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Monitoring Scrapy using the Python Agent API

anthonybloomer profile image Anthony Bloomer ・3 min read

Recently I worked on a project to learn more about the Scrapy framework and to demonstrate how a customer can monitor a framework such as Scrapy using the Python Agent API.

Basic Instrumentation using Agent Background Tasks

A trivial example of how a customer can monitor their Scrapy application is to use the background task decorator with the New Relic Python agent API. Consider the following Spider that scrapes content from Quotes to Scrape:

import scrapy


class QuotesSpider(scrapy.Spider):
    name = "quotes"
    start_urls = [
        'http://quotes.toscrape.com/page/1/',
    ]

    def parse(self, response):
        for quote in response.css('div.quote'):
            yield {
                'text': quote.css('span.text::text').get(),
                'author': quote.css('small.author::text').get(),
                'tags': quote.css('div.tags a.tag::text').getall(),
            }

        for a in response.css('li.next a'):
            yield response.follow(a, callback=self.parse)

To add basic instrumentation using the New Relic Python agent, we just need to add three additional lines of code!

import newrelic.agent
newrelic.agent.initialize('newrelic.ini')

import scrapy


class QuotesSpider(scrapy.Spider):
    name = "quotes"
    start_urls = [
        'http://quotes.toscrape.com/page/1/',
    ]

    @newrelic.agent.background_task()
    def parse(self, response):
        for quote in response.css('div.quote'):
            yield {
                'text': quote.css('span.text::text').get(),
                'author': quote.css('small.author::text').get(),
                'tags': quote.css('div.tags a.tag::text').getall(),
            }

        for a in response.css('li.next a'):
            yield response.follow(a, callback=self.parse)

In the example above, the initialize method is used to initialize the agent with the specified newrelic.ini configuration file. The @newrelic.agent.background_task() decorator is used to instrument the parse function as a background task. This transaction is then displayed as a non-web transactions in the APM UI and separated from web transactions.

Advanced Instrumentation using Scrapy Extensions

To go one step further with instrumenting Scrapy applications is to use Scrapy Extensions. The extensions framework built into Scrapy provides a mechanism for inserting your own custom functionality into Scrapy. Extensions are just regular classes that are instantiated at Scrapy startup, when extensions are initialized.

I worked on an extension that collects some statistics and records a New Relic custom event that can be queried using New Relic Insights. Scrapy uses signals to notify when certain events occur. You can catch some of those signals in your Scrapy application using a custom extension to perform tasks or extend Scrapy to add functionality not provided out of the box.

In my custom New Relic extension, I gather some basic statistics when the Spider is opened, closed, scraped, etc. In the closed method, I send the gathered data using the record_custom_event API method.

You can find the custom extension below:

import newrelic.agent

import logging
import datetime

from scrapy import signals
from scrapy.exceptions import NotConfigured

logger = logging.getLogger(__name__)


class NewRelic(object):

    def __init__(self):
        self.event_stats = {}

    @classmethod
    def from_crawler(cls, crawler):
        if not crawler.settings.getbool('MYEXT_ENABLED'):
            raise NotConfigured

        o = cls()
        crawler.signals.connect(o.spider_opened, signal=signals.spider_opened)
        crawler.signals.connect(o.spider_closed, signal=signals.spider_closed)
        crawler.signals.connect(o.item_scraped, signal=signals.item_scraped)
        crawler.signals.connect(o.item_dropped, signal=signals.item_dropped)
        crawler.signals.connect(o.response_received, signal=signals.response_received)
        return o

    def set_value(self, key, value):
        self.event_stats[key] = value

    def spider_opened(self, spider):
        self.set_value('start_time', datetime.datetime.utcnow())

    def spider_closed(self, spider, reason):
        self.set_value('finish_time', datetime.datetime.utcnow())
        application = newrelic.agent.application()
        self.event_stats.update({'spider': spider.name})
        newrelic.agent.record_custom_event("ScrapyEvent", self.event_stats, application)

    def inc_value(self, key, count=1, start=0, spider=None):
        d = self.event_stats
        d[key] = d.setdefault(key, start) + count

    def item_scraped(self, item, spider):
        self.inc_value('item_scraped_count', spider=spider)

    def response_received(self, spider):
        self.inc_value('response_received_count', spider=spider)

    def item_dropped(self, item, spider, exception):
        reason = exception.__class__.__name__
        self.inc_value('item_dropped_count', spider=spider)
        self.inc_value('item_dropped_reasons_count/%s' % reason, spider=spider)

The above example includes only a few of the signal events available. For a full list of signals go to: https://docs.scrapy.org/en/latest/topics/signals.html

Testing the Project

To try this project, follow these steps:

  1. Clone the repo: git clone https://github.com/AnthonyBloomer/nrscrapy.git
  2. Install the requirements. Run pip install -r requirements.txt
  3. Update newrelic.ini with your license key or export your license key as an environment variable.
  4. Run cd tutorial
  5. Run scrapy crawl quotes

Please note that the information presented here is done so as is without warranty or support. Scrapy is an unsupported framework, therefore New Relic Technical Support cannot offer assistance with this.

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