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7 Commits
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14
README.md
14
README.md
@@ -38,7 +38,8 @@ jobs = scrape_jobs(
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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/Indeed is hour specific, others round up to days old)
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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
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country_indeed='USA', # only needed for indeed / glassdoor
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# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
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)
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)
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print(f"Found {len(jobs)} jobs")
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print(f"Found {len(jobs)} jobs")
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print(jobs.head())
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print(jobs.head())
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@@ -61,22 +62,23 @@ zip_recruiter Software Developer TEKsystems Phoenix
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```plaintext
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```plaintext
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Optional
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Optional
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├── site_type (list): linkedin, zip_recruiter, indeed, glassdoor (default is all 4)
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├── site_name (list|str): linkedin, zip_recruiter, indeed, glassdoor (default is all four)
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├── search_term (str)
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├── search_term (str)
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├── location (str)
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├── location (str)
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├── distance (int): in miles, default 50
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├── distance (int): in miles, default 50
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├── job_type (str): fulltime, parttime, internship, contract
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├── job_type (str): fulltime, parttime, internship, contract
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├── proxy (str): in format 'http://user:pass@host:port'
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├── proxy (str): in format 'http://user:pass@host:port'
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├── is_remote (bool)
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├── is_remote (bool)
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├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
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├── results_wanted (int): number of job results to retrieve for each site specified in 'site_name'
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├── easy_apply (bool): filters for jobs that are hosted on the job board site (LinkedIn & Indeed do not allow pairing this with hours_old)
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├── easy_apply (bool): filters for jobs that are hosted on the job board site (LinkedIn & Indeed do not allow pairing this with hours_old)
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├── linkedin_fetch_description (bool): fetches full description for LinkedIn (slower)
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├── linkedin_fetch_description (bool): fetches full description and direct job url for LinkedIn (slower)
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├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
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├── linkedin_company_ids (list[int]): searches for linkedin jobs with specific company ids
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├── description_format (str): markdown, html (format type of the job descriptions)
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├── description_format (str): markdown, html (Format type of the job descriptions. Default is markdown.)
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├── country_indeed (str): filters the country on Indeed (see below for correct spelling)
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├── country_indeed (str): filters the country on Indeed (see below for correct spelling)
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├── offset (int): starts the search from an offset (e.g. 25 will start the search from the 25th result)
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├── offset (int): starts the search from an offset (e.g. 25 will start the search from the 25th result)
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├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type/is_remote/easy_apply)
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├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type/is_remote/easy_apply)
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├── 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.)
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├── 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.)
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├── hyperlinks (bool): Whether to turn `job_url`s into hyperlinks. Default is false.
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```
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```
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### JobPost Schema
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### JobPost Schema
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@@ -32,17 +32,18 @@ while len(all_jobs) < results_wanted:
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search_term="software engineer",
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search_term="software engineer",
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# New York, NY
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# New York, NY
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# Dallas, TX
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# Dallas, TX
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# Los Angeles, CA
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# Los Angeles, CA
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location="Los Angeles, CA",
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location="Los Angeles, CA",
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results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
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results_wanted=min(
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results_in_each_iteration, results_wanted - len(all_jobs)
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),
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country_indeed="USA",
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country_indeed="USA",
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offset=offset,
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offset=offset,
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# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
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# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
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)
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)
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# Add the scraped jobs to the list
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# Add the scraped jobs to the list
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all_jobs.extend(jobs.to_dict('records'))
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all_jobs.extend(jobs.to_dict("records"))
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# Increment the offset for the next page of results
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# Increment the offset for the next page of results
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offset += results_in_each_iteration
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offset += results_in_each_iteration
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2068
poetry.lock
generated
2068
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -1,6 +1,6 @@
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[tool.poetry]
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[tool.poetry]
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name = "python-jobspy"
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name = "python-jobspy"
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version = "1.1.51"
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version = "1.1.52"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/Bunsly/JobSpy"
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homepage = "https://github.com/Bunsly/JobSpy"
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@@ -19,13 +19,14 @@ NUMPY = "1.24.2"
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pydantic = "^2.3.0"
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pydantic = "^2.3.0"
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tls-client = "^1.0.1"
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tls-client = "^1.0.1"
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markdownify = "^0.11.6"
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markdownify = "^0.11.6"
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regex = "^2024.4.28"
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[tool.poetry.group.dev.dependencies]
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[tool.poetry.group.dev.dependencies]
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pytest = "^7.4.1"
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pytest = "^7.4.1"
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jupyter = "^1.0.0"
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jupyter = "^1.0.0"
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black = "^24.2.0"
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black = "*"
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pre-commit = "^3.6.2"
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pre-commit = "*"
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[build-system]
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[build-system]
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requires = ["poetry-core"]
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requires = ["poetry-core"]
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@@ -1,5 +1,7 @@
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from __future__ import annotations
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from ..jobs import (
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from ..jobs import (
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Enum,
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Enum,
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BaseModel,
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BaseModel,
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@@ -36,9 +38,10 @@ class ScraperInput(BaseModel):
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hours_old: int | None = None
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hours_old: int | None = None
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class Scraper:
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class Scraper(ABC):
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def __init__(self, site: Site, proxy: list[str] | None = None):
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def __init__(self, site: Site, proxy: list[str] | None = None):
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self.site = site
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self.site = site
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self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
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self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
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@abstractmethod
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def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
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def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
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@@ -90,10 +90,11 @@ class IndeedScraper(Scraper):
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jobs = []
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jobs = []
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new_cursor = None
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new_cursor = None
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filters = self._build_filters()
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filters = self._build_filters()
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search_term = self.scraper_input.search_term.replace('"', '\\"') if self.scraper_input.search_term else ""
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query = self.job_search_query.format(
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query = self.job_search_query.format(
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what=(
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what=(
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f'what: "{self.scraper_input.search_term}"'
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f'what: "{search_term}"'
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if self.scraper_input.search_term
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if search_term
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else ""
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else ""
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),
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),
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location=(
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location=(
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@@ -119,7 +120,7 @@ class IndeedScraper(Scraper):
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)
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)
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if response.status_code != 200:
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if response.status_code != 200:
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logger.info(
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logger.info(
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f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)"
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f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
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)
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)
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return jobs, new_cursor
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return jobs, new_cursor
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data = response.json()
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data = response.json()
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@@ -9,6 +9,8 @@ from __future__ import annotations
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import time
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import time
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import random
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import random
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import regex as re
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import urllib.parse
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from typing import Optional
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from typing import Optional
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from datetime import datetime
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from datetime import datetime
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@@ -51,6 +53,7 @@ class LinkedInScraper(Scraper):
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super().__init__(Site(Site.LINKEDIN), proxy=proxy)
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super().__init__(Site(Site.LINKEDIN), proxy=proxy)
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self.scraper_input = None
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self.scraper_input = None
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self.country = "worldwide"
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self.country = "worldwide"
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self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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"""
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"""
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@@ -194,16 +197,16 @@ class LinkedInScraper(Scraper):
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if metadata_card
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if metadata_card
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else None
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else None
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)
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)
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date_posted = description = job_type = None
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date_posted = None
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if datetime_tag and "datetime" in datetime_tag.attrs:
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if datetime_tag and "datetime" in datetime_tag.attrs:
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datetime_str = datetime_tag["datetime"]
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datetime_str = datetime_tag["datetime"]
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try:
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try:
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date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
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date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
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except:
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except:
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date_posted = None
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date_posted = None
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benefits_tag = job_card.find("span", class_="result-benefits__text")
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job_details = {}
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if full_descr:
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if full_descr:
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description, job_type = self._get_job_description(job_url)
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job_details = self._get_job_details(job_url)
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return JobPost(
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return JobPost(
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title=title,
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title=title,
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@@ -213,18 +216,18 @@ class LinkedInScraper(Scraper):
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date_posted=date_posted,
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date_posted=date_posted,
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job_url=job_url,
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job_url=job_url,
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compensation=compensation,
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compensation=compensation,
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job_type=job_type,
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job_type=job_details.get("job_type"),
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description=description,
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description=job_details.get("description"),
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emails=extract_emails_from_text(description) if description else None,
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job_url_direct=job_details.get("job_url_direct"),
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emails=extract_emails_from_text(job_details.get("description")),
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logo_photo_url=job_details.get("logo_photo_url"),
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)
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)
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def _get_job_description(
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def _get_job_details(self, job_page_url: str) -> dict:
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self, job_page_url: str
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) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
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"""
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"""
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Retrieves job description by going to the job page url
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Retrieves job description and other job details by going to the job page url
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:param job_page_url:
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:param job_page_url:
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:return: description or None
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:return: dict
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"""
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"""
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try:
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try:
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session = create_session(is_tls=False, has_retry=True)
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session = create_session(is_tls=False, has_retry=True)
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@@ -233,9 +236,9 @@ class LinkedInScraper(Scraper):
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)
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)
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response.raise_for_status()
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response.raise_for_status()
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except:
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except:
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return None, None
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return {}
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if response.url == "https://www.linkedin.com/signup":
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if response.url == "https://www.linkedin.com/signup":
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return None, None
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return {}
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soup = BeautifulSoup(response.text, "html.parser")
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soup = BeautifulSoup(response.text, "html.parser")
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div_content = soup.find(
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div_content = soup.find(
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@@ -253,7 +256,14 @@ class LinkedInScraper(Scraper):
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description = div_content.prettify(formatter="html")
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description = div_content.prettify(formatter="html")
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if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
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if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
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description = markdown_converter(description)
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description = markdown_converter(description)
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return description, self._parse_job_type(soup)
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return {
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"description": description,
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"job_type": self._parse_job_type(soup),
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"job_url_direct": self._parse_job_url_direct(soup),
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"logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
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"data-delayed-url"
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),
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}
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|
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def _get_location(self, metadata_card: Optional[Tag]) -> Location:
|
def _get_location(self, metadata_card: Optional[Tag]) -> Location:
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"""
|
"""
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@@ -306,6 +316,23 @@ class LinkedInScraper(Scraper):
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|
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return [get_enum_from_job_type(employment_type)] if employment_type else []
|
return [get_enum_from_job_type(employment_type)] if employment_type else []
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|
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|
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
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|
"""
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|
Gets the job url direct from job page
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||||||
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:param soup:
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:return: str
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|
"""
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job_url_direct = None
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job_url_direct_content = soup.find("code", id="applyUrl")
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|
if job_url_direct_content:
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|
job_url_direct_match = self.job_url_direct_regex.search(
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job_url_direct_content.decode_contents().strip()
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|
)
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|
if job_url_direct_match:
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|
job_url_direct = urllib.parse.unquote(job_url_direct_match.group())
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|
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return job_url_direct
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|
|
||||||
@staticmethod
|
@staticmethod
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||||||
def job_type_code(job_type_enum: JobType) -> str:
|
def job_type_code(job_type_enum: JobType) -> str:
|
||||||
return {
|
return {
|
||||||
|
|||||||
Reference in New Issue
Block a user