{"id":13883404,"url":"https://github.com/serpapi/google-search-results-python","last_synced_at":"2025-04-11T09:33:21.699Z","repository":{"id":29748445,"uuid":"116913347","full_name":"serpapi/google-search-results-python","owner":"serpapi","description":"Google Search Results via SERP API pip Python 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Google Search Results in Python\n\n[![Package](https://badge.fury.io/py/google-search-results.svg)](https://badge.fury.io/py/google-search-results)\n[![Build](https://github.com/serpapi/google-search-results-python/actions/workflows/python-package.yml/badge.svg)](https://github.com/serpapi/google-search-results-python/actions/workflows/python-package.yml)\n\nThis Python package is meant to scrape and parse search results from Google, Bing, Baidu, Yandex, Yahoo, Home Depot, eBay and more, using [SerpApi](https://serpapi.com). \n\nThe following services are provided:\n- [Search API](https://serpapi.com/search-api)\n- [Search Archive API](https://serpapi.com/search-archive-api)\n- [Account API](https://serpapi.com/account-api)\n- [Location API](https://serpapi.com/locations-api) (Google Only)\n\nSerpApi provides a [script builder](https://serpapi.com/demo) to get you started quickly.\n\n## Installation\n\nPython 3.7+\n```bash\npip install google-search-results\n```\n\n[Link to the python package page](https://pypi.org/project/google-search-results/)\n\n## Quick start\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\n    \"q\": \"coffee\", \n    \"location\": \"Austin,Texas\",\n    \"api_key\": \"\u003cyour secret api key\u003e\"\n  })\nresult = search.get_dict()\n```\n\nThis example runs a search for \"coffee\" using your secret API key.\n\nThe SerpApi service (backend)\n- Searches Google using the search: q = \"coffee\"\n- Parses the messy HTML responses\n- Returns a standardized JSON response\nThe GoogleSearch class\n- Formats the request\n- Executes a GET http request against SerpApi service\n- Parses the JSON response into a dictionary\n\nEt voilà...\n\nAlternatively, you can search:\n- Bing using BingSearch class\n- Baidu using BaiduSearch class\n- Yahoo using YahooSearch class\n- DuckDuckGo using DuckDuckGoSearch class\n- eBay using EbaySearch class\n- Yandex using YandexSearch class\n- HomeDepot using HomeDepotSearch class\n- GoogleScholar using GoogleScholarSearch class\n- Youtube using YoutubeSearch class\n- Walmart using WalmartSearch\n- Apple App Store using AppleAppStoreSearch class\n- Naver using NaverSearch class\n\n\nSee the [playground to generate your code.](https://serpapi.com/playground)\n\n## Summary\n- [Google Search Results in Python](#google-search-results-in-python)\n  - [Installation](#installation)\n  - [Quick start](#quick-start)\n  - [Summary](#summary)\n    - [Google Search API capability](#google-search-api-capability)\n    - [How to set SerpApi key](#how-to-set-serp-api-key)\n    - [Example by specification](#example-by-specification)\n    - [Location API](#location-api)\n    - [Search Archive API](#search-archive-api)\n    - [Account API](#account-api)\n    - [Search Bing](#search-bing)\n    - [Search Baidu](#search-baidu)\n    - [Search Yandex](#search-yandex)\n    - [Search Yahoo](#search-yahoo)\n    - [Search Ebay](#search-ebay)\n    - [Search Home depot](#search-home-depot)\n    - [Search Youtube](#search-youtube)\n    - [Search Google Scholar](#search-google-scholar)\n    - [Generic search with SerpApiClient](#generic-search-with-serpapiclient)\n    - [Search Google Images](#search-google-images)\n    - [Search Google News](#search-google-news)\n    - [Search Google Shopping](#search-google-shopping)\n    - [Google Search By Location](#google-search-by-location)\n    - [Batch Asynchronous Searches](#batch-asynchronous-searches)\n    - [Python object as a result](#python-object-as-a-result)\n    - [Python paginate using iterator](#pagination-using-iterator)\n    - [Error management](#error-management)\n  - [Change log](#change-log)\n  - [Conclusion](#conclusion)\n\n### Google Search API capability\nSource code.\n```python\nparams = {\n  \"q\": \"coffee\",\n  \"location\": \"Location Requested\", \n  \"device\": \"desktop|mobile|tablet\",\n  \"hl\": \"Google UI Language\",\n  \"gl\": \"Google Country\",\n  \"safe\": \"Safe Search Flag\",\n  \"num\": \"Number of Results\",\n  \"start\": \"Pagination Offset\",\n  \"api_key\": \"Your SerpApi Key\", \n  # To be match\n  \"tbm\": \"nws|isch|shop\", \n  # To be search\n  \"tbs\": \"custom to be search criteria\",\n  # allow async request\n  \"async\": \"true|false\",\n  # output format\n  \"output\": \"json|html\"\n}\n\n# define the search search\nsearch = GoogleSearch(params)\n# override an existing parameter\nsearch.params_dict[\"location\"] = \"Portland\"\n# search format return as raw html\nhtml_results = search.get_html()\n# parse results\n#  as python Dictionary\ndict_results = search.get_dict()\n#  as JSON using json package\njson_results = search.get_json()\n#  as dynamic Python object\nobject_result = search.get_object()\n```\n[Link to the full documentation](https://serpapi.com/search-api)\n\nSee below for more hands-on examples.\n\n### How to set SerpApi key\n\nYou can get an API key here if you don't already have one: https://serpapi.com/users/sign_up\n\nThe SerpApi `api_key` can be set globally:\n```python\nGoogleSearch.SERP_API_KEY = \"Your Private Key\"\n```\nThe SerpApi `api_key` can be provided for each search:\n```python\nquery = GoogleSearch({\"q\": \"coffee\", \"serp_api_key\": \"Your Private Key\"})\n```\n\n### Example by specification\n\nWe love true open source, continuous integration and Test Driven Development (TDD). \n We are using RSpec to test [our infrastructure around the clock](https://travis-ci.org/serpapi/google-search-results-python) to achieve the best Quality of Service (QoS).\n \nThe directory test/ includes specification/examples.\n\nSet your API key.\n```bash\nexport API_KEY=\"your secret key\"\n```\n\nRun test\n```python\nmake test\n```\n\n### Location API\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({})\nlocation_list = search.get_location(\"Austin\", 3)\nprint(location_list)\n```\n\nThis prints the first 3 locations matching Austin (Texas, Texas, Rochester).\n```python\n[   {   'canonical_name': 'Austin,TX,Texas,United States',\n        'country_code': 'US',\n        'google_id': 200635,\n        'google_parent_id': 21176,\n        'gps': [-97.7430608, 30.267153],\n        'id': '585069bdee19ad271e9bc072',\n        'keys': ['austin', 'tx', 'texas', 'united', 'states'],\n        'name': 'Austin, TX',\n        'reach': 5560000,\n        'target_type': 'DMA Region'},\n        ...]\n```\n\n### Search Archive API\n\nThe search results are stored in a temporary cache.\nThe previous search can be retrieved from the cache for free.\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\"q\": \"Coffee\", \"location\": \"Austin,Texas\"})\nsearch_result = search.get_dictionary()\nassert search_result.get(\"error\") == None\nsearch_id = search_result.get(\"search_metadata\").get(\"id\")\nprint(search_id)\n```\n\nNow let's retrieve the previous search from the archive.\n\n```python\narchived_search_result = GoogleSearch({}).get_search_archive(search_id, 'json')\nprint(archived_search_result.get(\"search_metadata\").get(\"id\"))\n```\nThis prints the search result from the archive.\n\n### Account API\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({})\naccount = search.get_account()\n```\nThis prints your account information.\n\n### Search Bing\n```python\nfrom serpapi import BingSearch\nsearch = BingSearch({\"q\": \"Coffee\", \"location\": \"Austin,Texas\"})\ndata = search.get_dict()\n```\nThis code prints Bing search results for coffee as a Dictionary. \n\nhttps://serpapi.com/bing-search-api\n\n### Search Baidu\n```python\nfrom serpapi import BaiduSearch\nsearch = BaiduSearch({\"q\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints Baidu search results for coffee as a Dictionary. \nhttps://serpapi.com/baidu-search-api\n\n### Search Yandex\n```python\nfrom serpapi import YandexSearch\nsearch = YandexSearch({\"text\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints Yandex search results for coffee as a Dictionary. \n\nhttps://serpapi.com/yandex-search-api\n\n### Search Yahoo\n```python\nfrom serpapi import YahooSearch\nsearch = YahooSearch({\"p\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints Yahoo search results for coffee as a Dictionary. \n\nhttps://serpapi.com/yahoo-search-api\n\n\n### Search eBay\n```python\nfrom serpapi import EbaySearch\nsearch = EbaySearch({\"_nkw\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints eBay search results for coffee as a Dictionary. \n\nhttps://serpapi.com/ebay-search-api\n\n### Search Home Depot\n```python\nfrom serpapi import HomeDepotSearch\nsearch = HomeDepotSearch({\"q\": \"chair\"})\ndata = search.get_dict()\n```\nThis code prints Home Depot search results for chair as Dictionary. \n\nhttps://serpapi.com/home-depot-search-api\n\n### Search Youtube\n```python\nfrom serpapi import YoutubeSearch\nsearch = YoutubeSearch({\"q\": \"chair\"})\ndata = search.get_dict()\n```\nThis code prints Youtube search results for chair as Dictionary. \n\nhttps://serpapi.com/youtube-search-api\n\n### Search Google Scholar\n```python\nfrom serpapi import GoogleScholarSearch\nsearch = GoogleScholarSearch({\"q\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints Google Scholar search results.\n\n### Search Walmart\n```python\nfrom serpapi import WalmartSearch\nsearch = WalmartSearch({\"query\": \"chair\"})\ndata = search.get_dict()\n```\nThis code prints Walmart search results.\n\n### Search Youtube\n```python\nfrom serpapi import YoutubeSearch\nsearch = YoutubeSearch({\"search_query\": \"chair\"})\ndata = search.get_dict()\n```\nThis code prints Youtube search results.\n\n### Search Apple App Store\n```python\nfrom serpapi import AppleAppStoreSearch\nsearch = AppleAppStoreSearch({\"term\": \"Coffee\"})\ndata = search.get_dict()\n```\nThis code prints Apple App Store search results.\n\n### Search Naver\n```python\nfrom serpapi import NaverSearch\nsearch = NaverSearch({\"query\": \"chair\"})\ndata = search.get_dict()\n```\nThis code prints Naver search results.\n\n### Generic search with SerpApiClient\n```python\nfrom serpapi import SerpApiClient\nquery = {\"q\": \"Coffee\", \"location\": \"Austin,Texas\", \"engine\": \"google\"}\nsearch = SerpApiClient(query)\ndata = search.get_dict()\n```\nThis class enables interaction with any search engine supported by SerpApi.com \n\n### Search Google Images\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\"q\": \"coffe\", \"tbm\": \"isch\"})\nfor image_result in search.get_dict()['images_results']:\n    link = image_result[\"original\"]\n    try:\n        print(\"link: \" + link)\n        # wget.download(link, '.')\n    except:\n        pass\n```\n\nThis code prints all the image links, \n and downloads the images if you un-comment the line with wget (Linux/OS X tool to download files).\n\nThis tutorial covers more ground on this topic.\nhttps://github.com/serpapi/showcase-serpapi-tensorflow-keras-image-training\n\n### Search Google News\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\n    \"q\": \"coffe\",   # search search\n    \"tbm\": \"nws\",  # news\n    \"tbs\": \"qdr:d\", # last 24h\n    \"num\": 10\n})\nfor offset in [0,1,2]:\n    search.params_dict[\"start\"] = offset * 10\n    data = search.get_dict()\n    for news_result in data['news_results']:\n        print(str(news_result['position'] + offset * 10) + \" - \" + news_result['title'])\n```\n\nThis script prints the first 3 pages of the news headlines for the last 24 hours.\n\n### Search Google Shopping\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\n    \"q\": \"coffe\",   # search search\n    \"tbm\": \"shop\",  # shopping\n    \"tbs\": \"p_ord:rv\", # ordered by review\n    \"num\": 100\n})\ndata = search.get_dict()\nfor shopping_result in data['shopping_results']:\n    print(shopping_result['position']) + \" - \" + shopping_result['title'])\n\n```\n\nThis script prints all the shopping results, ordered by review order.\n\n### Google Search By Location\n\nWith SerpApi, we can build a Google search from anywhere in the world.\nThis code looks for the best coffee shop for the given cities.\n\n```python\nfrom serpapi import GoogleSearch\nfor city in [\"new york\", \"paris\", \"berlin\"]:\n  location = GoogleSearch({}).get_location(city, 1)[0][\"canonical_name\"]\n  search = GoogleSearch({\n      \"q\": \"best coffee shop\",   # search search\n      \"location\": location,\n      \"num\": 1,\n      \"start\": 0\n  })\n  data = search.get_dict()\n  top_result = data[\"organic_results\"][0][\"title\"]\n```\n\n### Batch Asynchronous Searches\n\nWe offer two ways to boost your searches thanks to the`async` parameter.\n - Blocking - async=false - more compute intensive because the search needs to maintain many connections. (default) \n- Non-blocking - async=true - the way to go for large batches of queries  (recommended)\n\n```python\n# Operating system\nimport os\n\n# regular expression library\nimport re\n\n# safe queue (named Queue in python2)\nfrom queue import Queue\n\n# Time utility\nimport time\n\n# SerpApi search\nfrom serpapi import GoogleSearch\n\n# store searches\nsearch_queue = Queue()\n\n# SerpApi search\nsearch = GoogleSearch({\n    \"location\": \"Austin,Texas\",\n    \"async\": True,\n    \"api_key\": os.getenv(\"API_KEY\")\n})\n\n# loop through a list of companies\nfor company in ['amd', 'nvidia', 'intel']:\n    print(\"execute async search: q = \" + company)\n    search.params_dict[\"q\"] = company\n    result = search.get_dict()\n    if \"error\" in result:\n        print(\"oops error: \", result[\"error\"])\n        continue\n    print(\"add search to the queue where id: \", result['search_metadata'])\n    # add search to the search_queue\n    search_queue.put(result)\n\nprint(\"wait until all search statuses are cached or success\")\n\n# Create regular search\nwhile not search_queue.empty():\n    result = search_queue.get()\n    search_id = result['search_metadata']['id']\n\n    # retrieve search from the archive - blocker\n    print(search_id + \": get search from archive\")\n    search_archived = search.get_search_archive(search_id)\n    print(search_id + \": status = \" +\n          search_archived['search_metadata']['status'])\n\n    # check status\n    if re.search('Cached|Success',\n                 search_archived['search_metadata']['status']):\n        print(search_id + \": search done with q = \" +\n              search_archived['search_parameters']['q'])\n    else:\n        # requeue search_queue\n        print(search_id + \": requeue search\")\n        search_queue.put(result)\n\n        # wait 1s\n        time.sleep(1)\n\nprint('all searches completed')\n```\n\nThis code shows how to run searches asynchronously.\nThe search parameters must have {async: True}. This indicates that the client shouldn't wait for the search to be completed.\nThe current thread that executes the search is now non-blocking, which allows it to execute thousands of searches in seconds. The SerpApi backend will do the processing work.\nThe actual search result is deferred to a later call from the search archive using get_search_archive(search_id).\nIn this example the non-blocking searches are persisted in a queue: search_queue.\nA loop through the search_queue allows it to fetch individual search results.\nThis process can easily be multithreaded to allow a large number of concurrent search requests.\nTo keep things simple, this example only explores search results one at a time (single threaded).\n\n[See example.](https://github.com/serpapi/google-search-results-python/blob/master/tests/test_example.py)\n\n### Python object as a result\n\nThe search results can be automatically wrapped in dynamically generated Python object.\nThis solution offers a more dynamic, fully Oriented Object Programming approach over the regular Dictionary / JSON data structure.\n\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\"q\": \"Coffee\", \"location\": \"Austin,Texas\"})\nr = search.get_object()\nassert type(r.organic_results) == list\nassert r.organic_results[0].title\nassert r.search_metadata.id\nassert r.search_metadata.google_url\nassert r.search_parameters.q, \"Coffee\"\nassert r.search_parameters.engine, \"google\"\n```\n\n### Pagination using iterator\nLet's collect links across multiple search results pages.\n```python\n# to get 2 pages\nstart = 0\nend = 40\npage_size = 10\n\n# basic search parameters\nparameter = {\n  \"q\": \"coca cola\",\n  \"tbm\": \"nws\",\n  \"api_key\": os.getenv(\"API_KEY\"),\n  # optional pagination parameter\n  #  the pagination method can take argument directly\n  \"start\": start,\n  \"end\": end,\n  \"num\": page_size\n}\n\n# as proof of concept \n# urls collects\nurls = []\n\n# initialize a search\nsearch = GoogleSearch(parameter)\n\n# create a python generator using parameter\npages = search.pagination()\n# or set custom parameter\npages = search.pagination(start, end, page_size)\n\n# fetch one search result per iteration \n# using a basic python for loop \n# which invokes python iterator under the hood.\nfor page in pages:\n  print(f\"Current page: {page['serpapi_pagination']['current']}\")\n  for news_result in page[\"news_results\"]:\n    print(f\"Title: {news_result['title']}\\nLink: {news_result['link']}\\n\")\n    urls.append(news_result['link'])\n  \n# check if the total number pages is as expected\n# note: the exact number if variable depending on the search engine backend\nif len(urls) == (end - start):\n  print(\"all search results count match!\")\nif len(urls) == len(set(urls)):\n  print(\"all search results are unique!\")\n```\n\nExamples to fetch links with pagination: [test file](https://github.com/serpapi/google-search-results-python/blob/master/tests/test_example_paginate.py), [online IDE](https://replit.com/@DimitryZub1/Scrape-Google-News-with-Pagination-python-serpapi)\n\n### Error management\n\nSerpApi keeps error management simple.\n - backend service error or search fail\n - client error\n\nIf it's a backend error, a simple error message is returned as string in the server response.\n```python\nfrom serpapi import GoogleSearch\nsearch = GoogleSearch({\"q\": \"Coffee\", \"location\": \"Austin,Texas\", \"api_key\": \"\u003csecret_key\u003e\"})\ndata = search.get_json()\nassert data[\"error\"] == None\n```\nIn some cases, there are more details available in the data object.\n\nIf it's a client error, then a SerpApiClientException is raised.\n\n## Change log\n2023-03-10 @ 2.4.2\n - Change long description to README.md\n\n2021-12-22 @ 2.4.1\n - add more search engine \n   - youtube\n   - walmart\n   - apple_app_store\n   - naver\n - raise SerpApiClientException instead of raw string in order to follow Python guideline 3.5+\n - add more unit error tests for serp_api_client\n\n2021-07-26 @ 2.4.0\n - add page size support using num parameter\n - add youtube search engine\n\n2021-06-05 @ 2.3.0\n - add pagination support\n\n2021-04-28 @ 2.2.0\n - add get_response method to provide raw requests.Response object\n\n2021-04-04 @ 2.1.0\n - Add home depot search engine\n - get_object() returns dynamic Python object\n \n2020-10-26 @ 2.0.0\n - Reduce class name to \u003cengine\u003eSearch\n - Add get_raw_json\n\n2020-06-30 @ 1.8.3\n - simplify import\n - improve package for python 3.5+\n - add support for python 3.5 and 3.6\n\n2020-03-25 @ 1.8\n - add support for Yandex, Yahoo, Ebay\n - clean-up test\n\n2019-11-10 @ 1.7.1\n - increase engine parameter priority over engine value set in the class\n\n2019-09-12 @ 1.7\n - Change  namespace \"from lib.\" instead: \"from serpapi import GoogleSearch\"\n - Support for Bing and Baidu\n\n2019-06-25 @ 1.6\n - New search engine supported: Baidu and Bing\n\n## Conclusion\nSerpApi supports all the major search engines. Google has the more advance support with all the major services available: Images, News, Shopping and more..\nTo enable a type of search, the field tbm (to be matched) must be set to:\n\n * isch: Google Images API.\n * nws: Google News API.\n * shop: Google Shopping API.\n * any other Google service should work out of the box.\n * (no tbm parameter): regular Google search.\n\nThe field `tbs` allows to customize the search even more.\n\n[The full documentation is available here.](https://serpapi.com/search-api)\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fserpapi%2Fgoogle-search-results-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fserpapi%2Fgoogle-search-results-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fserpapi%2Fgoogle-search-results-python/lists"}