utils.py

import requests
import os
import json
from dotenv import load_dotenv

load_dotenv()

domain = os.environ.get("DOMAIN")


def get_token():
    """
    Returnează token-ul necesar pentru a face request-uri către API.
    :return: token-ul necesar pentru a face request-uri către API
    """
    endpoint = os.environ.get("TOKEN_ROUTE")
    email = os.environ.get("EMAIL")
    headers = {"User-Agent": "Mozilla/5.0"}
    url = f"{domain}{endpoint}"
    response = requests.post(url, json={"email": email}, headers=headers)
    return response.json()["access"]


def create_job(**kwargs):
    job = {}
    job.update(kwargs)
    return job


def publish_or_update(data):

    if not data:
        print("No jobs Available")
        return
    
    route = os.environ.get("ADD_JOBS_ROUTE")
    url = f"{domain}{route}"
    token = os.environ.get("TOKEN") if os.environ.get("TOKEN") else get_token()

    headers = {"Content-Type": "application/json", "Authorization": f"Bearer {token}", "User-Agent": "Mozilla/5.0"}

    res = requests.post(url, headers=headers, json=data)

    status_code = res.status_code

    if status_code == 200:
        company = data[0].get("company")
        total_jobs = len(data)

        print(f"Successfully added {total_jobs} jobs for {company} company.")
    else:
        raise Exception(f"Failed to add jobs. Status code: {status_code}")


def publish_logo(company, logo_url):
    content_type = "application/json"
    requests.post(
        "https://api.peviitor.ro/v1/logo/add/",
        headers={"Content-Type": content_type},
        json=[{"id": company, "logo": logo_url}],
    )


def show_jobs(data):
    print(json.dumps(data, indent=4))


def translate_city(city):
    city = city.replace(" ", "_")
    cities = {
        # This is general for all scrapers
        "bucharest": "Bucuresti",
        "cluj": "Cluj-Napoca",
        # This is for Arabesque Scraper
        "targul-mures": "Targu-Mures",
        "militari": "Bucuresti",
        ############################
        # This is for Vodafone Scraper
        "cluj_napoca": "Cluj-Napoca",
        "targu_mures": "Targu-Mures",
        "pipera": "Bucuresti",
        ############################
        # This is for ppt
        "campulung_muscel": "Campulung",
        # This is for Strabag
        "petrobrazi": "Ploiesti",
        # This is for CARTOFISSERIE
        "Satu-Mare": "Satu Mare",
        "Piatra_Neamt": "Piatra Neamt",
    }

    if cities.get(city.lower()):
        return cities.get(city.lower())
    else:
        return city.replace("_", " ")


def acurate_city_and_county(**kwargs):
    """
    Returns a dictionary containing accurate city and county information.

    Keyword Arguments:
    **kwargs -- key-value pairs representing city and county information

    Returns:
    A dictionary containing accurate city and county information.
    """
    city_and_county = {}
    if kwargs:
        city_and_county.update(kwargs)
    else:
        city_and_county = {
            "Satu_Mare": {"city": "Satu Mare", "county": "Satu Mare"},
            "Iasi": {"city": "Iasi", "county": "Iasi"},
            "Piatra_Neamt": {"city": "Piatra-Neamt", "county": "Neamt"},
            "Ramnicu_Valcea": {"city": "Ramnicu Valcea", "county": "Valcea"},
        }

    return city_and_county


def get_jobtype(sentence, **kwargs):
    """
    Get the job types mentioned in a sentence.

    Args:
        sentence (str): The sentence to analyze.
        **kwargs: Additional keyword arguments.
            jobs_typse (list): Additional job types to consider.

    Returns:
        list: A list of job types mentioned in the sentence.
    """

    jobs_typse = ["on-site", "remote", "hybrid"]
    jobs_typse.extend(kwargs.get("jobs_typse", []))

    sentence = sentence.lower().replace("_", "-").replace("onsite", "on-site")

    types = [jobtype for jobtype in jobs_typse if jobtype in sentence.lower()]

    return list(set(types))