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Multiple job types for Indeed, urgent keywords column (#56)

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* enh(indeed): mult job types

* feat(jobs):  urgent kws

* fix(indeed): use new session obj per request

* fix: emails as comma separated in output

* fix: put num urgent words in output

* chore: readme
This commit is contained in:
Cullen Watson
2023-10-10 11:23:04 -05:00
committed by GitHub
parent 628f4dee9c
commit e5353e604d
12 changed files with 271 additions and 247 deletions
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14
examples/JobSpy_Demo.py
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@@ -6,23 +6,23 @@ jobs: pd.DataFrame = scrape_jobs(
search_term="software engineer",
location="Dallas, TX",
results_wanted=50, # be wary the higher it is, the more likey you'll get blocked (rotating proxy should work tho)
country_indeed='USA',
country_indeed="USA",
offset=25 # start jobs from an offset (use if search failed and want to continue)
# 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
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')
jobs.to_csv("./jobs.csv", index=False)
print("outputted to jobs.csv")
# 3: output to .xlsx
# jobs.to_xlsx('jobs.xlsx', index=False)