A basic framework to scrap renting ads
This package provides an easy and maintenable way to build a Rentswatch scraper. Rentswatch is a cross-borders investigation that collects data on flat rents in Europe. Its scrapers mainly focus on classified ads.
How to install
Install using pip…
pip install rentswatch-scraper
How to use
Let’s take a look at a quick example of using Rentswatch Scraper to build a simple model-backed scraper to collect data from a website.
First, import the package components to build your scraper:
#!/usr/bin/env python from rentswatch_scraper.scraper import Scraper from rentswatch_scraper.browser import geocode, convert from rentswatch_scraper.fields import RegexField, ComputedField from rentswatch_scraper import reporting
To factorize as much code as possible we created an abstract class that every scraper will implement. For the sake of simplicity we’ll use a dummy website as follow:
class DummyScraper(Scraper): # Those are the basic meta-properties that define the scraper behavior class Meta: country = 'FR' site = "dummy" baseUrl = 'http://dummy.io' listUrl = baseUrl + '/rent/city/paris/list.php' adBlockSelector = '.ad-page-link'
Without any further configuration, this scraper will start to collect ads from the list page of dummy.io. To find links to the ads, it will use the CSS selector .ad-page-link to get <a> markups and follow their href attributes.
We have now to teach the scraper how to extract key figures from the ad page.
class DummyScraper(Scraper): # HEADS UP: Meta declarations are hidden here # ... # ... # Extract data using a CSS Selector. realtorName = RegexField('.realtor-title') # Extract data using a CSS Selector and a Regex. serviceCharge = RegexField('.description-list', 'charges : (.*)\s€') # Extract data using a CSS Selector and a Regex. # This will throw a custom exception if the field is missing. livingSpace = RegexField('.description-list', 'surface :(\d*)', required=True, exception=reporting.SpaceMissingError) # Extract the value directly, without using a Regex totalRent = RegexField('.description-price', required=True, exception=reporting.RentMissingError) # Store this value as a private property (begining with a underscore). # It won't be saved in the database but it can be helpful as you we'll see. _address = RegexField('.description-address')
Every attribute will be saved as an Ad’s property, according to the Ad model.
Some properties may not be extractable from the HTML. You may need to use a custom function that received existing properties. For this reason we created a second field type named ComputedField. Since the properties order of declaration is recorded, we can use previously declared (and extracted) values to compute new ones.
class DummyScraper(Scraper): # ... # ... # Use existing properties `totalRent` and `livingSpace` as they were # extracted before this one. pricePerSqm = ComputedField(fn=lambda s, values: values["totalRent"] / values["livingSpace"]) # This full exemple uses private properties to find latitude and longitude. # To do so we use a buid-in function named `convert` that transforms an # address into a dictionary of coordinates. _latLng = ComputedField(fn=lambda s, values: geocode(values['_address'], 'FRA') ) # Gets a the dictionary field we want. latitude = ComputedField(fn=lambda s, values: values['_latLng']['lat']) longitude = ComputedField(fn=lambda s, values: values['_latLng']['lng'])
All you need to do now is to create an instance of your class and run the scraper.
# When you script is executed directly if __name__ == "__main__": dummyScraper = DummyScraper() dummyScraper.run()
As seen above, every Ad attribute might be used as a Scraper attribute to declare which attribute extract.
|status||String||“listed” if needs more scraping, “scraped” if it’s done|
|site||String||Name of the website|
|createdAt||DateTime||Date the ad was first scraped|
|siteId||String||The unique ID from the site where it’s scrapped from|
|serviceCharge||Float||Extra costs (heating mostly)|
|baseRent||Float||Base costs (without heating)|
|livingSpace||Float||Surface in square meters|
|pricePerSqm||Float||Price per square meter|
|furnished||Bool||True if the flat or house is furnished|
|realtor||Bool||True if realtor, n if rented by a physical person|
|realtorName||Unicode||The name of the realtor or person offering the flat|
|balcony||Bool||True if there is a balcony/terrasse|
|yearConstructed||String||The year the building was built|
|cellar||Bool||True if the flat comes with a cellar|
|parking||Bool||True if the flat comes with a parking or a garage|
|houseNumber||String||House Number in the street|
|street||String||Street name (incl. “street”)|
|lift||Bool||True if a lift is present|
|typeOfFlat||String||Type of flat (no typology)|
|noRooms||String||Number of rooms|
|floor||String||Floor the flat is at|
|garden||Bool||True if there is a garden|
|barrierFree||Bool||True if the flat is wheelchair accessible|
|country||String||Country, 2 letter code|
|sourceUrl||String||URL of the page|
The Scraper class defines a lot of method that we encourage you to redefine in order to have the full control of your scraper behavior.
|extract_ad||Extract ads list from a page’s soup.|
|fail||Print out an error message.|
|fetch_ad||Fetch a single ad page from the target website then create Ad instances by calling èxtract_ad.|
|fetch_series||Fetch a single list page from the target website then fetch an ad by calling fetch_ad.|
|find_ad_blocks||Extract ad block from a page list. Called within fetch_series.|
|get_ad_href||Extract a href attribute from an ad block. Called within fetch_series.|
|get_ad_id||Extract a siteId from an ad block. Called within fetch_series.|
|get_fields||Used internally to generate a list of property to extract from the ad.|
|get_series||Fetch a list page from the target website.|
|has_issue||True if we met issues with this ad before.|
|is_scraped||True if we already scraped this ad before.|
|ok||Print out an success message.|
|prepare||Just before saving the values.|
|run||Run the scrapper.|
|transform_page||Transform HTML content of the series page before parsing it.|
Start a migration
yoyo new ./migrations -m "Your migration's description"
And apply it:
yoyo apply --database mysql://user:password@host/db ./migrations
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