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petpy is easily installed through pip.

pip install petpy

The library can also be cloned or downloaded into a location of your choosing and then installed using the setup.py file per the following:

git clone git@github.com:aschleg/petpy.git
cd petpy
python setup.py install

An account must first be created with Petfinder to receive an API and secret key. The API and secret key will be used to grant access to the Petfinder API, which lasts for 3600 seconds, or one hour. After the authentication period ends, you must re-authenticate with the Petfinder API. The following are some quick examples for using petpy to get started. More in-depth tutorials for petpy and some examples of what can be done with the library, please see the More Examples and Tutorials section below.

Authenticating the connection with the Petfinder API is done at the same time the Petfinder class is initialized.

pf = Petfinder(key=key, secret=secret)

The following are some quick examples for getting started with petpy and the Petfinder API.

# All animal types and their relevant data.
all_types = pf.animal_types()

# Returning data for a single animal type
dogs = pf.animal_types('dog')

# Getting multiple animal types at once
cat_dog_rabbit_types = pf.animal_types(['cat', 'dog', 'rabbit'])

cat_breeds = pf.breeds('cat')
dog_breeds = pf.breeds('dog')

# All available breeds or multiple breeds can also be returned.

all_breeds = pf.breeds()
cat_dog_rabbit = pf.breeds(types=['cat', 'dog', 'rabbit'])

The breeds method can also be set to coerce the returned JSON results into a pandas DataFrame by setting the parameter return_df = True.

cat_breeds_df = pf.breeds('cat', return_df = True)
all_breeds_df = pf.breeds(return_df = True)

The animals() method returns animals based on specified criteria that are listed in the Petfinder database. Specific animals can be searched using the animal_id parameter, or a search of the database can be performed by entering the desired search criteria.

# Getting first 20 results without any search criteria
animals = pf.animals()

# Extracting data on specific animals with animal_ids

animal_ids = []
for i in animals['animals'][0:3]:
    animal_ids.append(i['id'])
    
animal_data = pf.animals(animal_id=animal_ids)

# Returning a pandas DataFrame of the first 150 animal results
animals = pf.animals(results_per_page=50, pages=3, return_df=True)

Similar to the animals() method described above, the organizations() method returns data on animal welfare organizations listed in the Petfinder database based on specific criteria, if any. In addition to a general search of animal welfare organizations, specific organizational data can be extracted by supplying the organizations() method with organization IDs.

# Return the first 1,000 animal welfare organizations as a pandas DataFrame

organizations = pf.organizations(results_per_page=100, pages=10, return_df=True)

# Get organizations in the state of Washington

wa_organizations = pf.organizations(state='WA')

A series of IPython notebooks that introduce and explore some of the functionality and possible uses of the petpy library. The notebooks can also be launched interactively with binder by clicking the "launch binder" badge.

• 01 -Introduction to petpy
• 02 - Download 45,000 Adoptable Cat Images using petpy and multiprocessing
  • Please note the following notebook is still based on the legacy version of Petfinder and thus are not fully representative of the functionality and methods of the most recent version of petpy and the Petfinder API. These are currently being updated to reflect the new version of petpy.
• 03 - Download Pure Breeds Cat Images with petpy for Deep Neural Network training
  • Provided by contributor ma755

The following are longer usage examples and tutorials that have been posted to external media websites such as Medium.com:

• Analyze Petfinder Adoptable Pet Descriptions with the IBM Watson Tone Analyzer — Part One

• Petpy documentation
• Petpy changelog
• Petfinder API v2.0 documentation

• Python >= 3.6
• requests >= 2.18.4
• Although not strictly required to use petpy, the pandas library is needed for returning the results as a DataFrame.

Petfinder.com is one of the largest online, searchable databases for finding a new pet online. The database contains information on over 14,000 animal shelters and adoption organizations across North America with nearly 300,000 animals available for adoption. Not only does this make it a great resource for those looking to adopt their new best friend, but the data and information provided in Petfinder's database makes it ideal for analysis.

• ma755 - Fixed several functions that use an animal parameter and implementing checks for exceeding the Petfinder API limit.
• ljlevins - Found and fixed an error with the distance parameter used in the organizations API endpoint.

MIT