Signals¶
Scrapy uses signals extensively to notify when certain events occur. You can catch some of those signals in your Scrapy project (using an extension, for example) to perform additional tasks or extend Scrapy to add functionality not provided out of the box.
Even though signals provide several arguments, the handlers that catch them don’t need to accept all of them - the signal dispatching mechanism will only deliver the arguments that the handler receives.
You can connect to signals (or send your own) through the Signals API.
Here is a simple example showing how you can catch signals and perform some action:
from scrapy import signals
from scrapy import Spider
class DmozSpider(Spider):
name = "dmoz"
allowed_domains = ["dmoz.org"]
start_urls = [
"http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
"http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/",
]
@classmethod
def from_crawler(cls, crawler, *args, **kwargs):
spider = super(DmozSpider, cls).from_crawler(crawler, *args, **kwargs)
crawler.signals.connect(spider.spider_closed, signal=signals.spider_closed)
return spider
def spider_closed(self, spider):
spider.logger.info('Spider closed: %s', spider.name)
def parse(self, response):
pass
Deferred signal handlers¶
Some signals support returning Twisted deferreds from their handlers, see the Built-in signals reference below to know which ones.
Built-in signals reference¶
Here’s the list of Scrapy built-in signals and their meaning.
engine_started¶
-
scrapy.signals.
engine_started
()¶ Sent when the Scrapy engine has started crawling.
This signal supports returning deferreds from their handlers.
Note
This signal may be fired after the spider_opened
signal,
depending on how the spider was started. So don’t rely on this signal
getting fired before spider_opened
.
engine_stopped¶
-
scrapy.signals.
engine_stopped
()¶ Sent when the Scrapy engine is stopped (for example, when a crawling process has finished).
This signal supports returning deferreds from their handlers.
item_scraped¶
-
scrapy.signals.
item_scraped
(item, response, spider)¶ Sent when an item has been scraped, after it has passed all the Item Pipeline stages (without being dropped).
This signal supports returning deferreds from their handlers.
Parameters:
item_dropped¶
-
scrapy.signals.
item_dropped
(item, response, exception, spider)¶ Sent after an item has been dropped from the Item Pipeline when some stage raised a
DropItem
exception.This signal supports returning deferreds from their handlers.
Parameters: - item (dict or
Item
object) – the item dropped from the Item Pipeline - spider (
Spider
object) – the spider which scraped the item - response (
Response
object) – the response from where the item was dropped - exception (
DropItem
exception) – the exception (which must be aDropItem
subclass) which caused the item to be dropped
- item (dict or
item_error¶
-
scrapy.signals.
item_error
(item, response, spider, failure)¶ Sent when a Item Pipeline generates an error (ie. raises an exception), except
DropItem
exception.This signal supports returning deferreds from their handlers.
Parameters:
spider_closed¶
-
scrapy.signals.
spider_closed
(spider, reason)¶ Sent after a spider has been closed. This can be used to release per-spider resources reserved on
spider_opened
.This signal supports returning deferreds from their handlers.
Parameters: - spider (
Spider
object) – the spider which has been closed - reason (str) – a string which describes the reason why the spider was closed. If
it was closed because the spider has completed scraping, the reason
is
'finished'
. Otherwise, if the spider was manually closed by calling theclose_spider
engine method, then the reason is the one passed in thereason
argument of that method (which defaults to'cancelled'
). If the engine was shutdown (for example, by hitting Ctrl-C to stop it) the reason will be'shutdown'
.
- spider (
spider_opened¶
-
scrapy.signals.
spider_opened
(spider)¶ Sent after a spider has been opened for crawling. This is typically used to reserve per-spider resources, but can be used for any task that needs to be performed when a spider is opened.
This signal supports returning deferreds from their handlers.
Parameters: spider ( Spider
object) – the spider which has been opened
spider_idle¶
-
scrapy.signals.
spider_idle
(spider)¶ Sent when a spider has gone idle, which means the spider has no further:
- requests waiting to be downloaded
- requests scheduled
- items being processed in the item pipeline
If the idle state persists after all handlers of this signal have finished, the engine starts closing the spider. After the spider has finished closing, the
spider_closed
signal is sent.You may raise a
DontCloseSpider
exception to prevent the spider from being closed.This signal does not support returning deferreds from their handlers.
Parameters: spider ( Spider
object) – the spider which has gone idle
Note
Scheduling some requests in your spider_idle
handler does
not guarantee that it can prevent the spider from being closed,
although it sometimes can. That’s because the spider may still remain idle
if all the scheduled requests are rejected by the scheduler (e.g. filtered
due to duplication).
spider_error¶
-
scrapy.signals.
spider_error
(failure, response, spider)¶ Sent when a spider callback generates an error (ie. raises an exception).
This signal does not support returning deferreds from their handlers.
Parameters:


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Simply add the bs-generate
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Or embed by copy and pasting the following default code directly into the HTML where you would like the button to appear for it to be automatically generated
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Simply add the bs-donate
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module activated
Optional Inegrated Dynamic Labels:
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(click button to open accounts window)
Simply add the bs-accounts
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Or embed by copy and pasting the following default code directly into the HTML where you would like the button to appear for it to be automatically generated
<script src="/blockstrap/js/widget.js" data-type="btn-accounts_modal" data-salt="ADD_SALT_HERE" ></script>
UPDATING API CONFIGURATION AND SWITCHING WIDGET OPTIONS select from the nine available API providers below and add an API key if, when or where required
default_api
and default_key
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Projects Completed
{% for job in jobs.all %}
{% endfor %}
{{ job.description }}
WHO I AM
{{ hom.statement }}
GET IN TOUCH
AkinkunleGroup, Inc.{{ hom.address }},
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P: (+234)<PHONE_NUMBER>


Not connecting parts of a UI that relate to one another is a leading cause of stress accessibility issues
In this case, there's an implicit relation between the tab list and its associated tabs
<tab selected>Tab 1</tab>
Tab 2
Behind the scenes, we may want to automatically set the aria-activedescendant
attribute
It could look like the following in Vue.js using some utility mixins
const tabs = relation({ explicit: false })
const TabList = {
mixins: [hasMany(tabs, "tabs")],
computed: {
activeDescendant() {
return this.tabs.find(tab => tab.selected)
}
}
}
const Tab = {
mixins: [memberOf(tabs)]
}
In this case, there's an explicit relation between the button and the content it collapses
...
Behind the scenes, we may want to automatically set the aria-controls
attribute

...

Again, it could look like the following in Vue.js using some utility mixins
const collapse = relation({ explicit: true })
const Collapse = {
mixins: [hasOne(collapse)],
}
const Button = {
mixins: [memberOf(collapse, "collapse")],
computed: {
controls() {
return this.collapse.id
}
}
}
Another common pitfall: When to use
and when to use <button>
?
Find the "right" question to ask!
What kind of interaction do you want?
If you don't want interaction, this...
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If you want interaction and have a link, this...
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If you want interaction and have a click handler, this...
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It could look like the following in Vue.js as a component template


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giddy.ergodic.fmpt¶
-
giddy.ergodic.
fmpt
(P, fill_empty_classes=False)[source]¶ Generalized function for calculating first mean passage times for an ergodic or non-ergodic transition probability matrix.
- Parameters
- Parray
(k, k), an ergodic/non-ergodic Markov transition probability matrix.
- fill_empty_classes: bool, optional
If True, assign 1 to diagonal elements which fall in rows full of 0s to ensure the transition probability matrix is a stochastic one. Default is False.
- Returns
- fmpt_allarray
(k, k), elements are the expected value for the number of intervals required for a chain starting in state i to first enter state j. If i=j then this is the recurrence time.
Examples
>>> import numpy as np >>> from giddy.ergodic import fmpt >>> np.set_printoptions(suppress=True) #prevent scientific format
Irreducible Markov chain >>> p = np.array([[.5, .25, .25],[.5,0,.5],[.25,.25,.5]]) >>> fm = fmpt(p) >>> fm array([[2.5 , 4. , 3.33333333],
[2.66666667, 5. , 2.66666667], [3.33333333, 4. , 2.5 ]])
Thus, if it is raining today in Oz we can expect a nice day to come along in another 4 days, on average, and snow to hit in 3.33 days. We can expect another rainy day in 2.5 days. If it is nice today in Oz, we would experience a change in the weather (either rain or snow) in 2.67 days from today.
Reducible Markov chain: two communicating classes (this is an artificial example) >>> p = np.array([[.5, .5, 0],[.2,0.8,0],[0,0,1]]) >>> fmpt(p) array([[3.5, 2. , inf],
[5. , 1.4, inf], [inf, inf, 1. ]])
Thus, if it is raining today in Oz we can expect a nice day to come along in another 2 days, on average, and should not expect snow to hit. We can expect another rainy day in 3.5 days. If it is nice today in Oz, we should expect a rainy day in 5 days.
>>> p = np.array([[.5, .5, 0],[.2,0.8,0],[0,0,0]]) >>> fmpt(p, fill_empty_classes=True) array([[3.5, 2. , inf], [5. , 1.4, inf], [inf, inf, 1. ]])
>>> p = np.array([[.5, .5, 0],[.2,0.8,0],[0,0,0]]) >>> fmpt(p, fill_empty_classes=False) Traceback (most recent call last): ... ValueError: Input transition probability matrix has 1 rows full of 0s. Please set fill_empty_classes=True to set diagonal elements for these rows to be 1 to make sure the matrix is stochastic.


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