Merge branch 'only_task'

.gitignore

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

answer/1try.txt

@@ -0,0 +1 @@
+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

@@ -0,0 +1,72 @@
+[
+    {
+        "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

@@ -1,17 +1,89 @@
 import json
-from typing import List, Dict
-def load_vacancies(filepath: str) -> List[Dict]:
+from collections import Counter
+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_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 main():
-    print("Hello World")
-
+    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")
 if __name__ =="__main__":
-    #òóïî âûâîä 
+    #вход проги 
     main()