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enh: linkedin company logo (#141)
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@@ -27,4 +27,4 @@ print("outputted to jobs.csv")
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# jobs.to_xlsx('jobs.xlsx', index=False)
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# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
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# display(jobs)
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# display(jobs)
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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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# New York, NY
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# Dallas, TX
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# 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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offset=offset,
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# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
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)
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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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offset += results_in_each_iteration
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