Metadata-Version: 1.1
Name: daftlistings
Version: 1.6.1
Summary: A library that enables programmatic interaction with daft.ie. 
Home-page: https://github.com/AnthonyBloomer/daftlistings
Author: Anthony Bloomer
Author-email: ant0@protonmail.ch
License: MIT
Description: # Daftlistings
        
        Python library that enables Programmatic interaction with [Daft.ie](https://daft.ie)
        
        ## Installation
        
        daftlistings is available on the Python Package Index (PyPI). You can install daftlistings using pip.
        
        ``` bash
        virtualenv env
        source env/bin/activate
        pip install daftlistings
        ```
        
        To install the development version, run:
        
        ``` bash
        pip install https://github.com/AnthonyBloomer/daftlistings/archive/dev.zip
        ```
        
        ## Examples
        
        Get apartments to let in Dublin City that are between €1000 and €1500 and contact the advertiser of each listing.
        
        ``` python
        from daftlistings import Daft, RentType
        
        daft = Daft()
        
        daft.set_county("Dublin City")
        daft.set_listing_type(RentType.APARTMENTS)
        daft.set_min_price(1000)
        daft.set_max_price(1500)
        
        listings = daft.search()
        
        if len(listings) > 0:
            first = listings[0]
        
            contact = first.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("Advertiser contacted")
        ```
        
        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.
        
        ``` python
        
        from daftlistings import Daft, SortOrder, SortType, RentType
        
        daft = Daft()
        
        daft.set_county("Dublin City")
        daft.set_listing_type(RentType.ANY)
        daft.set_sort_order(SortOrder.ASCENDING)
        daft.set_sort_by(SortType.PRICE)
        daft.set_max_price(2500)
        
        listings = daft.search()
        
        for listing in listings:
            print(listing.formalised_address)
            print(listing.daft_link)
            print(listing.price)
            features = listing.features
            if features is not None:
                print('Features: ')
                for feature in features:
                    print(feature)
            print("")
        
        ```
        
        Parse listing data from a given search result url.
        
        ``` python
        
        from daftlistings import Daft
        
        offset = 0
        
        while 1:
            daft = Daft()
            daft.set_result_url("https://www.daft.ie/dublin-city/new-homes-for-sale/?ad_type=new_development")
            daft.set_offset(offset)
            listings = daft.search()
            if not listings:
                break
            for listing in listings:
                print(listing.formalised_address)
                print(listing.price)
                print(' ')
            offset += 10
        
        ```
        
        Find student accommodation near UCD that is between 850 and 1000 per month
        
        ``` python
        from daftlistings import Daft, SortOrder, SortType, RentType, University, StudentAccommodationType
        
        daft = Daft()
        daft.set_listing_type(RentType.STUDENT_ACCOMMODATION)
        daft.set_university(University.UCD)
        daft.set_student_accommodation_type(StudentAccommodationType.ROOMS_TO_SHARE)
        daft.set_min_price(850)
        daft.set_max_price(1000)
        daft.set_sort_by(SortType.PRICE)
        daft.set_sort_order(SortOrder.ASCENDING)
        daft.set_offset(offset)
        listings = daft.search()
        
        for listing in listings:
            print(listing.price)
            print(listing.formalised_address)
            print(listing.daft_link)
        
        ```
        
        ## Documentation
        
        The documentation has been created using [mkdocs](http://www.mkdocs.org/) and the [mkdocs material theme](https://squidfunk.github.io/mkdocs-material/). To update the documentation, clone the repository and edit the markdown files in the docs/ directory.
        
        To view your changes, run:
        
        ``` bash
        mkdocs serve
        ```
        
        
        To build and publish the documentation, run:
        
        ``` bash
        sh deploy_docs.sh "Updating documentation"
        ```
        
        ## Tests
        
        The Python unittest module contains its own test discovery function, which you can run from the command line:
        
        ```
         python -m unittest discover tests/
        ```
        
        ## Contributing
        
          - Fork the project and clone locally.
          - Create a new branch for what you're going to work on.
          - Push to your origin repository.
          - Create a new pull request in GitHub.
        
Keywords: daft,web scraping,real estate,web scraper,daft.ie
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
