Monitoring your jobs

Monitors

Monitors are the main class where you include your monitoring logic. After defining them, you need to include them in a MonitorSuite, so they can be executed.

As spidermon.core.monitors.Monitor inherits from Python unittest.TestCase, you can use all existing assertion methods in your monitors.

In the following example, we define a monitor that will verify whether a minimum number of items were extracted and fails if it is less than the expected threshold.

from spidermon import Monitor, monitors

@monitors.name('Item count')
class ItemCountMonitor(Monitor):

    @monitors.name('Minimum items extracted')
    def test_minimum_number_of_items_extracted(self):
        minimum_threshold = 100
        item_extracted = getattr(self.data.stats, 'item_scraped_count', 0)
        self.assertFalse(
            item_extracted < minimum_threshold,
            msg='Extracted less than {} items'.format(minimum_threshold)
        )

A Monitor instance has the following properties that can be used to help you implement your monitors:

data.stats dict-like object containing the stats of the spider execution

data.crawler instance of actual Crawler object

data.spider instance of actual Spider object

Monitor Suites

A Monitor Suite groups a set of Monitor classes and allows you to specify which actions must be executed at specified moments of the spider execution.

Here is an example of how to configure a new monitor suite in your project:

# monitors.py
from spidermon.core.suites import MonitorSuite

# Monitor definition above...
class SpiderCloseMonitorSuite(MonitorSuite):
    monitors = [
        # (your monitors)
    ]

    monitors_finished_actions = [
        # actions to execute when suite finishes its execution
    ]

    monitors_failed_actions = [
        # actions to execute when suite finishes its execution with a failed monitor
    ]
# settings.py
SPIDERMON_SPIDER_OPEN_MONITORS = (
    # list of monitor suites to be executed when the spider starts
)

SPIDERMON_SPIDER_CLOSE_MONITORS = (
    # list of monitor suites to be executed when the spider finishes
)
class MonitorSuite(name=None, monitors=None, monitors_finished_actions=None, monitors_passed_actions=None, monitors_failed_actions=None, order=None, crawler=None)

An instance of MonitorSuite defines a set of monitors and actions to be executed after the job finishes its execution.

name suite name

monitors list of Monitor that will be executed if this suite is enabled.

monitors_finished_actions list of action classes that will be executed when all monitors finished their execution.

monitors_passed_actions list of action classes that will be executed if all monitors passed.

monitors_failed_actions list of action classes that will be executed if at least one of the monitors failed.

order if you have more than one suite enabled in your project, this integer defines the order of execution of the suites

crawler crawler instance

on_monitors_finished(result)

Executed right after the monitors finished their execution and before any other action is executed.

result stats of the spider execution

on_monitors_passed(result)

Executed right after the monitors finished their execution but after the actions defined in monitors_finished_actions were executed if all monitors passed.

result stats of the spider execution

on_monitors_failed(result)

Executed right after the monitors finished their execution but after the actions defined in monitors_finished_actions were executed if at least one monitor failed.

result stats of the spider execution

The Basic Monitors

Spidermon has some batteries included :)

class spidermon.contrib.scrapy.monitors.FinishReasonMonitor(methodName='runTest', name=None)

Check if a job has a expected finish reason.

You can configure the expected reason with the SPIDERMON_EXPECTED_FINISH_REASONS, it should be an iterable of valid finish reasons.

The default value of this settings is: ['finished', ].

class spidermon.contrib.scrapy.monitors.ItemCountMonitor(methodName='runTest', name=None)

Check if spider extracted the minimum number of items.

You can configure it using SPIDERMON_MIN_ITEMS setting. There’s NO default value for this setting, if you try to use this monitor without setting it, it’ll raise a NotConfigured exception.

class spidermon.contrib.scrapy.monitors.UnwantedHTTPCodesMonitor(methodName='runTest', name=None)

Check for maximum number of unwanted HTTP codes.

You can configure a dict of unwanted HTTP codes with SPIDERMON_UNWANTED_HTTP_CODES the default value is:

DEFAULT_ERROR_CODES = {
    code: 10
    for code in [400, 407, 429, 500, 502, 503, 504, 523, 540, 541]}

Is there a Basic Scrapy Suite ready to use?

Of course, there is! We really want to make it easy for you to monitor your spiders ;)

class spidermon.contrib.scrapy.monitors.SpiderCloseMonitorSuite(name=None, monitors=None, monitors_finished_actions=None, monitors_passed_actions=None, monitors_failed_actions=None, order=None, crawler=None)

This Monitor Suite implements the following monitors:

You can easily enable this monitor after enabling Spidermon:

SPIDERMON_SPIDER_CLOSE_MONITORS = (
    'spidermon.contrib.scrapy.monitors.SpiderCloseMonitorSuite',
)

Periodic Monitors

Sometimes we don’t want to wait until the end of the spider execution to monitor it. For example, we may want to be notified as soon the number of errors reaches a value or close the spider if the time elapsed is greater than expected.

You define your Monitors and Monitor Suites the same way as before, but you need to provide the time interval (in seconds) between each of the times the Monitor Suites is run.

In the following example, we defined a periodic monitor suite that will be executed every minute and will verify if the number of errors found is lesser than a value. If not, the spider will be closed.

First we define a new action that will close the spider when executed:

# myproject/actions.py
from spidermon.core.actions import Action

class CloseSpiderAction(Action):

    def run_action(self):
        spider = self.data['spider']
        spider.logger.info("Closing spider")
        spider.crawler.engine.close_spider(spider, 'closed_by_spidermon')

Then we create our monitor and monitor suite that verifies the number of errors and then take an action if it fails:

# myproject/monitors.py
from myproject.actions import CloseSpiderAction

@monitors.name('Periodic job stats monitor')
class PeriodicJobStatsMonitor(Monitor, StatsMonitorMixin):

    @monitors.name('Maximum number of errors reached')
    def test_number_of_errors(self):
        accepted_num_errors = 20
        num_errors = self.data.stats.get('log_count/ERROR', 0)

        msg = 'The job has exceeded the maximum number of errors'
        self.assertLessEqual(num_errors, accepted_num_errors, msg=msg)

class PeriodicMonitorSuite(MonitorSuite):
    monitors = [PeriodicJobStatsMonitor]
    monitors_failed_actions = [CloseSpiderAction]

The last step is to configure the suite to be executed every 60 seconds:

# myproject/settings.py

SPIDERMON_PERIODIC_MONITORS = {
    'myproject.monitors.PeriodicMonitorSuite': 60,  # time in seconds
}

What to monitor?

These are some of the usual metrics used in the monitors:

  • the amount of items extracted by the spider.
  • the amount of successful responses received by the spider.
  • the amount of failed responses (server-side errors, network errors, proxy errors, etc.).
  • the amount of requests that reach the maximum amount of retries and are finally discarded.
  • the amount of time it takes to finish the crawl.
  • the amount of errors in the log (spider errors, generic errors detected by Scrapy, etc.)
  • the amount of bans.
  • the job outcome (if it finishes without major issues or if it is closed prematurely because it detects too many bans, for example).
  • the amount of items that don’t contain a specific field or a set of fields
  • the amount of items with validation errors (missing required fields, incorrect format, values that don’t match a specific regular expression, strings that are too long/short, numeric values that are too high/low, etc.)