Get jobs from categories

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Tags: #remoteok #jobs #csv #snippet
Author: Sanjeet Attili​
With this notebook, you will be able to get jobs offer from Remoteok:
URL: Job offer url.
TITLE: Job title.
COMPANY: Company name.
TAGS: Tags link to job.
LOCATION: Location link to job.
PUBLICATION_DATE: Date of publication.
Input
Import libraries
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import pandas as pd
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import requests
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from datetime import datetime
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import time
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Setup Remoteok
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categories = ['machine learning',
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              'data science',
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              'nlp',
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              'deep learning',
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              'computer vision',
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              'data',
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              'natural language processing',
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              'data engineer']
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date_from  = -30 ### this is 30 days from now => must be negative
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Variables
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csv_output = "REMOTIVE_JOBS.csv"
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Model
Get jobs from RemoteOk
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REMOTEOK_API = "https://remoteok.com/api"
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REMOTEOK_DATETIME = "%Y-%m-%dT%H:%M:%S"
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NAAS_DATETIME = "%Y-%m-%d %H:%M:%S"
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​
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def get_jobs(remoteok_url, categories):
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    df = pd.DataFrame()
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    headers = {
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            'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36',
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        }
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    index=0
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    for tag in categories:
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        url = remoteok_url + f"?tag={tag}"
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        res = requests.get(url, headers=headers)
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        try:
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            res.raise_for_status()
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        except requests.HTTPError as e:
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            return e
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        job_details = res.json()
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        if len(job_details)==1:
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            continue
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        else:
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            for idx, job in enumerate(job_details):
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                if idx!=0:
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                    date = job['date'].split('+')[0]
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                    publication_time = datetime.strptime(date, REMOTEOK_DATETIME).timestamp()
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                    required_time = time.time() + date_from* 24 * 60 * 60  ### time in seconds
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                    if publication_time >= required_time:
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                        df.loc[index, 'URL'] = job.get('url')
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                        df.loc[index, 'TITLE'] = job.get('position')
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                        df.loc[index, 'COMPANY'] = job.get('company')
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                        df.loc[index, 'TAGS'] = ", ".join(job.get('tags'))
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                        df.loc[index, 'LOCATION'] = job.get('location')
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                        df.loc[index, 'PUBLICATION_DATE'] = datetime.fromtimestamp(publication_time).strftime(NAAS_DATETIME)
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                        index+=1
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    df = df.sort_values(by='PUBLICATION_DATE', ascending=False)
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    return df
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​
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df_jobs = get_jobs(REMOTEOK_API, categories)
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df_jobs.head(5)
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Output
Save dataframe in csv
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df_jobs.to_csv(csv_output, index=False)
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Contents

Input

Model

Output