7/2/2023 0 Comments Parsing yahoo finance news![]() ![]() Matched_string = ''.join(re.findall(r'root\.App\.main = (.*) \n }\(this\)\) \n ', str(all_script_tags)))įor key, value in dict(matched_string_json).items():įull_exchange_name = valueĮxchange_time_zone_name = value Yahoo_finance_header_stocks_news.py import requests, lxml, json, re, datetime Yahoo_finance_main.py from yahoo_finance_right_side_stocks import yahoo_get_right_side_stocksįrom yahoo_finance_header_stocks_news import ( The approach was the same as in the previous section of the post, where the received response was converted to a json string for further manipulation. Note: User-Agent needs to be used, otherwise, it will throw a 403 forbidden. In total, there're 11 URLs ( might be changed in the future) but you can make a 1 request call with additional symbols added to the URL string without need to make 11 URL calls async. In the dev tools network tab, you can see requests being sent to the server with GET method, thus you can call them directly to get a json string. ![]() Get Scrolling News Results for yahoo_news_index in matched_string_json: Get Multiuse News Results for multiuse_index, multiuse_news in enumerate(matched_string_json_multiuse): Get Top News Video Results for top_news_video_index, top_news_video in enumerate(matched_string_json_video): Get Top News Results for top_news_result_index, top_news in enumerate(matched_string_json_stream): "exchangeTimezoneName": "America/New_York", If you want to iterate over specific stocks, then you can skip this step and write few functions just to iterate over specific stock results. for key, value in dict(matched_string_json).items():īecause json response contains unique stock key symbols and creating a different function for each stock symbol will lead to a lot of code, and if some symbol will be changed in the future, it will throw an error. It will iterate over each available stock from the response instead and will substitute the correct stock key symbol with appropriate value data. items() returns a key, value pair so I don't have to specify which stock symbol to iterate over. Matched_string_json = json.loads(matched_string)Īfter that, the for key, value in dict(.).items() option was used to make the code shorter and easier. Next is to extract the data and convert it to iterable JSON string since re.findall() returns a list, ''.join() making it a string to use json.loads() in the next step. Note: There's obviously a better regex that could be used, I used the easiest, a very basic one. Here's a screenshot to see what is being captured ( link to regular expression): Then, regular expression comes into play to extract JSON string from the tag. Just copied the stock name and pasted it in the source code and checked if there's a match under the tags.Īfter several matches were found in the same place under the tag I began to look where the tag starts and ends in order to extract the correct one using regular expression. The way I found where the data is located is very simple. Here's what UI looks like: Get header stock resultsįirstly, we need to locate where the data is located since we can't just use CSS selectors to extract the data because it is dynamically updating from the server. You can access and navigate through header stock results, news results json string data at jsonblob here.ĭadroit was used to preview json and copy paths to a specific key, value. Secondly, all/most of the existing Yahoo! Finance parsers (at least those that I looked at) extract only ticket(s) data, without news results that Yahoo! Finance has.Firstly, this blog post is more educational rather than a complete solution.The differences between those parsers and the one you'll see below are: ![]() Since Yahoo! Finance deprecated their API there're a lot of custom solutions out there. What will be scraped Difference between existing Yahoo! Finance parsers The provided DIY solution can be used for personal use. This blog post is to show you way how you can do it yourself as we noticed quite a few questions on Stackoverflow about scraping Yahoo! Finance and decided to create a blog about it. Currently, we don't have an API that supports extracting data from the Yahoo! Finance page. ![]()
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