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A library that enables programmatic interaction with daft.ie.

Project description

A library that enables programmatic interaction with daft.ie allowing you to retrieve properties by location, sale type, price and property type. daftlistings has been tested on Python 2.7 and Python 3.5.2

Install

daftlistings is available on the Python Package Index (PyPI) at https://pypi.python.org/pypi/daftlistings

You can install daftlistings using pip.

pip install daftlistings

Development Version

This library is under active development. Before new versions are pushed to PyPI, you can download the development version to avail of any new features.

git clone https://github.com/AnthonyBloomer/daftlistings.git
cd daftlistings
virtualenv env
source env/bin/activate
pip install -r requirements.txt

Examples

Get the current properties for rent in Dublin that are between €1000 and €1500 per month and contact the advertiser for each listing.

from daftlistings import Daft, CommercialType, SaleType, RentType

daft = Daft()
daft.set_county('Dublin City')
daft.set_area('Dublin 15')
daft.set_listing_type(RentType.APARTMENTS)
daft.set_min_price(1000)
daft.set_max_price(1500)

listings = daft.get_listings()

for listing in listings:
    print(listing.get_formalised_address())
    print(listing.get_daft_link())

    contact = listing.contact_advertiser(
        name="Jane Doe",
        contact_number="019202222",
        email="jane@example.com",
        message="Hi, I seen your listing on daft.ie and I would like to schedule a viewing."
    )

    if contact:
        print("Message sent")

Retrieve commercial office listings in Dublin.

daft.set_county("Dublin")
daft.set_listing_type(SaleType.COMMERCIAL)
daft.set_commercial_property_type(CommercialType.OFFICE)

listings = daft.get_listings()

for listing in listings:
    print(listing.get_formalised_address())
    print(listing.get_daft_link())

Get the current sale agreed prices for properties in Dublin.

daft.set_county('Dublin City')
daft.set_area('Dublin 15')
daft.set_listing_type(SaleType.PROPERTIES)
daft.set_min_price(1000)
daft.set_max_price(1500)
daft.set_sale_agreed(True)

listings = daft.get_listings()

for listing in listings:
    print(listing.get_formalised_address())
    print(listing.get_daft_link())

You can sort the listings by price, distance, upcoming viewing or date using the SortType object. The SortOrder object allows you to sort the listings descending or ascending. For example:

from daftlistings import SortOrder, SortType

daft.set_county('Dublin City')
daft.set_area('Dublin 15')
daft.set_listing_type(SaleType.PROPERTIES)
daft.set_min_price(150000)
daft.set_max_price(175000)
daft.set_sort_order(SortOrder.ASCENDING)
daft.set_sort_by(SortType.PRICE)


listings = daft.get_listings()

for listing in listings:
    print(listing.get_formalised_address())
    print(listing.get_daft_link())
    print(listing.get_price())

Retrieve all properties for sale in Dublin 15. This example loops through each page of listings and prints the result.

offset = 0
pages = True

while pages:

    daft.set_county('Dublin City')
    daft.set_area('Dublin 15')
    daft.set_listing_type(SaleType.PROPERTIES)
    daft.set_offset(offset)

    listings = daft.get_listings()

    if not listings:
        pages = False

    for listing in listings:
        print(listing.get_agent_url())
        print(listing.get_price())
        print(listing.get_formalised_address())
        print(listing.get_daft_link())
        print(' ')


    offset += 10

Documentation

The current documentation can be viewed here: https://anthonybloomer.github.io/daftlistings/

The documentation has been created using mkdocs.

To update the documentation, clone the repository and edit docs/index.md

To view your changes, run:

mkdocs serve

To build the documentation, run:

mkdocs build

This will create a directory called site. Copy the site directory to a new directory and checkout gh-pages

git checkout gh-pages

Copy any changes from the site directory to this directory and push your changes.

Contributing

Contribute to daftlistings by suggesting new features or providing feedback / criticism. Pull requests are always welcome too so feel free to hack away.

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