Scrapy’s documentation does a pretty bad job at giving examples on real applications of both. CrawlerProcess assumes that scrapy is the only thing that is going to use twisted’s reactor. If you are using threads in python to run other code this isn’t always true. Let’s take this as an example. from scrapy.crawler import CrawlerProcess … Read more
You could also use findAll to get all the rows in a list and after that just use the slice syntax to access the elements that you need: rows = soup.findAll(‘tr’)[4::5]
demjson.decode() import demjson # from js_obj = ‘{x:1, y:2, z:3}’ # to py_obj = demjson.decode(js_obj) chompjs.parse_js_object() import chompjs # from js_obj = ‘{x:1, y:2, z:3}’ # to py_obj = chompjs.parse_js_object(js_obj) jsonnet.evaluate_snippet() import json, _jsonnet # from js_obj = ‘{x:1, y:2, z:3}’ # to py_obj = json.loads(_jsonnet.evaluate_snippet(‘snippet’, js_obj)) ast.literal_eval() import ast # from js_obj = “{‘x’:1, … Read more
Note that you can also use regular expressions to search in attributes of tags. For example: import re from bs4 import BeautifulSoup soup.find_all(‘a’, {‘href’: re.compile(r’crummy\.com/’)}) This example finds all <a> tags that link to a website containing the substring ‘crummy.com’.
The link you included in your question is simply a wrapper that executes urllib’s read() function, which catches any incomplete read exceptions for you. If you don’t want to implement this entire patch, you could always just throw in a try/catch loop where you read your links. For example: try: page = urllib2.urlopen(urls).read() except httplib.IncompleteRead, … Read more
[:] is the array slice syntax for every element in the array. This answer here goes more in depth of the general uses: How slicing in Python works del arr # Deletes the array itself del arr[:] # Deletes all the elements in the array del arr[2] # Deletes the third element in the array … Read more
For anyone else experiencing this issue when running selenium webdriver in a Docker container, increasing the container size to 2gb fixes this issue. I guess this affects physical machines too if the OP fixed their issue by upgrading their server RAM to 2Gb, but could be coincidence.
This is not the specific code you need, just a demo of how to work with BeautifulSoup. It finds the table who’s id is “Table1” and gets all of its tr elements. html = urllib2.urlopen(url).read() bs = BeautifulSoup(html) table = bs.find(lambda tag: tag.name==’table’ and tag.has_attr(‘id’) and tag[‘id’]==”Table1″) rows = table.findAll(lambda tag: tag.name==’tr’)
First there is a plethora of HTML scraping libs in JVM all you need to do is pimp one of them (pimp my library pattern). The four I have used are: HtmlUnit – Will emulate the browser and even run Javascript Jericho – Preserves formatting and ideal if you want to edit the scraped HTML … Read more
In BeautifulSoup 4, the class attribute (and several other attributes, such as accesskey and the headers attribute on table cell elements) is treated as a set; you match against individual elements listed in the attribute. This follows the HTML standard. As such, you cannot limit the search to just one class. You’ll have to use … Read more