys_str}"]
|
||||||
|
}}
|
||||||
|
}}]
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
"""
|
||||||
|
return filters_str
|
||||||
|
|
||||||
|
def _process_job(self, job: dict) -> JobPost | None:
|
||||||
|
"""
|
||||||
|
Parses the job dict into JobPost model
|
||||||
|
:param job: dict to parse
|
||||||
|
:return: JobPost if it's a new job
|
||||||
|
"""
|
||||||
|
job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
|
||||||
|
if job_url in self.seen_urls:
|
||||||
|
return
|
||||||
|
self.seen_urls.add(job_url)
|
||||||
|
description = job["description"]["html"]
|
||||||
|
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||||
|
description = markdown_converter(description)
|
||||||
|
|
||||||
|
job_type = self._get_job_type(job["attributes"])
|
||||||
|
timestamp_seconds = job["datePublished"] / 1000
|
||||||
|
date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
|
||||||
|
employer = job["employer"].get("dossier") if job["employer"] else None
|
||||||
|
employer_details = employer.get("employerDetails", {}) if employer else {}
|
||||||
|
rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
|
||||||
|
return JobPost(
|
||||||
|
id=str(job["key"]),
|
||||||
|
title=job["title"],
|
||||||
|
description=description,
|
||||||
|
company_name=job["employer"].get("name") if job.get("employer") else None,
|
||||||
|
company_url=(f"{self.base_url}{rel_url}" if job["employer"] else None),
|
||||||
|
company_url_direct=(
|
||||||
|
employer["links"]["corporateWebsite"] if employer else None
|
||||||
|
),
|
||||||
|
location=Location(
|
||||||
|
city=job.get("location", {}).get("city"),
|
||||||
|
state=job.get("location", {}).get("admin1Code"),
|
||||||
|
country=job.get("location", {}).get("countryCode"),
|
||||||
|
),
|
||||||
|
job_type=job_type,
|
||||||
|
compensation=self._get_compensation(job),
|
||||||
|
date_posted=date_posted,
|
||||||
|
job_url=job_url,
|
||||||
|
job_url_direct=(
|
||||||
|
job["recruit"].get("viewJobUrl") if job.get("recruit") else None
|
||||||
|
),
|
||||||
|
emails=extract_emails_from_text(description) if description else None,
|
||||||
|
is_remote=self._is_job_remote(job, description),
|
||||||
|
company_addresses=(
|
||||||
|
employer_details["addresses"][0]
|
||||||
|
if employer_details.get("addresses")
|
||||||
|
else None
|
||||||
|
),
|
||||||
|
company_industry=(
|
||||||
|
employer_details["industry"]
|
||||||
|
.replace("Iv1", "")
|
||||||
|
.replace("_", " ")
|
||||||
|
.title()
|
||||||
|
if employer_details.get("industry")
|
||||||
|
else None
|
||||||
|
),
|
||||||
|
company_num_employees=employer_details.get("employeesLocalizedLabel"),
|
||||||
|
company_revenue=employer_details.get("revenueLocalizedLabel"),
|
||||||
|
company_description=employer_details.get("briefDescription"),
|
||||||
|
ceo_name=employer_details.get("ceoName"),
|
||||||
|
ceo_photo_url=employer_details.get("ceoPhotoUrl"),
|
||||||
|
logo_photo_url=(
|
||||||
|
employer["images"].get("squareLogoUrl")
|
||||||
|
if employer and employer.get("images")
|
||||||
|
else None
|
||||||
|
),
|
||||||
|
banner_photo_url=(
|
||||||
|
employer["images"].get("headerImageUrl")
|
||||||
|
if employer and employer.get("images")
|
||||||
|
else None
|
||||||
|
),
|
||||||
|
)
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def get_job_type(job: dict) -> list[JobType] | None:
|
def _get_job_type(attributes: list) -> list[JobType]:
|
||||||
"""
|
"""
|
||||||
Parses the job to get list of job types
|
Parses the attributes to get list of job types
|
||||||
:param job:
|
:param attributes:
|
||||||
:return:
|
:return: list of JobType
|
||||||
"""
|
"""
|
||||||
job_types: list[JobType] = []
|
job_types: list[JobType] = []
|
||||||
for taxonomy in job["taxonomyAttributes"]:
|
for attribute in attributes:
|
||||||
if taxonomy["label"] == "job-types":
|
job_type_str = attribute["label"].replace("-", "").replace(" ", "").lower()
|
||||||
for i in range(len(taxonomy["attributes"])):
|
job_type = get_enum_from_job_type(job_type_str)
|
||||||
label = taxonomy["attributes"][i].get("label")
|
if job_type:
|
||||||
if label:
|
job_types.append(job_type)
|
||||||
job_type_str = label.replace("-", "").replace(" ", "").lower()
|
|
||||||
job_type = get_enum_from_job_type(job_type_str)
|
|
||||||
if job_type:
|
|
||||||
job_types.append(job_type)
|
|
||||||
return job_types
|
return job_types
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def get_compensation(job: dict, job_detailed: dict) -> Compensation:
|
def _get_compensation(job: dict) -> Compensation | None:
|
||||||
"""
|
"""
|
||||||
Parses the job to get
|
Parses the job to get compensation
|
||||||
|
:param job:
|
||||||
:param job:
|
:param job:
|
||||||
:param job_detailed:
|
|
||||||
:return: compensation object
|
:return: compensation object
|
||||||
"""
|
"""
|
||||||
comp = job_detailed['compensation']['baseSalary']
|
comp = job["compensation"]["baseSalary"]
|
||||||
if comp:
|
if not comp:
|
||||||
interval = IndeedScraper.get_correct_interval(comp['unitOfWork'])
|
|
||||||
if interval:
|
|
||||||
return Compensation(
|
|
||||||
interval=interval,
|
|
||||||
min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None,
|
|
||||||
max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None,
|
|
||||||
currency=job_detailed['compensation']['currencyCode']
|
|
||||||
)
|
|
||||||
|
|
||||||
extracted_salary = job.get("extractedSalary")
|
|
||||||
compensation = None
|
|
||||||
if extracted_salary:
|
|
||||||
salary_snippet = job.get("salarySnippet")
|
|
||||||
currency = salary_snippet.get("currency") if salary_snippet else None
|
|
||||||
interval = (extracted_salary.get("type"),)
|
|
||||||
if isinstance(interval, tuple):
|
|
||||||
interval = interval[0]
|
|
||||||
|
|
||||||
interval = interval.upper()
|
|
||||||
if interval in CompensationInterval.__members__:
|
|
||||||
compensation = Compensation(
|
|
||||||
interval=CompensationInterval[interval],
|
|
||||||
min_amount=int(extracted_salary.get("min")),
|
|
||||||
max_amount=int(extracted_salary.get("max")),
|
|
||||||
currency=currency,
|
|
||||||
)
|
|
||||||
return compensation
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def parse_jobs(soup: BeautifulSoup) -> dict:
|
|
||||||
"""
|
|
||||||
Parses the jobs from the soup object
|
|
||||||
:param soup:
|
|
||||||
:return: jobs
|
|
||||||
"""
|
|
||||||
|
|
||||||
def find_mosaic_script() -> Tag | None:
|
|
||||||
"""
|
|
||||||
Finds jobcards script tag
|
|
||||||
:return: script_tag
|
|
||||||
"""
|
|
||||||
script_tags = soup.find_all("script")
|
|
||||||
|
|
||||||
for tag in script_tags:
|
|
||||||
if (
|
|
||||||
tag.string
|
|
||||||
and "mosaic.providerData" in tag.string
|
|
||||||
and "mosaic-provider-jobcards" in tag.string
|
|
||||||
):
|
|
||||||
return tag
|
|
||||||
return None
|
return None
|
||||||
|
interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
|
||||||
script_tag = find_mosaic_script()
|
if not interval:
|
||||||
|
return None
|
||||||
if script_tag:
|
min_range = comp["range"].get("min")
|
||||||
script_str = script_tag.string
|
max_range = comp["range"].get("max")
|
||||||
pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
|
return Compensation(
|
||||||
p = re.compile(pattern, re.DOTALL)
|
interval=interval,
|
||||||
m = p.search(script_str)
|
min_amount=round(min_range, 2) if min_range is not None else None,
|
||||||
if m:
|
max_amount=round(max_range, 2) if max_range is not None else None,
|
||||||
jobs = json.loads(m.group(1).strip())
|
currency=job["compensation"]["currencyCode"],
|
||||||
return jobs
|
)
|
||||||
else:
|
|
||||||
raise IndeedException("Could not find mosaic provider job cards data")
|
@staticmethod
|
||||||
else:
|
def _is_job_remote(job: dict, description: str) -> bool:
|
||||||
raise IndeedException(
|
"""
|
||||||
"Could not find any results for the search"
|
Searches the description, location, and attributes to check if job is remote
|
||||||
)
|
"""
|
||||||
|
remote_keywords = ["remote", "work from home", "wfh"]
|
||||||
@staticmethod
|
is_remote_in_attributes = any(
|
||||||
def total_jobs(soup: BeautifulSoup) -> int:
|
any(keyword in attr["label"].lower() for keyword in remote_keywords)
|
||||||
"""
|
for attr in job["attributes"]
|
||||||
Parses the total jobs for that search from soup object
|
)
|
||||||
:param soup:
|
is_remote_in_description = any(
|
||||||
:return: total_num_jobs
|
keyword in description.lower() for keyword in remote_keywords
|
||||||
"""
|
|
||||||
script = soup.find("script", string=lambda t: t and "window._initialData" in t)
|
|
||||||
|
|
||||||
pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
|
|
||||||
match = pattern.search(script.string)
|
|
||||||
total_num_jobs = 0
|
|
||||||
if match:
|
|
||||||
json_str = match.group(1)
|
|
||||||
data = json.loads(json_str)
|
|
||||||
total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
|
|
||||||
return total_num_jobs
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def get_headers():
|
|
||||||
return {
|
|
||||||
'Host': 'www.indeed.com',
|
|
||||||
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
|
|
||||||
'sec-fetch-site': 'same-origin',
|
|
||||||
'sec-fetch-dest': 'document',
|
|
||||||
'accept-language': 'en-US,en;q=0.9',
|
|
||||||
'sec-fetch-mode': 'navigate',
|
|
||||||
'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 192.0',
|
|
||||||
'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
|
|
||||||
}
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
|
|
||||||
# `fromage` is the posting time filter in days
|
|
||||||
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
|
|
||||||
params = {
|
|
||||||
"q": scraper_input.search_term,
|
|
||||||
"l": scraper_input.location if scraper_input.location else scraper_input.country.value[0].split(',')[-1],
|
|
||||||
"filter": 0,
|
|
||||||
"start": scraper_input.offset + page * 10,
|
|
||||||
"sort": "date",
|
|
||||||
"fromage": fromage,
|
|
||||||
}
|
|
||||||
if scraper_input.distance:
|
|
||||||
params["radius"] = scraper_input.distance
|
|
||||||
|
|
||||||
sc_values = []
|
|
||||||
if scraper_input.is_remote:
|
|
||||||
sc_values.append("attr(DSQF7)")
|
|
||||||
if scraper_input.job_type:
|
|
||||||
sc_values.append("jt({})".format(scraper_input.job_type.value))
|
|
||||||
|
|
||||||
if sc_values:
|
|
||||||
params["sc"] = "0kf:" + "".join(sc_values) + ";"
|
|
||||||
|
|
||||||
if scraper_input.easy_apply:
|
|
||||||
params['iafilter'] = 1
|
|
||||||
|
|
||||||
return params
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def is_job_remote(job: dict, job_detailed: dict, description: str) -> bool:
|
|
||||||
remote_keywords = ['remote', 'work from home', 'wfh']
|
|
||||||
is_remote_in_attributes = any(
|
|
||||||
any(keyword in attr['label'].lower() for keyword in remote_keywords)
|
|
||||||
for attr in job_detailed['attributes']
|
|
||||||
)
|
)
|
||||||
is_remote_in_description = any(keyword in description.lower() for keyword in remote_keywords)
|
|
||||||
is_remote_in_location = any(
|
is_remote_in_location = any(
|
||||||
keyword in job_detailed['location']['formatted']['long'].lower()
|
keyword in job["location"]["formatted"]["long"].lower()
|
||||||
for keyword in remote_keywords
|
for keyword in remote_keywords
|
||||||
)
|
)
|
||||||
is_remote_in_taxonomy = any(
|
return (
|
||||||
taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0
|
is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
||||||
for taxonomy in job.get("taxonomyAttributes", [])
|
|
||||||
)
|
)
|
||||||
return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
|
||||||
|
|
||||||
def get_job_details(self, job_keys: list[str]) -> dict:
|
|
||||||
"""
|
|
||||||
Queries the GraphQL endpoint for detailed job information for the given job keys.
|
|
||||||
"""
|
|
||||||
url = "https://apis.indeed.com/graphql"
|
|
||||||
headers = {
|
|
||||||
'Host': 'apis.indeed.com',
|
|
||||||
'content-type': 'application/json',
|
|
||||||
'indeed-api-key': '161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8',
|
|
||||||
'accept': 'application/json',
|
|
||||||
'indeed-locale': 'en-US',
|
|
||||||
'accept-language': 'en-US,en;q=0.9',
|
|
||||||
'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1',
|
|
||||||
'indeed-app-info': 'appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone',
|
|
||||||
'indeed-co': 'US',
|
|
||||||
}
|
|
||||||
|
|
||||||
job_keys_gql = '[' + ', '.join(f'"{key}"' for key in job_keys) + ']'
|
|
||||||
|
|
||||||
payload = {
|
|
||||||
"query": f"""
|
|
||||||
query GetJobData {{
|
|
||||||
jobData(input: {{
|
|
||||||
jobKeys: {job_keys_gql}
|
|
||||||
}}) {{
|
|
||||||
results {{
|
|
||||||
job {{
|
|
||||||
key
|
|
||||||
title
|
|
||||||
description {{
|
|
||||||
html
|
|
||||||
}}
|
|
||||||
location {{
|
|
||||||
countryName
|
|
||||||
countryCode
|
|
||||||
city
|
|
||||||
postalCode
|
|
||||||
streetAddress
|
|
||||||
formatted {{
|
|
||||||
short
|
|
||||||
long
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
compensation {{
|
|
||||||
baseSalary {{
|
|
||||||
unitOfWork
|
|
||||||
range {{
|
|
||||||
... on Range {{
|
|
||||||
min
|
|
||||||
max
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
currencyCode
|
|
||||||
}}
|
|
||||||
attributes {{
|
|
||||||
label
|
|
||||||
}}
|
|
||||||
employer {{
|
|
||||||
relativeCompanyPageUrl
|
|
||||||
}}
|
|
||||||
recruit {{
|
|
||||||
viewJobUrl
|
|
||||||
detailedSalary
|
|
||||||
workSchedule
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
}}
|
|
||||||
"""
|
|
||||||
}
|
|
||||||
response = requests.post(url, headers=headers, json=payload, proxies=self.proxy)
|
|
||||||
if response.status_code == 200:
|
|
||||||
return response.json()['data']['jobData']['results']
|
|
||||||
else:
|
|
||||||
return {}
|
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def get_correct_interval(interval: str) -> CompensationInterval:
|
def _get_compensation_interval(interval: str) -> CompensationInterval:
|
||||||
interval_mapping = {
|
interval_mapping = {
|
||||||
"DAY": "DAILY",
|
"DAY": "DAILY",
|
||||||
"YEAR": "YEARLY",
|
"YEAR": "YEARLY",
|
||||||
"HOUR": "HOURLY",
|
"HOUR": "HOURLY",
|
||||||
"WEEK": "WEEKLY",
|
"WEEK": "WEEKLY",
|
||||||
"MONTH": "MONTHLY"
|
"MONTH": "MONTHLY",
|
||||||
}
|
}
|
||||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||||
return CompensationInterval[mapped_interval]
|
return CompensationInterval[mapped_interval]
|
||||||
else:
|
else:
|
||||||
raise ValueError(f"Unsupported interval: {interval}")
|
raise ValueError(f"Unsupported interval: {interval}")
|
||||||
|
|
||||||
|
api_headers = {
|
||||||
|
"Host": "apis.indeed.com",
|
||||||
|
"content-type": "application/json",
|
||||||
|
"indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
|
||||||
|
"accept": "application/json",
|
||||||
|
"indeed-locale": "en-US",
|
||||||
|
"accept-language": "en-US,en;q=0.9",
|
||||||
|
"user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
|
||||||
|
"indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
|
||||||
|
}
|
||||||
|
job_search_query = """
|
||||||
|
query GetJobData {{
|
||||||
|
jobSearch(
|
||||||
|
{what}
|
||||||
|
{location}
|
||||||
|
includeSponsoredResults: NONE
|
||||||
|
limit: 100
|
||||||
|
sort: DATE
|
||||||
|
{cursor}
|
||||||
|
{filters}
|
||||||
|
) {{
|
||||||
|
pageInfo {{
|
||||||
|
nextCursor
|
||||||
|
}}
|
||||||
|
results {{
|
||||||
|
trackingKey
|
||||||
|
job {{
|
||||||
|
key
|
||||||
|
title
|
||||||
|
datePublished
|
||||||
|
dateOnIndeed
|
||||||
|
description {{
|
||||||
|
html
|
||||||
|
}}
|
||||||
|
location {{
|
||||||
|
countryName
|
||||||
|
countryCode
|
||||||
|
admin1Code
|
||||||
|
city
|
||||||
|
postalCode
|
||||||
|
streetAddress
|
||||||
|
formatted {{
|
||||||
|
short
|
||||||
|
long
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
compensation {{
|
||||||
|
baseSalary {{
|
||||||
|
unitOfWork
|
||||||
|
range {{
|
||||||
|
... on Range {{
|
||||||
|
min
|
||||||
|
max
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
currencyCode
|
||||||
|
}}
|
||||||
|
attributes {{
|
||||||
|
key
|
||||||
|
label
|
||||||
|
}}
|
||||||
|
employer {{
|
||||||
|
relativeCompanyPageUrl
|
||||||
|
name
|
||||||
|
dossier {{
|
||||||
|
employerDetails {{
|
||||||
|
addresses
|
||||||
|
industry
|
||||||
|
employeesLocalizedLabel
|
||||||
|
revenueLocalizedLabel
|
||||||
|
briefDescription
|
||||||
|
ceoName
|
||||||
|
ceoPhotoUrl
|
||||||
|
}}
|
||||||
|
images {{
|
||||||
|
headerImageUrl
|
||||||
|
squareLogoUrl
|
||||||
|
}}
|
||||||
|
links {{
|
||||||
|
corporateWebsite
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
recruit {{
|
||||||
|
viewJobUrl
|
||||||
|
detailedSalary
|
||||||
|
workSchedule
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
}}
|
||||||
|
"""
|
||||||
|
|||||||
@@ -4,17 +4,18 @@ jobspy.scrapers.linkedin
|
|||||||
|
|
||||||
This module contains routines to scrape LinkedIn.
|
This module contains routines to scrape LinkedIn.
|
||||||
"""
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
import time
|
import time
|
||||||
import random
|
import random
|
||||||
|
import regex as re
|
||||||
from typing import Optional
|
from typing import Optional
|
||||||
from datetime import datetime
|
from datetime import datetime
|
||||||
|
|
||||||
import requests
|
|
||||||
from requests.exceptions import ProxyError
|
|
||||||
from threading import Lock
|
|
||||||
from bs4.element import Tag
|
from bs4.element import Tag
|
||||||
from bs4 import BeautifulSoup
|
from bs4 import BeautifulSoup
|
||||||
from urllib.parse import urlparse, urlunparse
|
from urllib.parse import urlparse, urlunparse, unquote
|
||||||
|
|
||||||
from .. import Scraper, ScraperInput, Site
|
from .. import Scraper, ScraperInput, Site
|
||||||
from ..exceptions import LinkedInException
|
from ..exceptions import LinkedInException
|
||||||
@@ -25,28 +26,40 @@ from ...jobs import (
|
|||||||
JobResponse,
|
JobResponse,
|
||||||
JobType,
|
JobType,
|
||||||
Country,
|
Country,
|
||||||
Compensation
|
Compensation,
|
||||||
|
DescriptionFormat,
|
||||||
)
|
)
|
||||||
from ..utils import (
|
from ..utils import (
|
||||||
count_urgent_words,
|
logger,
|
||||||
extract_emails_from_text,
|
extract_emails_from_text,
|
||||||
get_enum_from_job_type,
|
get_enum_from_job_type,
|
||||||
currency_parser,
|
currency_parser,
|
||||||
modify_and_get_description
|
markdown_converter,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
class LinkedInScraper(Scraper):
|
class LinkedInScraper(Scraper):
|
||||||
DELAY = 3
|
base_url = "https://www.linkedin.com"
|
||||||
|
delay = 3
|
||||||
|
band_delay = 4
|
||||||
|
jobs_per_page = 25
|
||||||
|
|
||||||
def __init__(self, proxy: Optional[str] = None):
|
def __init__(self, proxies: list[str] | str | None = None):
|
||||||
"""
|
"""
|
||||||
Initializes LinkedInScraper with the LinkedIn job search url
|
Initializes LinkedInScraper with the LinkedIn job search url
|
||||||
"""
|
"""
|
||||||
site = Site(Site.LINKEDIN)
|
super().__init__(Site.LINKEDIN, proxies=proxies)
|
||||||
|
self.session = create_session(
|
||||||
|
proxies=self.proxies,
|
||||||
|
is_tls=False,
|
||||||
|
has_retry=True,
|
||||||
|
delay=5,
|
||||||
|
clear_cookies=True,
|
||||||
|
)
|
||||||
|
self.session.headers.update(self.headers)
|
||||||
|
self.scraper_input = None
|
||||||
self.country = "worldwide"
|
self.country = "worldwide"
|
||||||
self.url = "https://www.linkedin.com"
|
self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
|
||||||
super().__init__(site, proxy=proxy)
|
|
||||||
|
|
||||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||||
"""
|
"""
|
||||||
@@ -54,67 +67,65 @@ class LinkedInScraper(Scraper):
|
|||||||
:param scraper_input:
|
:param scraper_input:
|
||||||
:return: job_response
|
:return: job_response
|
||||||
"""
|
"""
|
||||||
|
self.scraper_input = scraper_input
|
||||||
job_list: list[JobPost] = []
|
job_list: list[JobPost] = []
|
||||||
seen_urls = set()
|
seen_urls = set()
|
||||||
url_lock = Lock()
|
page = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
|
||||||
page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
|
request_count = 0
|
||||||
|
|
||||||
seconds_old = (
|
seconds_old = (
|
||||||
scraper_input.hours_old * 3600
|
scraper_input.hours_old * 3600 if scraper_input.hours_old else None
|
||||||
if scraper_input.hours_old
|
)
|
||||||
else None
|
continue_search = (
|
||||||
|
lambda: len(job_list) < scraper_input.results_wanted and page < 1000
|
||||||
)
|
)
|
||||||
|
|
||||||
def job_type_code(job_type_enum):
|
|
||||||
mapping = {
|
|
||||||
JobType.FULL_TIME: "F",
|
|
||||||
JobType.PART_TIME: "P",
|
|
||||||
JobType.INTERNSHIP: "I",
|
|
||||||
JobType.CONTRACT: "C",
|
|
||||||
JobType.TEMPORARY: "T",
|
|
||||||
}
|
|
||||||
|
|
||||||
return mapping.get(job_type_enum, "")
|
|
||||||
|
|
||||||
continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
|
|
||||||
|
|
||||||
while continue_search():
|
while continue_search():
|
||||||
session = create_session(is_tls=False, has_retry=True, delay=5)
|
request_count += 1
|
||||||
|
logger.info(f"LinkedIn search page: {request_count}")
|
||||||
params = {
|
params = {
|
||||||
"keywords": scraper_input.search_term,
|
"keywords": scraper_input.search_term,
|
||||||
"location": scraper_input.location,
|
"location": scraper_input.location,
|
||||||
"distance": scraper_input.distance,
|
"distance": scraper_input.distance,
|
||||||
"f_WT": 2 if scraper_input.is_remote else None,
|
"f_WT": 2 if scraper_input.is_remote else None,
|
||||||
"f_JT": job_type_code(scraper_input.job_type)
|
"f_JT": (
|
||||||
if scraper_input.job_type
|
self.job_type_code(scraper_input.job_type)
|
||||||
else None,
|
if scraper_input.job_type
|
||||||
|
else None
|
||||||
|
),
|
||||||
"pageNum": 0,
|
"pageNum": 0,
|
||||||
"start": page + scraper_input.offset,
|
"start": page,
|
||||||
"f_AL": "true" if scraper_input.easy_apply else None,
|
"f_AL": "true" if scraper_input.easy_apply else None,
|
||||||
"f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None,
|
"f_C": (
|
||||||
"f_TPR": f"r{seconds_old}",
|
",".join(map(str, scraper_input.linkedin_company_ids))
|
||||||
|
if scraper_input.linkedin_company_ids
|
||||||
|
else None
|
||||||
|
),
|
||||||
}
|
}
|
||||||
|
if seconds_old is not None:
|
||||||
|
params["f_TPR"] = f"r{seconds_old}"
|
||||||
|
|
||||||
params = {k: v for k, v in params.items() if v is not None}
|
params = {k: v for k, v in params.items() if v is not None}
|
||||||
try:
|
try:
|
||||||
response = session.get(
|
response = self.session.get(
|
||||||
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
||||||
params=params,
|
params=params,
|
||||||
allow_redirects=True,
|
|
||||||
proxies=self.proxy,
|
|
||||||
headers=self.headers(),
|
|
||||||
timeout=10,
|
timeout=10,
|
||||||
)
|
)
|
||||||
response.raise_for_status()
|
if response.status_code not in range(200, 400):
|
||||||
|
if response.status_code == 429:
|
||||||
except requests.HTTPError as e:
|
err = (
|
||||||
raise LinkedInException(
|
f"429 Response - Blocked by LinkedIn for too many requests"
|
||||||
f"bad response status code: {e.response.status_code}"
|
)
|
||||||
)
|
else:
|
||||||
except ProxyError as e:
|
err = f"LinkedIn response status code {response.status_code}"
|
||||||
raise LinkedInException("bad proxy")
|
err += f" - {response.text}"
|
||||||
|
logger.error(err)
|
||||||
|
return JobResponse(jobs=job_list)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
raise LinkedInException(str(e))
|
if "Proxy responded with" in str(e):
|
||||||
|
logger.error(f"LinkedIn: Bad proxy")
|
||||||
|
else:
|
||||||
|
logger.error(f"LinkedIn: {str(e)}")
|
||||||
|
return JobResponse(jobs=job_list)
|
||||||
|
|
||||||
soup = BeautifulSoup(response.text, "html.parser")
|
soup = BeautifulSoup(response.text, "html.parser")
|
||||||
job_cards = soup.find_all("div", class_="base-search-card")
|
job_cards = soup.find_all("div", class_="base-search-card")
|
||||||
@@ -127,30 +138,32 @@ class LinkedInScraper(Scraper):
|
|||||||
if href_tag and "href" in href_tag.attrs:
|
if href_tag and "href" in href_tag.attrs:
|
||||||
href = href_tag.attrs["href"].split("?")[0]
|
href = href_tag.attrs["href"].split("?")[0]
|
||||||
job_id = href.split("-")[-1]
|
job_id = href.split("-")[-1]
|
||||||
job_url = f"{self.url}/jobs/view/{job_id}"
|
job_url = f"{self.base_url}/jobs/view/{job_id}"
|
||||||
|
|
||||||
with url_lock:
|
if job_url in seen_urls:
|
||||||
if job_url in seen_urls:
|
continue
|
||||||
continue
|
seen_urls.add(job_url)
|
||||||
seen_urls.add(job_url)
|
|
||||||
|
|
||||||
# Call process_job directly without threading
|
|
||||||
try:
|
try:
|
||||||
job_post = self.process_job(job_card, job_url, scraper_input.full_description)
|
fetch_desc = scraper_input.linkedin_fetch_description
|
||||||
|
job_post = self._process_job(job_card, job_url, fetch_desc)
|
||||||
if job_post:
|
if job_post:
|
||||||
job_list.append(job_post)
|
job_list.append(job_post)
|
||||||
|
if not continue_search():
|
||||||
|
break
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
raise LinkedInException("Exception occurred while processing jobs")
|
raise LinkedInException(str(e))
|
||||||
|
|
||||||
if continue_search():
|
if continue_search():
|
||||||
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
|
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
|
||||||
page += 25
|
page += len(job_list)
|
||||||
|
|
||||||
job_list = job_list[: scraper_input.results_wanted]
|
job_list = job_list[: scraper_input.results_wanted]
|
||||||
return JobResponse(jobs=job_list)
|
return JobResponse(jobs=job_list)
|
||||||
|
|
||||||
def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
|
def _process_job(
|
||||||
salary_tag = job_card.find('span', class_='job-search-card__salary-info')
|
self, job_card: Tag, job_url: str, full_descr: bool
|
||||||
|
) -> Optional[JobPost]:
|
||||||
|
salary_tag = job_card.find("span", class_="job-search-card__salary-info")
|
||||||
|
|
||||||
compensation = None
|
compensation = None
|
||||||
if salary_tag:
|
if salary_tag:
|
||||||
@@ -179,26 +192,26 @@ class LinkedInScraper(Scraper):
|
|||||||
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
|
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
|
||||||
|
|
||||||
metadata_card = job_card.find("div", class_="base-search-card__metadata")
|
metadata_card = job_card.find("div", class_="base-search-card__metadata")
|
||||||
location = self.get_location(metadata_card)
|
location = self._get_location(metadata_card)
|
||||||
|
|
||||||
datetime_tag = (
|
datetime_tag = (
|
||||||
metadata_card.find("time", class_="job-search-card__listdate")
|
metadata_card.find("time", class_="job-search-card__listdate")
|
||||||
if metadata_card
|
if metadata_card
|
||||||
else None
|
else None
|
||||||
)
|
)
|
||||||
date_posted = description = job_type = None
|
date_posted = None
|
||||||
if datetime_tag and "datetime" in datetime_tag.attrs:
|
if datetime_tag and "datetime" in datetime_tag.attrs:
|
||||||
datetime_str = datetime_tag["datetime"]
|
datetime_str = datetime_tag["datetime"]
|
||||||
try:
|
try:
|
||||||
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
|
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
|
||||||
except Exception as e:
|
except:
|
||||||
date_posted = None
|
date_posted = None
|
||||||
benefits_tag = job_card.find("span", class_="result-benefits__text")
|
job_details = {}
|
||||||
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
|
|
||||||
if full_descr:
|
if full_descr:
|
||||||
description, job_type = self.get_job_description(job_url)
|
job_details = self._get_job_details(job_url)
|
||||||
|
|
||||||
return JobPost(
|
return JobPost(
|
||||||
|
id=self._get_id(job_url),
|
||||||
title=title,
|
title=title,
|
||||||
company_name=company,
|
company_name=company,
|
||||||
company_url=company_url,
|
company_url=company_url,
|
||||||
@@ -206,71 +219,77 @@ class LinkedInScraper(Scraper):
|
|||||||
date_posted=date_posted,
|
date_posted=date_posted,
|
||||||
job_url=job_url,
|
job_url=job_url,
|
||||||
compensation=compensation,
|
compensation=compensation,
|
||||||
benefits=benefits,
|
job_type=job_details.get("job_type"),
|
||||||
job_type=job_type,
|
description=job_details.get("description"),
|
||||||
description=description,
|
job_url_direct=job_details.get("job_url_direct"),
|
||||||
emails=extract_emails_from_text(description) if description else None,
|
emails=extract_emails_from_text(job_details.get("description")),
|
||||||
num_urgent_words=count_urgent_words(description) if description else None,
|
logo_photo_url=job_details.get("logo_photo_url"),
|
||||||
|
job_function=job_details.get("job_function"),
|
||||||
)
|
)
|
||||||
|
|
||||||
def get_job_description(
|
def _get_id(self, url: str):
|
||||||
self, job_page_url: str
|
|
||||||
) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
|
|
||||||
"""
|
"""
|
||||||
Retrieves job description by going to the job page url
|
Extracts the job id from the job url
|
||||||
|
:param url:
|
||||||
|
:return: str
|
||||||
|
"""
|
||||||
|
if not url:
|
||||||
|
return None
|
||||||
|
return url.split("/")[-1]
|
||||||
|
|
||||||
|
def _get_job_details(self, job_page_url: str) -> dict:
|
||||||
|
"""
|
||||||
|
Retrieves job description and other job details by going to the job page url
|
||||||
:param job_page_url:
|
:param job_page_url:
|
||||||
:return: description or None
|
:return: dict
|
||||||
"""
|
"""
|
||||||
try:
|
try:
|
||||||
session = create_session(is_tls=False, has_retry=True)
|
response = self.session.get(job_page_url, timeout=5)
|
||||||
response = session.get(job_page_url, timeout=5, proxies=self.proxy)
|
|
||||||
response.raise_for_status()
|
response.raise_for_status()
|
||||||
except requests.HTTPError as e:
|
except:
|
||||||
return None, None
|
return {}
|
||||||
except Exception as e:
|
if "linkedin.com/signup" in response.url:
|
||||||
return None, None
|
return {}
|
||||||
if response.url == "https://www.linkedin.com/signup":
|
|
||||||
return None, None
|
|
||||||
|
|
||||||
soup = BeautifulSoup(response.text, "html.parser")
|
soup = BeautifulSoup(response.text, "html.parser")
|
||||||
div_content = soup.find(
|
div_content = soup.find(
|
||||||
"div", class_=lambda x: x and "show-more-less-html__markup" in x
|
"div", class_=lambda x: x and "show-more-less-html__markup" in x
|
||||||
)
|
)
|
||||||
|
|
||||||
description = None
|
description = None
|
||||||
if div_content:
|
if div_content is not None:
|
||||||
description = modify_and_get_description(div_content)
|
|
||||||
|
|
||||||
def get_job_type(
|
def remove_attributes(tag):
|
||||||
soup_job_type: BeautifulSoup,
|
for attr in list(tag.attrs):
|
||||||
) -> list[JobType] | None:
|
del tag[attr]
|
||||||
"""
|
return tag
|
||||||
Gets the job type from job page
|
|
||||||
:param soup_job_type:
|
div_content = remove_attributes(div_content)
|
||||||
:return: JobType
|
description = div_content.prettify(formatter="html")
|
||||||
"""
|
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||||
h3_tag = soup_job_type.find(
|
description = markdown_converter(description)
|
||||||
"h3",
|
|
||||||
class_="description__job-criteria-subheader",
|
h3_tag = soup.find(
|
||||||
string=lambda text: "Employment type" in text,
|
"h3", text=lambda text: text and "Job function" in text.strip()
|
||||||
|
)
|
||||||
|
|
||||||
|
job_function = None
|
||||||
|
if h3_tag:
|
||||||
|
job_function_span = h3_tag.find_next(
|
||||||
|
"span", class_="description__job-criteria-text"
|
||||||
)
|
)
|
||||||
|
if job_function_span:
|
||||||
|
job_function = job_function_span.text.strip()
|
||||||
|
return {
|
||||||
|
"description": description,
|
||||||
|
"job_type": self._parse_job_type(soup),
|
||||||
|
"job_url_direct": self._parse_job_url_direct(soup),
|
||||||
|
"logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
|
||||||
|
"data-delayed-url"
|
||||||
|
),
|
||||||
|
"job_function": job_function,
|
||||||
|
}
|
||||||
|
|
||||||
employment_type = None
|
def _get_location(self, metadata_card: Optional[Tag]) -> Location:
|
||||||
if h3_tag:
|
|
||||||
employment_type_span = h3_tag.find_next_sibling(
|
|
||||||
"span",
|
|
||||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
|
||||||
)
|
|
||||||
if employment_type_span:
|
|
||||||
employment_type = employment_type_span.get_text(strip=True)
|
|
||||||
employment_type = employment_type.lower()
|
|
||||||
employment_type = employment_type.replace("-", "")
|
|
||||||
|
|
||||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
|
||||||
|
|
||||||
return description, get_job_type(soup)
|
|
||||||
|
|
||||||
def get_location(self, metadata_card: Optional[Tag]) -> Location:
|
|
||||||
"""
|
"""
|
||||||
Extracts the location data from the job metadata card.
|
Extracts the location data from the job metadata card.
|
||||||
:param metadata_card
|
:param metadata_card
|
||||||
@@ -292,28 +311,67 @@ class LinkedInScraper(Scraper):
|
|||||||
)
|
)
|
||||||
elif len(parts) == 3:
|
elif len(parts) == 3:
|
||||||
city, state, country = parts
|
city, state, country = parts
|
||||||
location = Location(
|
country = Country.from_string(country)
|
||||||
city=city,
|
location = Location(city=city, state=state, country=country)
|
||||||
state=state,
|
|
||||||
country=Country.from_string(country),
|
|
||||||
)
|
|
||||||
|
|
||||||
return location
|
return location
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def headers() -> dict:
|
def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
|
||||||
|
"""
|
||||||
|
Gets the job type from job page
|
||||||
|
:param soup_job_type:
|
||||||
|
:return: JobType
|
||||||
|
"""
|
||||||
|
h3_tag = soup_job_type.find(
|
||||||
|
"h3",
|
||||||
|
class_="description__job-criteria-subheader",
|
||||||
|
string=lambda text: "Employment type" in text,
|
||||||
|
)
|
||||||
|
employment_type = None
|
||||||
|
if h3_tag:
|
||||||
|
employment_type_span = h3_tag.find_next_sibling(
|
||||||
|
"span",
|
||||||
|
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||||
|
)
|
||||||
|
if employment_type_span:
|
||||||
|
employment_type = employment_type_span.get_text(strip=True)
|
||||||
|
employment_type = employment_type.lower()
|
||||||
|
employment_type = employment_type.replace("-", "")
|
||||||
|
|
||||||
|
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||||
|
|
||||||
|
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
|
||||||
|
"""
|
||||||
|
Gets the job url direct from job page
|
||||||
|
:param soup:
|
||||||
|
:return: str
|
||||||
|
"""
|
||||||
|
job_url_direct = None
|
||||||
|
job_url_direct_content = soup.find("code", id="applyUrl")
|
||||||
|
if job_url_direct_content:
|
||||||
|
job_url_direct_match = self.job_url_direct_regex.search(
|
||||||
|
job_url_direct_content.decode_contents().strip()
|
||||||
|
)
|
||||||
|
if job_url_direct_match:
|
||||||
|
job_url_direct = unquote(job_url_direct_match.group())
|
||||||
|
|
||||||
|
return job_url_direct
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def job_type_code(job_type_enum: JobType) -> str:
|
||||||
return {
|
return {
|
||||||
"authority": "www.linkedin.com",
|
JobType.FULL_TIME: "F",
|
||||||
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
|
JobType.PART_TIME: "P",
|
||||||
"accept-language": "en-US,en;q=0.9",
|
JobType.INTERNSHIP: "I",
|
||||||
"cache-control": "max-age=0",
|
JobType.CONTRACT: "C",
|
||||||
"sec-ch-ua": '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
|
JobType.TEMPORARY: "T",
|
||||||
# 'sec-ch-ua-mobile': '?0',
|
}.get(job_type_enum, "")
|
||||||
# 'sec-ch-ua-platform': '"macOS"',
|
|
||||||
# 'sec-fetch-dest': 'document',
|
headers = {
|
||||||
# 'sec-fetch-mode': 'navigate',
|
"authority": "www.linkedin.com",
|
||||||
# 'sec-fetch-site': 'none',
|
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
|
||||||
# 'sec-fetch-user': '?1',
|
"accept-language": "en-US,en;q=0.9",
|
||||||
"upgrade-insecure-requests": "1",
|
"cache-control": "max-age=0",
|
||||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
"upgrade-insecure-requests": "1",
|
||||||
}
|
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
||||||
|
}
|
||||||
|
|||||||
@@ -1,34 +1,148 @@
|
|||||||
import re
|
from __future__ import annotations
|
||||||
import numpy as np
|
|
||||||
|
import re
|
||||||
|
import logging
|
||||||
|
from itertools import cycle
|
||||||
|
|
||||||
import tls_client
|
|
||||||
import requests
|
import requests
|
||||||
|
import tls_client
|
||||||
|
import numpy as np
|
||||||
|
from markdownify import markdownify as md
|
||||||
from requests.adapters import HTTPAdapter, Retry
|
from requests.adapters import HTTPAdapter, Retry
|
||||||
|
|
||||||
from ..jobs import JobType
|
from ..jobs import JobType
|
||||||
|
|
||||||
|
logger = logging.getLogger("JobSpy")
|
||||||
def modify_and_get_description(soup):
|
logger.propagate = False
|
||||||
for li in soup.find_all('li'):
|
if not logger.handlers:
|
||||||
li.string = "- " + li.get_text()
|
logger.setLevel(logging.INFO)
|
||||||
|
console_handler = logging.StreamHandler()
|
||||||
description = soup.get_text(separator='\n').strip()
|
format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||||
description = re.sub(r'\n+', '\n', description)
|
formatter = logging.Formatter(format)
|
||||||
return description
|
console_handler.setFormatter(formatter)
|
||||||
|
logger.addHandler(console_handler)
|
||||||
|
|
||||||
|
|
||||||
def count_urgent_words(description: str) -> int:
|
class RotatingProxySession:
|
||||||
|
def __init__(self, proxies=None):
|
||||||
|
if isinstance(proxies, str):
|
||||||
|
self.proxy_cycle = cycle([self.format_proxy(proxies)])
|
||||||
|
elif isinstance(proxies, list):
|
||||||
|
self.proxy_cycle = (
|
||||||
|
cycle([self.format_proxy(proxy) for proxy in proxies])
|
||||||
|
if proxies
|
||||||
|
else None
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
self.proxy_cycle = None
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def format_proxy(proxy):
|
||||||
|
"""Utility method to format a proxy string into a dictionary."""
|
||||||
|
if proxy.startswith("http://") or proxy.startswith("https://"):
|
||||||
|
return {"http": proxy, "https": proxy}
|
||||||
|
return {"http": f"http://{proxy}", "https": f"http://{proxy}"}
|
||||||
|
|
||||||
|
|
||||||
|
class RequestsRotating(RotatingProxySession, requests.Session):
|
||||||
|
|
||||||
|
def __init__(self, proxies=None, has_retry=False, delay=1, clear_cookies=False):
|
||||||
|
RotatingProxySession.__init__(self, proxies=proxies)
|
||||||
|
requests.Session.__init__(self)
|
||||||
|
self.clear_cookies = clear_cookies
|
||||||
|
self.allow_redirects = True
|
||||||
|
self.setup_session(has_retry, delay)
|
||||||
|
|
||||||
|
def setup_session(self, has_retry, delay):
|
||||||
|
if has_retry:
|
||||||
|
retries = Retry(
|
||||||
|
total=3,
|
||||||
|
connect=3,
|
||||||
|
status=3,
|
||||||
|
status_forcelist=[500, 502, 503, 504, 429],
|
||||||
|
backoff_factor=delay,
|
||||||
|
)
|
||||||
|
adapter = HTTPAdapter(max_retries=retries)
|
||||||
|
self.mount("http://", adapter)
|
||||||
|
self.mount("https://", adapter)
|
||||||
|
|
||||||
|
def request(self, method, url, **kwargs):
|
||||||
|
if self.clear_cookies:
|
||||||
|
self.cookies.clear()
|
||||||
|
|
||||||
|
if self.proxy_cycle:
|
||||||
|
next_proxy = next(self.proxy_cycle)
|
||||||
|
if next_proxy["http"] != "http://localhost":
|
||||||
|
self.proxies = next_proxy
|
||||||
|
else:
|
||||||
|
self.proxies = {}
|
||||||
|
return requests.Session.request(self, method, url, **kwargs)
|
||||||
|
|
||||||
|
|
||||||
|
class TLSRotating(RotatingProxySession, tls_client.Session):
|
||||||
|
|
||||||
|
def __init__(self, proxies=None):
|
||||||
|
RotatingProxySession.__init__(self, proxies=proxies)
|
||||||
|
tls_client.Session.__init__(self, random_tls_extension_order=True)
|
||||||
|
|
||||||
|
def execute_request(self, *args, **kwargs):
|
||||||
|
if self.proxy_cycle:
|
||||||
|
next_proxy = next(self.proxy_cycle)
|
||||||
|
if next_proxy["http"] != "http://localhost":
|
||||||
|
self.proxies = next_proxy
|
||||||
|
else:
|
||||||
|
self.proxies = {}
|
||||||
|
response = tls_client.Session.execute_request(self, *args, **kwargs)
|
||||||
|
return response
|
||||||
|
|
||||||
|
|
||||||
|
def create_session(
|
||||||
|
*,
|
||||||
|
proxies: dict | str | None = None,
|
||||||
|
is_tls: bool = True,
|
||||||
|
has_retry: bool = False,
|
||||||
|
delay: int = 1,
|
||||||
|
clear_cookies: bool = False,
|
||||||
|
) -> requests.Session:
|
||||||
"""
|
"""
|
||||||
Count the number of urgent words or phrases in a job description.
|
Creates a requests session with optional tls, proxy, and retry settings.
|
||||||
|
:return: A session object
|
||||||
"""
|
"""
|
||||||
urgent_patterns = re.compile(
|
if is_tls:
|
||||||
r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
|
session = TLSRotating(proxies=proxies)
|
||||||
re.IGNORECASE,
|
else:
|
||||||
)
|
session = RequestsRotating(
|
||||||
matches = re.findall(urgent_patterns, description)
|
proxies=proxies,
|
||||||
count = len(matches)
|
has_retry=has_retry,
|
||||||
|
delay=delay,
|
||||||
|
clear_cookies=clear_cookies,
|
||||||
|
)
|
||||||
|
|
||||||
return count
|
return session
|
||||||
|
|
||||||
|
|
||||||
|
def set_logger_level(verbose: int = 2):
|
||||||
|
"""
|
||||||
|
Adjusts the logger's level. This function allows the logging level to be changed at runtime.
|
||||||
|
|
||||||
|
Parameters:
|
||||||
|
- verbose: int {0, 1, 2} (default=2, all logs)
|
||||||
|
"""
|
||||||
|
if verbose is None:
|
||||||
|
return
|
||||||
|
level_name = {2: "INFO", 1: "WARNING", 0: "ERROR"}.get(verbose, "INFO")
|
||||||
|
level = getattr(logging, level_name.upper(), None)
|
||||||
|
if level is not None:
|
||||||
|
logger.setLevel(level)
|
||||||
|
else:
|
||||||
|
raise ValueError(f"Invalid log level: {level_name}")
|
||||||
|
|
||||||
|
|
||||||
|
def markdown_converter(description_html: str):
|
||||||
|
if description_html is None:
|
||||||
|
return None
|
||||||
|
markdown = md(description_html)
|
||||||
|
return markdown.strip()
|
||||||
|
|
||||||
|
|
||||||
def extract_emails_from_text(text: str) -> list[str] | None:
|
def extract_emails_from_text(text: str) -> list[str] | None:
|
||||||
@@ -38,37 +152,6 @@ def extract_emails_from_text(text: str) -> list[str] | None:
|
|||||||
return email_regex.findall(text)
|
return email_regex.findall(text)
|
||||||
|
|
||||||
|
|
||||||
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
|
|
||||||
"""
|
|
||||||
Creates a requests session with optional tls, proxy, and retry settings.
|
|
||||||
|
|
||||||
:return: A session object
|
|
||||||
"""
|
|
||||||
if is_tls:
|
|
||||||
session = tls_client.Session(
|
|
||||||
client_identifier="chrome112",
|
|
||||||
random_tls_extension_order=True,
|
|
||||||
)
|
|
||||||
session.proxies = proxy
|
|
||||||
else:
|
|
||||||
session = requests.Session()
|
|
||||||
session.allow_redirects = True
|
|
||||||
if proxy:
|
|
||||||
session.proxies.update(proxy)
|
|
||||||
if has_retry:
|
|
||||||
retries = Retry(total=3,
|
|
||||||
connect=3,
|
|
||||||
status=3,
|
|
||||||
status_forcelist=[500, 502, 503, 504, 429],
|
|
||||||
backoff_factor=delay)
|
|
||||||
adapter = HTTPAdapter(max_retries=retries)
|
|
||||||
|
|
||||||
session.mount('http://', adapter)
|
|
||||||
session.mount('https://', adapter)
|
|
||||||
|
|
||||||
return session
|
|
||||||
|
|
||||||
|
|
||||||
def get_enum_from_job_type(job_type_str: str) -> JobType | None:
|
def get_enum_from_job_type(job_type_str: str) -> JobType | None:
|
||||||
"""
|
"""
|
||||||
Given a string, returns the corresponding JobType enum member if a match is found.
|
Given a string, returns the corresponding JobType enum member if a match is found.
|
||||||
@@ -79,17 +162,18 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
|
|||||||
res = job_type
|
res = job_type
|
||||||
return res
|
return res
|
||||||
|
|
||||||
|
|
||||||
def currency_parser(cur_str):
|
def currency_parser(cur_str):
|
||||||
# Remove any non-numerical characters
|
# Remove any non-numerical characters
|
||||||
# except for ',' '.' or '-' (e.g. EUR)
|
# except for ',' '.' or '-' (e.g. EUR)
|
||||||
cur_str = re.sub("[^-0-9.,]", '', cur_str)
|
cur_str = re.sub("[^-0-9.,]", "", cur_str)
|
||||||
# Remove any 000s separators (either , or .)
|
# Remove any 000s separators (either , or .)
|
||||||
cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
|
cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]
|
||||||
|
|
||||||
if '.' in list(cur_str[-3:]):
|
if "." in list(cur_str[-3:]):
|
||||||
num = float(cur_str)
|
num = float(cur_str)
|
||||||
elif ',' in list(cur_str[-3:]):
|
elif "," in list(cur_str[-3:]):
|
||||||
num = float(cur_str.replace(',', '.'))
|
num = float(cur_str.replace(",", "."))
|
||||||
else:
|
else:
|
||||||
num = float(cur_str)
|
num = float(cur_str)
|
||||||
|
|
||||||
|
|||||||
@@ -4,36 +4,81 @@ jobspy.scrapers.ziprecruiter
|
|||||||
|
|
||||||
This module contains routines to scrape ZipRecruiter.
|
This module contains routines to scrape ZipRecruiter.
|
||||||
"""
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
import math
|
import math
|
||||||
import time
|
import time
|
||||||
from datetime import datetime, timezone
|
from datetime import datetime
|
||||||
from typing import Optional, Tuple, Any
|
from typing import Optional, Tuple, Any
|
||||||
|
|
||||||
from bs4 import BeautifulSoup
|
|
||||||
from concurrent.futures import ThreadPoolExecutor
|
from concurrent.futures import ThreadPoolExecutor
|
||||||
|
|
||||||
from .. import Scraper, ScraperInput, Site
|
from .. import Scraper, ScraperInput, Site
|
||||||
from ..exceptions import ZipRecruiterException
|
from ..utils import (
|
||||||
from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
|
logger,
|
||||||
from ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
|
extract_emails_from_text,
|
||||||
|
create_session,
|
||||||
|
markdown_converter,
|
||||||
|
)
|
||||||
|
from ...jobs import (
|
||||||
|
JobPost,
|
||||||
|
Compensation,
|
||||||
|
Location,
|
||||||
|
JobResponse,
|
||||||
|
JobType,
|
||||||
|
Country,
|
||||||
|
DescriptionFormat,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
class ZipRecruiterScraper(Scraper):
|
class ZipRecruiterScraper(Scraper):
|
||||||
def __init__(self, proxy: Optional[str] = None):
|
base_url = "https://www.ziprecruiter.com"
|
||||||
|
api_url = "https://api.ziprecruiter.com"
|
||||||
|
|
||||||
|
def __init__(self, proxies: list[str] | str | None = None):
|
||||||
"""
|
"""
|
||||||
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
|
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
|
||||||
"""
|
"""
|
||||||
site = Site(Site.ZIP_RECRUITER)
|
super().__init__(Site.ZIP_RECRUITER, proxies=proxies)
|
||||||
self.url = "https://www.ziprecruiter.com"
|
|
||||||
self.session = create_session(proxy)
|
|
||||||
self.get_cookies()
|
|
||||||
super().__init__(site, proxy=proxy)
|
|
||||||
|
|
||||||
|
self.scraper_input = None
|
||||||
|
self.session = create_session(proxies=proxies)
|
||||||
|
self._get_cookies()
|
||||||
|
|
||||||
|
self.delay = 5
|
||||||
self.jobs_per_page = 20
|
self.jobs_per_page = 20
|
||||||
self.seen_urls = set()
|
self.seen_urls = set()
|
||||||
self.delay = 5
|
|
||||||
|
|
||||||
def find_jobs_in_page(
|
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||||
|
"""
|
||||||
|
Scrapes ZipRecruiter for jobs with scraper_input criteria.
|
||||||
|
:param scraper_input: Information about job search criteria.
|
||||||
|
:return: JobResponse containing a list of jobs.
|
||||||
|
"""
|
||||||
|
self.scraper_input = scraper_input
|
||||||
|
job_list: list[JobPost] = []
|
||||||
|
continue_token = None
|
||||||
|
|
||||||
|
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||||
|
for page in range(1, max_pages + 1):
|
||||||
|
if len(job_list) >= scraper_input.results_wanted:
|
||||||
|
break
|
||||||
|
if page > 1:
|
||||||
|
time.sleep(self.delay)
|
||||||
|
logger.info(f"ZipRecruiter search page: {page}")
|
||||||
|
jobs_on_page, continue_token = self._find_jobs_in_page(
|
||||||
|
scraper_input, continue_token
|
||||||
|
)
|
||||||
|
if jobs_on_page:
|
||||||
|
job_list.extend(jobs_on_page)
|
||||||
|
else:
|
||||||
|
break
|
||||||
|
if not continue_token:
|
||||||
|
break
|
||||||
|
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||||
|
|
||||||
|
def _find_jobs_in_page(
|
||||||
self, scraper_input: ScraperInput, continue_token: str | None = None
|
self, scraper_input: ScraperInput, continue_token: str | None = None
|
||||||
) -> Tuple[list[JobPost], Optional[str]]:
|
) -> Tuple[list[JobPost], Optional[str]]:
|
||||||
"""
|
"""
|
||||||
@@ -42,75 +87,54 @@ class ZipRecruiterScraper(Scraper):
|
|||||||
:param continue_token:
|
:param continue_token:
|
||||||
:return: jobs found on page
|
:return: jobs found on page
|
||||||
"""
|
"""
|
||||||
params = self.add_params(scraper_input)
|
jobs_list = []
|
||||||
|
params = self._add_params(scraper_input)
|
||||||
if continue_token:
|
if continue_token:
|
||||||
params["continue_from"] = continue_token
|
params["continue_from"] = continue_token
|
||||||
try:
|
try:
|
||||||
response = self.session.get(
|
res = self.session.get(
|
||||||
f"https://api.ziprecruiter.com/jobs-app/jobs",
|
f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
|
||||||
headers=self.headers(),
|
|
||||||
params=params
|
|
||||||
)
|
)
|
||||||
if response.status_code != 200:
|
if res.status_code not in range(200, 400):
|
||||||
raise ZipRecruiterException(
|
if res.status_code == 429:
|
||||||
f"bad response status code: {response.status_code}"
|
err = "429 Response - Blocked by ZipRecruiter for too many requests"
|
||||||
)
|
else:
|
||||||
|
err = f"ZipRecruiter response status code {res.status_code}"
|
||||||
|
err += f" with response: {res.text}" # ZipRecruiter likely not available in EU
|
||||||
|
logger.error(err)
|
||||||
|
return jobs_list, ""
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
if "Proxy responded with non 200 code" in str(e):
|
if "Proxy responded with" in str(e):
|
||||||
raise ZipRecruiterException("bad proxy")
|
logger.error(f"Indeed: Bad proxy")
|
||||||
raise ZipRecruiterException(str(e))
|
else:
|
||||||
|
logger.error(f"Indeed: {str(e)}")
|
||||||
response_data = response.json()
|
return jobs_list, ""
|
||||||
jobs_list = response_data.get("jobs", [])
|
|
||||||
next_continue_token = response_data.get("continue", None)
|
|
||||||
|
|
||||||
|
res_data = res.json()
|
||||||
|
jobs_list = res_data.get("jobs", [])
|
||||||
|
next_continue_token = res_data.get("continue", None)
|
||||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||||
job_results = [executor.submit(self.process_job, job) for job in jobs_list]
|
job_results = [executor.submit(self._process_job, job) for job in jobs_list]
|
||||||
|
|
||||||
job_list = list(filter(None, (result.result() for result in job_results)))
|
job_list = list(filter(None, (result.result() for result in job_results)))
|
||||||
return job_list, next_continue_token
|
return job_list, next_continue_token
|
||||||
|
|
||||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
def _process_job(self, job: dict) -> JobPost | None:
|
||||||
"""
|
"""
|
||||||
Scrapes ZipRecruiter for jobs with scraper_input criteria.
|
Processes an individual job dict from the response
|
||||||
:param scraper_input: Information about job search criteria.
|
|
||||||
:return: JobResponse containing a list of jobs.
|
|
||||||
"""
|
"""
|
||||||
job_list: list[JobPost] = []
|
|
||||||
continue_token = None
|
|
||||||
|
|
||||||
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
|
||||||
|
|
||||||
for page in range(1, max_pages + 1):
|
|
||||||
if len(job_list) >= scraper_input.results_wanted:
|
|
||||||
break
|
|
||||||
|
|
||||||
if page > 1:
|
|
||||||
time.sleep(self.delay)
|
|
||||||
|
|
||||||
jobs_on_page, continue_token = self.find_jobs_in_page(
|
|
||||||
scraper_input, continue_token
|
|
||||||
)
|
|
||||||
if jobs_on_page:
|
|
||||||
job_list.extend(jobs_on_page)
|
|
||||||
|
|
||||||
if not continue_token:
|
|
||||||
break
|
|
||||||
|
|
||||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
|
||||||
|
|
||||||
def process_job(self, job: dict) -> JobPost | None:
|
|
||||||
"""Processes an individual job dict from the response"""
|
|
||||||
title = job.get("name")
|
title = job.get("name")
|
||||||
job_url = f"https://www.ziprecruiter.com/jobs//j?lvk={job['listing_key']}"
|
job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
|
||||||
if job_url in self.seen_urls:
|
if job_url in self.seen_urls:
|
||||||
return
|
return
|
||||||
self.seen_urls.add(job_url)
|
self.seen_urls.add(job_url)
|
||||||
|
|
||||||
job_description_html = job.get("job_description", "").strip()
|
description = job.get("job_description", "").strip()
|
||||||
description_soup = BeautifulSoup(job_description_html, "html.parser")
|
description = (
|
||||||
description = modify_and_get_description(description_soup)
|
markdown_converter(description)
|
||||||
|
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
|
||||||
|
else description
|
||||||
|
)
|
||||||
company = job.get("hiring_company", {}).get("name")
|
company = job.get("hiring_company", {}).get("name")
|
||||||
country_value = "usa" if job.get("job_country") == "US" else "canada"
|
country_value = "usa" if job.get("job_country") == "US" else "canada"
|
||||||
country_enum = Country.from_string(country_value)
|
country_enum = Country.from_string(country_value)
|
||||||
@@ -118,95 +142,72 @@ class ZipRecruiterScraper(Scraper):
|
|||||||
location = Location(
|
location = Location(
|
||||||
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
|
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
|
||||||
)
|
)
|
||||||
job_type = ZipRecruiterScraper.get_job_type_enum(
|
job_type = self._get_job_type_enum(
|
||||||
job.get("employment_type", "").replace("_", "").lower()
|
job.get("employment_type", "").replace("_", "").lower()
|
||||||
)
|
)
|
||||||
date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
|
date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
|
||||||
|
comp_interval = job.get("compensation_interval")
|
||||||
|
comp_interval = "yearly" if comp_interval == "annual" else comp_interval
|
||||||
|
comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
|
||||||
|
comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
|
||||||
|
comp_currency = job.get("compensation_currency")
|
||||||
return JobPost(
|
return JobPost(
|
||||||
|
id=str(job["listing_key"]),
|
||||||
title=title,
|
title=title,
|
||||||
company_name=company,
|
company_name=company,
|
||||||
location=location,
|
location=location,
|
||||||
job_type=job_type,
|
job_type=job_type,
|
||||||
compensation=Compensation(
|
compensation=Compensation(
|
||||||
interval="yearly"
|
interval=comp_interval,
|
||||||
if job.get("compensation_interval") == "annual"
|
min_amount=comp_min,
|
||||||
else job.get("compensation_interval"),
|
max_amount=comp_max,
|
||||||
min_amount=int(job["compensation_min"])
|
currency=comp_currency,
|
||||||
if "compensation_min" in job
|
|
||||||
else None,
|
|
||||||
max_amount=int(job["compensation_max"])
|
|
||||||
if "compensation_max" in job
|
|
||||||
else None,
|
|
||||||
currency=job.get("compensation_currency"),
|
|
||||||
),
|
),
|
||||||
date_posted=date_posted,
|
date_posted=date_posted,
|
||||||
job_url=job_url,
|
job_url=job_url,
|
||||||
description=description,
|
description=description,
|
||||||
emails=extract_emails_from_text(description) if description else None,
|
emails=extract_emails_from_text(description) if description else None,
|
||||||
num_urgent_words=count_urgent_words(description) if description else None,
|
|
||||||
)
|
)
|
||||||
|
|
||||||
def get_cookies(self):
|
def _get_cookies(self):
|
||||||
url="https://api.ziprecruiter.com/jobs-app/event"
|
data = "event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
|
||||||
data="event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
|
url = f"{self.api_url}/jobs-app/event"
|
||||||
self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
|
self.session.post(url, data=data, headers=self.headers)
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||||
for job_type in JobType:
|
for job_type in JobType:
|
||||||
if job_type_str in job_type.value:
|
if job_type_str in job_type.value:
|
||||||
return [job_type]
|
return [job_type]
|
||||||
return None
|
return None
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def add_params(scraper_input) -> dict[str, str | Any]:
|
def _add_params(scraper_input) -> dict[str, str | Any]:
|
||||||
params = {
|
params = {
|
||||||
"search": scraper_input.search_term,
|
"search": scraper_input.search_term,
|
||||||
"location": scraper_input.location,
|
"location": scraper_input.location,
|
||||||
}
|
}
|
||||||
if scraper_input.hours_old:
|
if scraper_input.hours_old:
|
||||||
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
|
params["days"] = max(scraper_input.hours_old // 24, 1)
|
||||||
params['days'] = fromage
|
job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
|
||||||
job_type_value = None
|
|
||||||
if scraper_input.job_type:
|
if scraper_input.job_type:
|
||||||
if scraper_input.job_type.value == "fulltime":
|
job_type = scraper_input.job_type
|
||||||
job_type_value = "full_time"
|
params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
|
||||||
elif scraper_input.job_type.value == "parttime":
|
|
||||||
job_type_value = "part_time"
|
|
||||||
else:
|
|
||||||
job_type_value = scraper_input.job_type.value
|
|
||||||
if scraper_input.easy_apply:
|
if scraper_input.easy_apply:
|
||||||
params['zipapply'] = 1
|
params["zipapply"] = 1
|
||||||
|
|
||||||
if job_type_value:
|
|
||||||
params[
|
|
||||||
"refine_by_employment"
|
|
||||||
] = f"employment_type:employment_type:{job_type_value}"
|
|
||||||
|
|
||||||
if scraper_input.is_remote:
|
if scraper_input.is_remote:
|
||||||
params["refine_by_location_type"] = "only_remote"
|
params["remote"] = 1
|
||||||
|
|
||||||
if scraper_input.distance:
|
if scraper_input.distance:
|
||||||
params["radius"] = scraper_input.distance
|
params["radius"] = scraper_input.distance
|
||||||
|
return {k: v for k, v in params.items() if v is not None}
|
||||||
|
|
||||||
params = {k: v for k, v in params.items() if v is not None}
|
headers = {
|
||||||
|
"Host": "api.ziprecruiter.com",
|
||||||
return params
|
"accept": "*/*",
|
||||||
|
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
|
||||||
@staticmethod
|
"x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
|
||||||
def headers() -> dict:
|
"x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
|
||||||
"""
|
"user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
|
||||||
Returns headers needed for requests
|
"authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
|
||||||
:return: dict - Dictionary containing headers
|
"accept-language": "en-US,en;q=0.9",
|
||||||
"""
|
}
|
||||||
return {
|
|
||||||
"Host": "api.ziprecruiter.com",
|
|
||||||
"accept": "*/*",
|
|
||||||
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
|
|
||||||
"x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
|
|
||||||
"x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
|
|
||||||
"user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
|
|
||||||
"authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
|
|
||||||
"accept-language": "en-US,en;q=0.9",
|
|
||||||
}
|
|
||||||
|
|||||||
Reference in New Issue
Block a user