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https://github.com/Bunsly/JobSpy.git
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6 Commits
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22
.github/workflows/python-test.yml
vendored
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22
.github/workflows/python-test.yml
vendored
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@@ -0,0 +1,22 @@
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name: Python Tests
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on:
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pull_request:
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branches:
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- main
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jobs:
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test:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: '3.8'
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- name: Install dependencies
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run: |
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pip install poetry
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poetry install
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- name: Run tests
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run: poetry run pytest src/tests/test_all.py
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2
poetry.toml
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2
poetry.toml
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@@ -0,0 +1,2 @@
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[virtualenvs]
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in-project = true
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@@ -1,10 +1,11 @@
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[tool.poetry]
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name = "python-jobspy"
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version = "1.1.60"
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version = "1.1.65"
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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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homepage = "https://github.com/Bunsly/JobSpy"
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readme = "README.md"
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keywords = ['jobs-scraper', 'linkedin', 'indeed', 'glassdoor', 'ziprecruiter']
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packages = [
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{ include = "jobspy", from = "src" }
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@@ -189,7 +189,9 @@ def scrape_jobs(
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job_data["salary_source"] = SalarySource.DESCRIPTION.value
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job_data["salary_source"] = (
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job_data["salary_source"] if job_data["min_amount"] else None
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job_data["salary_source"]
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if "min_amount" in job_data and job_data["min_amount"]
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else None
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)
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job_df = pd.DataFrame([job_data])
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jobs_dfs.append(job_df)
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@@ -92,7 +92,7 @@ class Country(Enum):
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JAPAN = ("japan", "jp")
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KUWAIT = ("kuwait", "kw")
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LUXEMBOURG = ("luxembourg", "lu")
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MALAYSIA = ("malaysia", "malaysia")
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MALAYSIA = ("malaysia", "malaysia:my", "com")
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MEXICO = ("mexico", "mx", "com.mx")
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MOROCCO = ("morocco", "ma")
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NETHERLANDS = ("netherlands", "nl", "nl")
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@@ -236,7 +236,7 @@ class LinkedInScraper(Scraper):
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"""
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try:
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response = self.session.get(
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f"{self.base_url}/jobs-guest/jobs/api/jobPosting/{job_id}", timeout=5
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f"{self.base_url}/jobs/view/{job_id}", timeout=5
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)
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response.raise_for_status()
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except:
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@@ -198,6 +198,7 @@ def extract_salary(
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if not salary_str:
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return None, None, None, None
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annual_max_salary = None
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min_max_pattern = r"\$(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)\s*[-—–]\s*(?:\$)?(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)"
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def to_int(s):
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@@ -238,6 +239,8 @@ def extract_salary(
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annual_max_salary = max_salary
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# Ensure salary range is within specified limits
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if not annual_max_salary:
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return None, None, None, None
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if (
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lower_limit <= annual_min_salary <= upper_limit
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and lower_limit <= annual_max_salary <= upper_limit
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@@ -200,7 +200,7 @@ class ZipRecruiterScraper(Scraper):
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script_tag = soup.find("script", type="application/json")
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if script_tag:
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job_json = json.loads(script_tag.string)
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job_url_val = job_json["model"]["saveJobURL"]
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job_url_val = job_json["model"].get("saveJobURL", "")
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m = re.search(r"job_url=(.+)", job_url_val)
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if m:
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job_url_direct = m.group(1)
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@@ -4,11 +4,15 @@ import pandas as pd
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def test_all():
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result = scrape_jobs(
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site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
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search_term="software engineer",
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site_name=[
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"linkedin",
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"indeed",
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"glassdoor",
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], # ziprecruiter needs good ip, and temp fix to pass test on ci
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search_term="engineer",
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results_wanted=5,
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)
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assert (
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isinstance(result, pd.DataFrame) and not result.empty
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isinstance(result, pd.DataFrame) and len(result) == 15
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), "Result should be a non-empty DataFrame"
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@@ -2,10 +2,12 @@ from ..jobspy import scrape_jobs
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import pandas as pd
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def test_indeed():
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def test_glassdoor():
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result = scrape_jobs(
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site_name="glassdoor", search_term="software engineer", country_indeed="USA"
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site_name="glassdoor",
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search_term="engineer",
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results_wanted=5,
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)
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assert (
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isinstance(result, pd.DataFrame) and not result.empty
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isinstance(result, pd.DataFrame) and len(result) == 5
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), "Result should be a non-empty DataFrame"
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@@ -4,8 +4,10 @@ import pandas as pd
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def test_indeed():
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result = scrape_jobs(
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site_name="indeed", search_term="software engineer", country_indeed="usa"
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site_name="indeed",
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search_term="engineer",
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results_wanted=5,
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)
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assert (
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isinstance(result, pd.DataFrame) and not result.empty
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isinstance(result, pd.DataFrame) and len(result) == 5
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), "Result should be a non-empty DataFrame"
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@@ -3,10 +3,7 @@ import pandas as pd
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def test_linkedin():
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result = scrape_jobs(
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site_name="linkedin",
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search_term="software engineer",
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)
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result = scrape_jobs(site_name="linkedin", search_term="engineer", results_wanted=5)
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assert (
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isinstance(result, pd.DataFrame) and not result.empty
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isinstance(result, pd.DataFrame) and len(result) == 5
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), "Result should be a non-empty DataFrame"
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@@ -4,10 +4,9 @@ import pandas as pd
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def test_ziprecruiter():
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result = scrape_jobs(
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site_name="zip_recruiter",
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search_term="software engineer",
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site_name="zip_recruiter", search_term="software engineer", results_wanted=5
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)
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assert (
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isinstance(result, pd.DataFrame) and not result.empty
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isinstance(result, pd.DataFrame) and len(result) == 5
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), "Result should be a non-empty DataFrame"
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