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Exceptions silently swollen when using CralwerRunner of Scrapy

I am trying to use CrawlerRunner to run a spider using Scrapy as follows:
a_crawler = CrawlerRunner(settings)
#defer.inlineCallbacks
def crawl():
CodeThatGenerateException()
print("Starting crawler")
yield a_crawler.crawl(MySpider)
reactor.stop()
crawl()
reactor.run()
Strangely the Exception generated by the first line of the crawl function is not printed, nothing happens and the application hangs and does not stop
I cannot figure out what is going on
Any suggestion is welcomed

How to make Scrapy general purpose?

I am using Scrapy for scraping text from websites.
I would like Scrapy to scrape text from various URLs with different structure, without having to change the code for each website.
The following example works in my Jupyter Notebook for the given URL ( http://quotes.toscrape.com/tag/humor/ ). But it does not work for another (for ex.: https://en.wikipedia.org/wiki/Web_scraping ).
My question is, how to make it work for (most) other websites without manually inspecting every site and changing the code all the time? I guess I need to make a change under def parse(self, response), but so far I could not find a good example how to do that.
Modules:
import scrapy
import scrapy.crawler as crawler
from multiprocessing import Process, Queue
from twisted.internet import reactor
Spider:
class QuotesSpider(scrapy.Spider):
name = "quotes"
start_urls = ['http://quotes.toscrape.com/tag/humor/']
def parse(self, response):
for quote in response.css('div.quote'):
print(quote.css('span.text::text').extract_first())
A wrapper to make it run more times in Jupyter:
def run_spider(spider):
def f(q):
try:
runner = crawler.CrawlerRunner()
deferred = runner.crawl(spider)
deferred.addBoth(lambda _: reactor.stop())
reactor.run()
q.put(None)
except Exception as e:
q.put(e)
q = Queue()
p = Process(target=f, args=(q,))
p.start()
result = q.get()
p.join()
if result is not None:
raise result
Get the result:
print('Extracted text:')
run_spider(QuotesSpider)
Extracted text:
“The person, be it gentleman or lady, who has not pleasure in a good novel, ..."

Broad crawling - different xpaths - Scrapy

I'm new in Scrapy. I have thousands of url,xpath tuples and values in a database.
These urls are from different domains (not allways, there can be 100 urls from the same domain).
x.com/a //h1
y.com/a //div[#class='1']
z.com/a //div[#href='...']
x.com/b //h1
x.com/c //h1
...
Now I want to get these values every 2 hours as fast as possible but to be sure that I don't overload any of these.
Can't figure out how to do that.
My thoughts:
I could create one Spider for every different domain, set it's parsing rules and run them at once.
Is it a good practice?
EDIT:
I'm not sure how it would work with outputting data into database according to concurrency.
EDIT2:
I can do something like this - for every domain there is a new spider. But this is impossible to do having thousands of different urls and it's xpaths.
class WikiScraper(scrapy.Spider):
name = "wiki_headers"
def start_requests(self):
urls = [
'https://en.wikipedia.org/wiki/Spider',
'https://en.wikipedia.org/wiki/Data_scraping',
]
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
hxs = HtmlXPathSelector(response)
header = hxs.select('//h1/text()').extract()
print header
filename = 'result.txt'
with open(filename, 'a') as f:
f.write(header[0])
self.log('Saved file %s' % filename)
class CraigslistScraper(scrapy.Spider):
name = "craigslist_headers"
def start_requests(self):
urls = [
'https://columbusga.craigslist.org/act/6062657418.html',
'https://columbusga.craigslist.org/acc/6060297390.html',
]
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
hxs = HtmlXPathSelector(response)
header = hxs.select('//span[#id="titletextonly"]/text()').extract()
filename = 'result.txt'
with open(filename, 'a') as f:
f.write(header[0])
self.log('Saved file %s' % filename)

From the example you posted in edit2, it looks like all your classes are easily abstractable by one more level. How about this:?
from urllib.parse import urlparse
class GenericScraper(scrapy.Spider):
def __init__(self, urls, xpath):
super().__init__()
self.name = self._create_scraper_name_from_url(urls[0])
self.urls = urls
self.xpath = xpath
def _create_scraper_name_from_url(url):
'''Generate scraper name from url
www.example.com/foobar/bar -> www_example_com'''
netloc = urlparse(url).netloc
return netloc.replace('.','_')
def start_requests(self):
for url in self.urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
hxs = HtmlXPathSelector(response)
header = hxs.select(self.xpath).extract()
filename = 'result.txt'
with open(filename, 'a') as f:
f.write(header[0])
self.log('Saved file %s' % filename)
Next, you could group the data from database by xpaths
for urls, xpath in grouped_data:
scraper = GenericScraper(urls, xpath)
# do whatever you need with scraper
AD concurency: your database should handle concurent writes so I do not see a problem there
Edit:
Related to the timeouts: I Do not know how scrapy works under the hood i.e. if it uses some sort of paralelization and whether it runs asynchronously in the background. But from what you wrote I guess it does and when you fire up 1k scrapers each firing multiple requests at time your hardware cant handle that much traffic (disclaimer, this is just a guess!).
There might be a native way to do this, but a possible workaround is to use multiprocessing + Queue:
from multiprocessing import JoinableQueue, Process
NUMBER_OF_CPU = 4 # change this to your number.
SENTINEL = None
class Worker(Process):
def __init__(self, queue):
super().__init__()
self.queue = queue
def run(self):
# blocking wait !You have to use sentinels if you use blocking waits!
item = self.queue.get():
if item is SENTINEL:
# we got sentinel, there are no more scrapers to process
self.queue.task_done()
return
else:
# item is scraper, run it
item.run_spider() # or however you run your scrapers
# This assumes that each scraper is **not** running in background!
# Tell the JoinableQueue we have processed one more item
# In the main thread the queue.join() waits untill for
# each item taken from queue a queue.task_done() is called
self.queue.task_done()
def run():
queue = JoinableQueue()
# if putting that many things in the queue gets slow (I imagine
# it can) You can fire up a separate Thread/Process to fill the
# queue in the background while workers are already consuming it.
for urls, xpath in grouped_data:
scraper = GenericScraper(urls, xpath)
queue.put(scraper)
for sentinel in range(NUMBER_OF_CPU):
# None or sentinel of your choice to tell the workers there are
# no more scrapers to process
queue.put(SENTINEL)
workers = []
for _ in range(NUMBER_OF_CPU):
worker = Worker(queue)
workers.append(worker)
worker.start()
# We have to wait until the queue is processed
queue.join()
But please bear in mind that this is a vanilla approach for paralell execution completely ignoring Scrapy abilities. I have found This blogpost which uses twisted to achieve (what I think is) the same thing. But since I've never used twisted I can't comment on that

if you are thinking about scrapy can't handle multiple domains at once because of the allowed_domains parameters, remember that it is optional.
If no allowed_domains parameter is set in the spider, it can work with every domain it gets.

If I understand correctly you have map of domain to xpath values and you want to pull xpath depending on what domain you crawl?
Try something like:
DOMAIN_DATA = [('domain.com', '//div')]
def get_domain(url):
for domain, xpath in DOMAIN_DATA:
if domain in url:
return xp
def parse(self, response):
xpath = get_domain(response.url)
if not xpath:
logging.error('no xpath for url: {}; unknown domain'.format(response.url))
return
item = dict()
item['some_field'] = repsonse.xpath(xpath).extract()
yield item

Calling Scrapy from another file without threading

I have to call the crawler from another python file, for which I use the following code.
def crawl_koovs():
spider = SomeSpider()
settings = get_project_settings()
crawler = Crawler(settings)
crawler.signals.connect(reactor.stop, signal=signals.spider_closed)
crawler.configure()
crawler.crawl(spider)
crawler.start()
log.start()
reactor.run()
On running this, I get the error as
exceptions.ValueError: signal only works in main thread
The only workaround I could find is to use
reactor.run(installSignalHandlers=False)
which I don't want to use as I want to call this method multiple times and want reactor to be stopped before the next call. What can I do to make this work (maybe force the crawler to start in the same 'main' thread)?

The first thing I would say to you is when you're executing Scrapy from external file the loglevel is set to INFO,you should change it to DEBUG to see what's happening if your code doesn't work
you should change the line:
log.start()
for:
log.start(loglevel=log.DEBUG)
To store everything in the log and generate a text file (for debugging purposes) you can do:
log.start(logfile="file.log", loglevel=log.DEBUG, crawler=crawler, logstdout=False)
About the signals issue with the log level changed to DEBUG maybe you can see some output that can help you to fix it, you can try to put your script into the Scrapy Project folder to see if still crashes.
If you change the line:
crawler.signals.connect(reactor.stop, signal=signals.spider_closed)
for:
dispatcher.connect(reactor.stop, signals.spider_closed)
What does it say ?
Depending on your Scrapy version it may be deprecated

for looping and use un azure functions with timertrigger use this taks
from twisted.internet import task from twisted.internet import reactor
loopTimes = 3 failInTheEnd = False
_loopCounter = 0
def runEverySecond():
"""
Called at ever loop interval.
"""
global _loopCounter
if _loopCounter < loopTimes:
_loopCounter += 1
print('A new second has passed.')
return
if failInTheEnd:
raise Exception('Failure during loop execution.')
# We looped enough times.
loop.stop()
return
def cbLoopDone(result):
"""
Called when loop was stopped with success.
"""
print("Loop done.")
reactor.stop()
def ebLoopFailed(failure):
"""
Called when loop execution failed.
"""
print(failure.getBriefTraceback())
reactor.stop()
loop = task.LoopingCall(runEverySecond)
# Start looping every 1 second. loopDeferred = loop.start(1.0)
# Add callbacks for stop and failure. loopDeferred.addCallback(cbLoopDone) loopDeferred.addErrback(ebLoopFailed)
reactor.run()
If we want a task to run every X seconds repeatedly, we can use twisted.internet.task.LoopingCall:
from https://docs.twisted.org/en/stable/core/howto/time.html

Running Scrapy tasks in Python

My Scrapy script seems to work just fine when I run it in 'one off' scenarios from the command line, but if I try running the code twice in the same python session I get this error:
"ReactorNotRestartable"
Why?
The offending code (last line throws the error):
crawler = CrawlerProcess(settings)
crawler.install()
crawler.configure()
# schedule spider
#crawler.crawl(MySpider())
spider = MySpider()
crawler.queue.append_spider(spider)
# start engine scrapy/twisted
crawler.start()

Close to Joël's answer, but I want to elaborate a bit more than is possible in the comments. If you look at the Crawler source code, you see that the CrawlerProcess class has a start, but also a stop function. This stop function takes care of cleaning up the internals of the crawling so that the system ends up in a state from which it can start again.
So, if you want to restart the crawling without leaving your process, call crawler.stop() at the appropriate time. Later on, simply call crawler.start() again to resume operations.
Edit: in retrospect, this is not possible (due to the Twisted reactor, as mentioned in a different answer); the stop just takes care of a clean termination. Looking back at my code, I happened to have a wrapper for the Crawler processes. Below you can find some (redacted) code to make it work using Python's multiprocessing module. In this way you can more easily restart crawlers. (Note: I found the code online last month, but I didn't include the source... so if someone knows where it came from, I'll update the credits for the source.)
from scrapy import project, signals
from scrapy.conf import settings
from scrapy.crawler import CrawlerProcess
from scrapy.xlib.pydispatch import dispatcher
from multiprocessing.queues import Queue
from multiprocessing import Process
class CrawlerWorker(Process):
def __init__(self, spider, results):
Process.__init__(self)
self.results = results
self.crawler = CrawlerProcess(settings)
if not hasattr(project, 'crawler'):
self.crawler.install()
self.crawler.configure()
self.items = []
self.spider = spider
dispatcher.connect(self._item_passed, signals.item_passed)
def _item_passed(self, item):
self.items.append(item)
def run(self):
self.crawler.crawl(self.spider)
self.crawler.start()
self.crawler.stop()
self.results.put(self.items)
# The part below can be called as often as you want
results = Queue()
crawler = CrawlerWorker(MySpider(myArgs), results)
crawler.start()
for item in results.get():
pass # Do something with item

crawler.start() starts Twisted reactor. There can be only one reactor.
If you want to run more spiders - use
another_spider = MyAnotherSpider()
crawler.queue.append_spider(another_spider)

I've used threads to start reactor several time in one app and avoid ReactorNotRestartable error.
Thread(target=process.start).start()
Here is the detailed explanation: Run a Scrapy spider in a Celery Task

Seems to me that you cannot use crawler.start() command twice: you may have to re-create it if you want it to run a second time.