Yandex search api python

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Search library for yandex.ru search engine.

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fluquid/yandex-search

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README.rst

Search library for yandex.ru search engine.

Yandex allows 10,000 searches per day when registered with a validated (international) mobile number.

>>> yandex = yandex_search.Yandex(api_user='asdf', api_key='asdf') >>> yandex.search('"Interactive Saudi"').items [< "snippet": "Your Software Development Partner In Saudi Arabia . Since our early days in 2003, our main goal in Interactive Saudi Arabia has been: \"To earn customer respect and maintain long-term loyalty\".", "url": "http://www.interactive.sa/en", "title": "Interactive Saudi Arabia Limited", "domain": "www.interactive.sa" >]

• register account: https://passport.yandex.ru/registration
  • use google translate addon (right-click «translate page») * provide an (international) mobile phone number to unlock 10k queries/day
  • Navigate to «Settings»
    • switch language to english in bottom left (En/Ru)
    • enter email for «Email notifications»
    • set «Search type» to «Worldwide»
    • set «Main IP-address» to your querying machine
    • «I accept the terms of License Agreement»
    • Save

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    Simple Python implementation of the Yandex search API (https://tech.yandex.com/xml/)

    License

    S0mbre/yandexml

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    README.md

    Simple Python implementation of the Yandex search API (https://tech.yandex.com/xml/)

    • class-based Yandexml engine for a given Yandex account (username), API key and host IP
    • all current Yandex XML API constraints honored in code (search query length etc.)
    • request available daily / hourly limits
    • return search results in Python native objects (dict, list), as well as JSON and formatted text
    • output results to file
    • full Unicode support
    • handle Yandex captchas when robot protection activates on the server side
    • automatic host IP lookup (with several whats-my-ip online services)
    • use requests package for HTTP communication
    • easy CLI or use engine manually in Python
    • Python 3x compatible (2x not supported so far. and hardly will be)
    • check you’ve got Python 3.7 or later
    • pip install -r requirements.txt (will install/upgrade requests and fire)

    1. Command-line interface (CLI)

    python yxml.py —username —apikey run

    • (re)set engine parameters, e.g. switch mode to «ru» and ip to 127.0.0.1: r —mode=ru ip=127.0.0.1
    • view current engine parameters: v or v 2 or v 3 (output more detail)
    • search (output results to console): q «SEARCH QUERY»
    • search and save results to file: q «SEARCH QUERY» —txtformat=[xml|json|txt] —outfile=»filename[.xml]»
    • search without grouping by domain: q «SEARCH QUERY» —grouped=False
    • output previous search results to file: o —txtformat=json —outfile=»filename.json»
    • get limits for next hour / day: l
    • get all limits: L
    • create Yandex logo: y —background==[red|white|black|any. ] —fullpage=[True|False] —title=’Logo’ —outfile=[None|»myfile.html»]
    • logo with custom CSS styles: y —fullpage=True —outfile=»myfile.html» —width=»100px» —font-size=»12pt» —font-family=»Arial»
    • solve sample captcha (download sample using Yandex XML API, use passed captcha_solver to solve): c —retries=[1|2|. ]
    • show help (usage string): h
    • show detailed help: h 2
    • quit CLI: w

    2. In Python code

    See comments in yxmlengine.py and examples in tester.py.

    Источник

    How to Scrape Yandex Search Results: A Step-by-Step Guide

    In this tutorial, you’ll learn how to use Yandex Scraper API to scrape Yandex search results. Before we begin, let’s briefly discuss what Yandex Search Engine Results Pages (SERPs) look like and why it’s difficult to scrape them.

    Yandex SERP overview

    Like Google, Bing, or any other search engine, Yandex provides a way to search the web. Yandex SERP displays search results based on various factors, including the relevance of the content to the search query, the website’s quality and authority, the user’s language and location, and other personalized factors. Users can refine their search results by using filters and advanced search options.

    Let’s say we searched for the term “iPhone.” You should see something similar to the below:

    Notice the results page has two different sections: Advertisements on top and organic search results below. The organic search results section includes web pages that are not paid for and are displayed based on their relevance to the search query, as determined by Yandex’s search algorithm.

    On the other hand, you can identify ads by a label such as «Sponsored» or «Advertisement.» They are displayed based on the keywords used in the search query and the advertiser’s bid for those keywords. The ads usually include basic details, such as the title, the price, and the link to the product on the Yandex market.

    The pain points of scraping Yandex

    One of the key challenges of scraping Yandex is its CAPTCHA protection. See the screenshot below:

    Yandex has a strict anti-bot system to prevent scrapers from extracting data programmatically from the Yandex search engine. They can block your IP address if the CAPTCHA is triggered frequently. Moreover, they constantly update the anti-bot system, which is tough to keep up with. This makes scraping SERPs at scale complicated, and raw scripts require frequent maintenance to adapt to the changes.

    Fortunately, our Yandex Scraper API is an excellent solution to bypass Yandex’s anti-bot system. The Scraper API can scale on demand by using sophisticated crawling methods and rotating proxies. In the next section, we’ll explore how you can take advantage of it to scrape Yandex using Python.

    Setting up the environment

    Begin by downloading and installing Python from the official website. If you already have Python installed, make sure you have the latest version.

    To scrape Yandex, we’ll use two Python libraries: requests and pandas. You can install them using Python’s package manager pip with the following command:

    python -m pip install requests pandas 

    The requests module will enable you to interact with the API by making network requests, and you’ll be able to store the results using pandas.

    Yandex Scraper API query parameters

    Since the Yandex Scraper API is part of our SERP Scraper API, let’s get to know some query parameters for a smooth start. Essentially, the API supports two different ways of searching Yandex:

    1. Search by URL

    When searching by URL, you must set the source to yandex , and the url should be a valid Yandex URL. You can also tell the API what user agent type to use by adding an extra parameter: user_agent_type . If needed, you can enable Javascript rendering by using the render parameter. Lastly, you can use the callback_url parameter to specify a URL where the server should send a response after processing the request.

    2. Search by query

    In this tutorial, we’ll use this method. When utilizing this technique, you need to set the source to yandex_search since you’ll be looking for a term on Yandex search results. You need to specify the term that you want to search in the query parameter.

    The yandex_search source also supports additional parameters such as domain , pages , start_page , limit , locale , and geo_location . The domain parameter allows users to choose a specific Top-level Domain (TLD). For example, if you set it to com the result will only consist of websites with .com TLD. Available domains include com, ru, ua, by, kz, tr.

    The pages parameter sets the number of pages to retrieve from the search result. The start_page parameter tells from which result page to begin. limit retrieves a certain number of results per page. Using the geo_location parameter, you can tell the API to use a specific geographical location. Lastly, the locale parameter customizes the Accept-Language header, which allows the user to gather data in a different language. Currently, it supports the following values: en, ru, by, fr, de, id, kk, tt, tr, uk. Visit our documentation to find out more about parameters and their values.

    Scraping Yandex Search Pages for any keyword

    Now that everything’s ready, let’s write a Python script to interact with the Yandex SERP and retrieve results for any keyword.

    1. Import required libraries

    Start by importing the libraries that you’ve installed in the previous step:

    import requests import pandas as pd 

    2. Prepare a payload

    Next, prepare a payload as shown below:

    payload =  'source': 'yandex_search', 'domain': 'com', 'query': 'what is web scraping', 'start_page': 1, 'pages': 5 >  

    Using the above payload, we’re searching Yandex for the term “what is web scraping.” We’re telling the scraper to retrieve search results that only include websites with the domain .com from the first to the fifth page.

    3. Send a POST request

    Next, we need to make a POST request to the Yandex Scraper API. To do that, use the requests library you’ve imported previously:

    credentials = ('USERNAME', 'PASSWORD') response = requests.post( 'https://realtime.oxylabs.io/v1/queries', auth=credentials, json=payload, )  

    Note that we have declared a tuple named credentials . For the code to work, you’ll have to replace the USERNAME and PASSWORD with the authentication credentials you’ve received from us. If you don’t have them, you can sign up and get a 1-week free trial.

    We use the POST method of the requests library to send the payload to the URL https://realtime.oxylabs.io/v1/queries . We also pass the authentication credentials and the payload as JSON.

    Next, let’s print the result with the following line:

    print(response.status_code, response.content)  

    It’ll print the HTTP status code and the content of the response. A successful Yandex scraping request will return a 200 status code, but if you encounter a different response, we recommend visiting our documentation, where we’ve detailed common response codes.

    4. Export data into a CSV/JSON file

    To export the data into a CSV or JSON format, you must first create a data frame:

    df = pd.DataFrame(response.json()) 

    With this code, you’re using the pandas library to pass the response that you’ve received by calling the json() function. Now, you can simply export the data frame into JSON as below:

    df.to_json("yandex_result.json", orient="records") 

    Similarly, you can export the results into CSV as well using the following code:

    df.to_csv("yandex_result.csv", index=False) 

    Once you execute the code, the script will create two new files in the current directory with the response results.

    Conclusion

    While scraping Yandex SERPs is extremely challenging, by following the steps outlined in this article and using the provided Python code, you can easily scrape Yandex search results for any chosen keyword and export the data into a CSV or JSON file. With the help of Yandex Scraper API, you can bypass Yandex’s anti-bot measures and scrape SERPs at scale.

    If you require assistance or want to know more, feel free to contact us via email or live chat.

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