mirror of https://github.com/Bunsly/JobSpy
fix(indeed): readd param
parent
0d150d519f
commit
3e93454738
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@ -69,7 +69,7 @@ Optional
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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_type'
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├── easy_apply (bool): filters for jobs that are hosted on the job board site (not supported on Indeed)
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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 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)
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@ -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 = "1.1.50"
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version = "1.1.51"
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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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@ -41,7 +41,7 @@ def scrape_jobs(
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) -> pd.DataFrame:
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) -> pd.DataFrame:
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"""
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"""
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Simultaneously scrapes job data from multiple job sites.
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Simultaneously scrapes job data from multiple job sites.
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:return: results_wanted: pandas dataframe containing job data
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:return: pandas dataframe containing job data
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"""
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"""
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SCRAPER_MAPPING = {
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SCRAPER_MAPPING = {
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Site.LINKEDIN: LinkedInScraper,
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Site.LINKEDIN: LinkedInScraper,
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@ -150,6 +150,15 @@ class IndeedScraper(Scraper):
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""".format(
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""".format(
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start=self.scraper_input.hours_old
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start=self.scraper_input.hours_old
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)
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)
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elif self.scraper_input.easy_apply:
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filters_str = """
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filters: {
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keyword: {
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field: "indeedApplyScope",
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keys: ["DESKTOP"]
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}
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}
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"""
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elif self.scraper_input.job_type or self.scraper_input.is_remote:
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elif self.scraper_input.job_type or self.scraper_input.is_remote:
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job_type_key_mapping = {
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job_type_key_mapping = {
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JobType.FULL_TIME: "CF3CP",
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JobType.FULL_TIME: "CF3CP",
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