.gitignore

@@ -1,6 +0,0 @@
-.venv/
-__pycache__/
-*.pyc
-output.txt
-*.docx
-

answer/1try.txt

@@ -1 +0,0 @@
-ID 2: Data Engineer в Тинькофф, Москва — от 180000 до 250000ID 6: Senior Python Developer в Wildberries, Москва — от 200000 до 300000

data/test.json

@@ -1,72 +0,0 @@
-[
-    {
-        "id": 1,
-        "title": "Python разработчик",
-        "company": "Яндекс",
-        "city": "Москва",
-        "salary_from": 150000,
-        "salary_to": 200000,
-        "skills": ["Python", "SQL", "Django", "PostgreSQL"],
-        "published_at": "2024-01-15"
-    },
-    {
-        "id": 2,
-        "title": "Data Engineer",
-        "company": "Тинькофф",
-        "city": "Москва",
-        "salary_from": 180000,
-        "salary_to": 250000,
-        "skills": ["Python", "SQL", "Spark", "Airflow"],
-        "published_at": "2024-01-20"
-    },
-    {
-        "id": 3,
-        "title": "Backend Developer",
-        "company": "Ozon",
-        "city": "Санкт-Петербург",
-        "salary_from": 130000,
-        "salary_to": 170000,
-        "skills": ["Python", "FastAPI", "MongoDB"],
-        "published_at": "2024-01-18"
-    },
-    {
-        "id": 4,
-        "title": "Data Analyst",
-        "company": "Яндекс",
-        "city": "Москва",
-        "salary_from": 140000,
-        "salary_to": 180000,
-        "skills": ["Python", "SQL", "Tableau"],
-        "published_at": "2024-01-22"
-    },
-    {
-        "id": 5,
-        "title": "Junior Python Developer",
-        "company": "Сбер",
-        "city": "Москва",
-        "salary_from": 100000,
-        "salary_to": 130000,
-        "skills": ["Python", "SQL", "Git"],
-        "published_at": "2024-01-25"
-    },
-    {
-        "id": 6,
-        "title": "Senior Python Developer",
-        "company": "Wildberries",
-        "city": "Москва",
-        "salary_from": 200000,
-        "salary_to": 300000,
-        "skills": ["Python", "SQL", "Kafka", "Kubernetes"],
-        "published_at": "2024-01-28"
-    },
-    {
-        "id": 7,
-        "title": "Full Stack Developer",
-        "company": "Avito",
-        "city": "Москва",
-        "salary_from": 170000,
-        "salary_to": 220000,
-        "skills": ["Python", "JavaScript", "React", "SQL"],
-        "published_at": "2024-01-30"
-    }
-]

vacancy_analyzer.py

@@ -1,89 +1,17 @@
 import json
-from collections import Counter
-def  load_vacancies(filepath: str) -> list[dict]:
+from typing import List, Dict
+def load_vacancies(filepath: str) -> List[Dict]:
     try:
         with open(filepath,"r") as file:
             return json.load(file)
     except:
         print()    
         return []
-def filter_by_city(vacancies: list[dict], city: str) -> list[dict]:
-    return [i for i in vacancies if i.get('city','').lower() == city.lower()]
-def filter_by_skills(vacancies: list[dict], required_skills: list[str]) -> list[dict]:
-    return [i for i in vacancies if all(skill.lower() in set(k.lower() for k in i.get('skills')) for skill in required_skills ) ]
-def filter_by_salary(vacancies: list[dict], min_salary: int) -> list[dict]:
-    return [v for v in vacancies if v.get('salary_to') and v.get('salary_from') and v.get('salary_to')>= min_salary and v.get('salary_from')> min_salary]
-def extract_unique_companies(vacancies: list[dict]) -> list[str]:
-    return list({v.get('company') for v in vacancies if v.get('company')})
-def extract_top_skills(vacancies: list[dict], top_n: int) -> list[tuple[str, int]]:
-    all_skills = []
-    for v in vacancies:
-        all_skills.extend(v.get('skills', [])) 
-    skill_counts = Counter(all_skills)
-    return skill_counts.most_common(top_n)
-def calculate_average_salary(vacancies: list[dict]) -> float:
-    if not vacancies:
-        return 0.0
-    else:
-        salaries = []
-        for v in vacancies:
-            salary_from = v.get('salary_from')
-            salary_to = v.get('salary_to')          
-            if salary_from is not None and salary_to is not None:
-                salaries.append((salary_from + salary_to) / 2)
-            elif salary_from is not None:
-                salaries.append(salary_from)
-            elif salary_to is not None:
-                salaries.append(salary_to)        
-        if not salaries:
-            return 0.0       
-        return sum(salaries) / len(salaries)
-def group_by_company(vacancies: list[dict]) -> dict[str, int]:
-    all_company = []
-    for v in vacancies:
-        all_company.append(v.get('company'))
-    company_count = Counter(all_company)
-    return company_count
-def format_vacancy_short(vacancy: dict) -> str:
-    salary_from = vacancy.get('salary_from')
-    salary_to = vacancy.get('salary_to')  
-    if salary_from is not None and salary_to is not None:
-        salary_str = f"от {salary_from} до {salary_to}"
-    elif salary_from is not None:
-        salary_str = f"от {salary_from}"
-    elif salary_to is not None:
-        salary_str = f"до {salary_to}"
-    else:
-        salary_str = "зарплата не указана"
-    return (f"ID {vacancy.get('id')}: {vacancy.get('title')} в {vacancy.get('company')}, "
-            f"{vacancy.get('city')} — {salary_str}\n")
-def save_filtered_results(vacancies: list[dict], filename: str) -> bool:
-    try:
-        with open(filename,"w") as file:
-            file.writelines(format_vacancy_short(x) for x in vacancies)
-        return 0
-    except:
-        return 1
+def filter_by_city(vacancies: List[Dict], city: str) -> List[Dict]:
+    return [i for i in vacancies if i.get('city').lower() == city.lower()]
 def main():
-    main_list=load_vacancies(input("Write path for json:"))
-    filered_vacancies = filter_by_city(main_list,input("Write city"))
-    skils_list=[]
-    for i in range(int(input("Write number of skills: "))):
-        skils_list.append(input(f"Write №{i + 1} skill: "))
-    filered_vacancies=filter_by_skills(filered_vacancies,skils_list)
-    filered_vacancies = filter_by_salary(filered_vacancies,int(input("Write salary: ")))
-    print("Уникальные компании: ", ", ".join(extract_unique_companies(filered_vacancies)))
-    top_skills = extract_top_skills(filered_vacancies, 5)
-    print(f"Топ-5 навыков:")
-    for skill, count in top_skills:
-        print(f"  {skill}: {count} вакансий")
-    print(f"\nСредняя зарплата: {calculate_average_salary(filered_vacancies):,.0f} руб.")
-    for company, count in group_by_company(filered_vacancies).items():
-        print(f"  {company}: {count} вакансий")
-    if(save_filtered_results(filered_vacancies,input("Write where to save"))):
-        print("Check your path")
-    else:
-        print("Everything is fine, the file is saved")
+    print("Hello World")
+
 if __name__ =="__main__":
-    #вход проги 
+    #òóïî âûâîä 
     main()