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255 changes: 255 additions & 0 deletions parcing_4.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "code",
"source": [
"from pprint import pprint\n",
"from bs4 import BeautifulSoup as bs\n",
"import requests\n",
"import pymongo as pm"
],
"metadata": {
"id": "NetlqVRWTCC1"
},
"execution_count": 48,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### Task 1 Парсинг вакансий с hh.ru"
],
"metadata": {
"id": "hl1lg9CwUmVA"
}
},
{
"cell_type": "code",
"source": [
"User_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.0.0 YaBrowser/22.11.0.2419 Yowser/2.5 Safari/537.36'\n",
"URL_first_page = 'https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1'\n",
"\n",
"headers = {\n",
" 'User-Agent': User_agent,\n",
"}"
],
"metadata": {
"id": "b-loiR9aTCID"
},
"execution_count": 49,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def parse_hh(url_page, headers, result=[], index_page=1):\n",
" response = requests.get(url_page, headers=headers)\n",
" if response.status_code != 200:\n",
" print('Парсинг завершен')\n",
" return result\n",
" else:\n",
" print('Cтраница №%d, ссылка: %s'%(index_page, response.url))\n",
"\n",
" dom = bs(response.content, 'html.parser')\n",
" vacancies = dom.find_all('div', {'class': 'vacancy-serp-item__layout'})\n",
" for vacancy in vacancies:\n",
" result.append(parse_vacancy_hh(vacancy))\n",
"\n",
" link_next_page = dom.find('a', {'data-qa': 'pager-next'})\n",
" if link_next_page:\n",
" link_next_page = 'https://hh.ru' + link_next_page['href']\n",
" else:\n",
" print('Парсинг завершен')\n",
" return result\n",
"\n",
" result = parse_hh(link_next_page, headers, result, index_page+1) \n",
" return result\n",
" \n",
"def parse_vacancy_hh(dom_vacancy):\n",
" vacancy_name = dom_vacancy.find('a').text\n",
"\n",
" vacancy_salary = dom_vacancy.find('span', {'class', 'bloko-header-section-3'})\n",
" if vacancy_salary:\n",
" vacancy_salary = vacancy_salary.text\n",
" min_salary, max_salary, currency_salary = clean_salary(vacancy_salary)\n",
" else:\n",
" min_salary, max_salary, currency_salary = None, None, None\n",
"\n",
" vacancy_link = dom_vacancy.find('a')['href']\n",
" \n",
" return {\n",
" 'vacancy_name': vacancy_name,\n",
" 'vacancy_salary': vacancy_salary,\n",
" 'min_salary': min_salary,\n",
" 'max_salary': max_salary,\n",
" 'currency_salary': currency_salary,\n",
" 'vacancy_link': vacancy_link,\n",
" 'vacancy_source': 'hh.ru',\n",
" }\n",
"\n",
"def clean_salary(vacancy_salary_text, min_salary=None, max_salary=None, currency_salary=None):\n",
" list_salary = vacancy_salary_text.replace('\\u202f', '').split()\n",
" for i in range(len(list_salary) - 1):\n",
" if list_salary[i] == 'от':\n",
" min_salary = int(list_salary[i + 1])\n",
" elif list_salary[i] == 'до':\n",
" max_salary = int(list_salary[i + 1])\n",
" elif list_salary[i] == '–':\n",
" min_salary = int(list_salary[i - 1])\n",
" max_salary = int(list_salary[i + 1])\n",
" currency_salary = list_salary[-1]\n",
"\n",
" return min_salary, max_salary, currency_salary"
],
"metadata": {
"id": "nVxbHP0RTNu8"
},
"execution_count": 50,
"outputs": []
},
{
"cell_type": "code",
"source": [
"result = parse_hh(URL_first_page, headers)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "knn1xMkaTNyK",
"outputId": "8eacecfe-cc26-425f-fbe5-78cca625caf6"
},
"execution_count": 51,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cтраница №1, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1\n",
"Cтраница №2, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=1&hhtmFrom=vacancy_search_list\n",
"Cтраница №3, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=2&hhtmFrom=vacancy_search_list\n",
"Cтраница №4, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=3&hhtmFrom=vacancy_search_list\n",
"Cтраница №5, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=4&hhtmFrom=vacancy_search_list\n",
"Cтраница №6, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=5&hhtmFrom=vacancy_search_list\n",
"Cтраница №7, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=6&hhtmFrom=vacancy_search_list\n",
"Cтраница №8, ссылка: https://hh.ru/search/vacancy?search_field=name&search_field=company_name&search_field=description&text=Data+Scientist&from=suggest_post&customDomain=1&page=7&hhtmFrom=vacancy_search_list\n",
"Парсинг завершен\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(f'Вакансия: {result[0]}\\nКол-во вакансий: {len(result)}')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LiWF5lKiU23P",
"outputId": "64e2e897-f8ba-422b-a2a5-462f89b4039c"
},
"execution_count": 52,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Вакансия: {'vacancy_name': 'Специалист по углубленной аналитике данных (Data scientist)', 'vacancy_salary': None, 'min_salary': None, 'max_salary': None, 'currency_salary': None, 'vacancy_link': 'https://hh.ru/vacancy/72920605?from=vacancy_search_list&query=Data+Scientist', 'vacancy_source': 'hh.ru'}\n",
"Кол-во вакансий: 143\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"### Task 2 Перенос данных в базу"
],
"metadata": {
"id": "DmkARgQrVzjK"
}
},
{
"cell_type": "code",
"source": [
"client = pm.MongoClient()\n",
"\n",
"db = client['vacancies_ds']\n",
"collection_of_ds_vacancies = db['Data_Scientist']"
],
"metadata": {
"id": "4gOSlK6TTzfD"
},
"execution_count": 53,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def check_and_save_vacancies_in_db(vacancies):\n",
" for vacancy in vacancies:\n",
" if not len(list(collection_of_ds_vacancies.find({'vacancy_link': vacancy['vacancy_link']}))):\n",
" collection_of_ds_vacancies.insert_one(vacancy)"
],
"metadata": {
"id": "6r-cAODZT1hG"
},
"execution_count": 54,
"outputs": []
},
{
"cell_type": "code",
"source": [
"check_and_save_vacancies_in_db(result)\n",
"result_find = list(collection_of_ds_vacancies.find())"
],
"metadata": {
"id": "Qh8URYTKT1k4"
},
"execution_count": 55,
"outputs": []
},
{
"cell_type": "code",
"source": [
"len(result_find)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "7gGUia1IUC0r",
"outputId": "2d2a932f-45f6-4dff-e68f-390406678133"
},
"execution_count": 56,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"143"
]
},
"metadata": {},
"execution_count": 56
}
]
}
]
}