final changes for release

CHANGELOG.md

@@ -3,14 +3,18 @@
 
 Changelog and version changes made with each release.
 
-## Version 2.3.2
+## Version 2.4.0
 
 * Implemented rate-limiting for API calls that could potentially exceed the quotas 
   set by Petfinder (50 calls/second, 1,000/day). An exponential backoff strategy is employed when rates exceed 
   the given limits and tries ten more times before giving up and returning the collected results.
-* Access token that is generated on first initialization of Petfinder is now refreshed automatically
-  after expiring. 
-
+* Access token that is generated on first initialization of Petfinder should now refresh automatically
+  after expiring.
+* Removed the `max_page_warning` that would be displayed when there were fewer total pages 
+  in the Petfinder API results to those requested in the `pages` parameter.
+* A `response` key has been added to the returned animal or organization object. If an ID isn't found,
+  the `response` value will be 404.
+* Type annotations have been added to the `Petfinder` methods.
 
 ## Version 2.3.1
 
@@ -25,7 +29,7 @@ Changelog and version changes made with each release.
     - `special_needs`: Filters results by animals that have special needs
 * Search filters that can take multiple values in the `animals()` function, 
   including `age`, `gender`, `status`, `animal_type`, `size`, and `coat`, should 
-  now correctly accept both comma-delimited strings, such as `age='baby,'young'` 
+  now correctly accept both comma-delimited strings, such as `age='baby,young'` 
   and lists or tuples.
 * The required version for `pandas` has been updated to at least version `1.0.0`
 
@@ -37,7 +41,7 @@ Very small maintenance patch to update several `setup.py` settings. There is no
 
 * Support for Python 3.5 has been discontinued. 
 * The `animals()` method has been updated to include new parameters provided by Petfinder's `animal` 
-  endpoint. This parameters include:
+  endpoint. These parameters include:
   - `good_with_cats`: Boolean for filtering animals that are designated as good with cats.
   - `good_with_children`: Boolean for filtering animals that are designated as good with children.
   - `good_with_dogs`: Boolean for filtering animals that are designated as good with dogs.

README.md

@@ -1,7 +1,6 @@
 # Petpy - Python Wrapper for the Petfinder API
 
 [![Documentation Status](https://readthedocs.org/projects/petpy/badge/?version=latest)](http://petpy.readthedocs.io/en/latest/?badge=latest)
-[![CircleCI](https://circleci.com/gh/aschleg/petpy/tree/master.svg?style=svg)](https://circleci.com/gh/aschleg/petpy/tree/master)
 [![Coverage Status](https://coveralls.io/repos/github/aschleg/petpy/badge.svg?branch=master)](https://coveralls.io/github/aschleg/petpy?branch=master)
 [![codecov](https://codecov.io/gh/aschleg/petpy/branch/master/graph/badge.svg)](https://codecov.io/gh/aschleg/petpy)
 [![Codacy Badge](https://api.codacy.com/project/badge/Grade/ac2a4c228a9e425ba11af69f7a5c9e51)](https://www.codacy.com/app/aschleg/petpy?utm_source=github.com&utm_medium=referral&utm_content=aschleg/petpy&utm_campaign=Badge_Grade)

test-requirements.txt

@@ -7,4 +7,5 @@ pandas>=1.0.0
 requests>=2.18.4
 ratelimit>=2.2.1
 backoff>=1.11.1
-setuptools
+setuptools
+pytest-recording

tests/test_api.py

@@ -1,18 +1,20 @@
 import os
 import pytest
 import vcr
-from dotenv import load_dotenv
-from pandas import DataFrame
+import time
 
+from pandas import DataFrame
+from dotenv import load_dotenv
 from petpy.api import Petfinder
 
+
 tape = vcr.VCR(
     cassette_library_dir='tests/cassettes',
     serializer='json',
-    record_mode='once'
+    record_mode='all'
 )
 
-#load_dotenv('../.env')
+load_dotenv('.env')
 key = os.environ.get('PETPY_PETFINDER_KEY')
 secret_key = os.environ.get('PETPY_PETFINDER_SECRET_KEY')
 
@@ -28,19 +30,21 @@ def test_authentication():
 
 
 def authenticate():
-    petf = Petfinder(key=key, secret=secret_key)
-
-    return petf
+    pf = Petfinder(key=key, secret=secret_key)
+    return pf
 
 
-petf = authenticate()
+pf = authenticate()
 
 
 @vcr.use_cassette('tests/cassettes/animal_types.yml')
 def test_animal_types():
-    response1 = petf.animal_types()
-    response2 = petf.animal_types('cat')
-    response3 = petf.animal_types(['cat', 'dog'])
+    time.sleep(2)
+    response1 = pf.animal_types()
+    time.sleep(2)
+    response2 = pf.animal_types('cat')
+    time.sleep(2)
+    response3 = pf.animal_types(['cat', 'dog'])
 
     assert isinstance(response1, dict)
     assert isinstance(response2, dict)
@@ -51,22 +55,30 @@ def test_animal_types():
     assert str.lower(response3['types'][1]['name']) == 'dog'
 
     with pytest.raises(ValueError):
-        petf.animal_types(types='elephant')
+        time.sleep(2)
+        pf.animal_types(types='elephant')
     with pytest.raises(ValueError):
-        petf.animal_types(types=['dragon', 'unicorn'])
+        time.sleep(2)
+        pf.animal_types(types=['dragon', 'unicorn'])
     with pytest.raises(TypeError):
-        petf.animal_types(types={})
+        time.sleep(2)
+        pf.animal_types(types={})
 
 
 @vcr.use_cassette('tests/cassettes/breeds.yml')
 def test_breeds():
-
-    response1 = petf.breeds()
-    response1_df = petf.breeds(return_df=True)
-    response2 = petf.breeds('cat')
-    response2_df = petf.breeds('cat', return_df=True)
-    response3 = petf.breeds(['cat', 'dog'])
-    response3_df = petf.breeds(['cat', 'dog'], return_df=True)
+    time.sleep(2)
+    response1 = pf.breeds()
+    time.sleep(2)
+    response1_df = pf.breeds(return_df=True)
+    time.sleep(2)
+    response2 = pf.breeds('cat')
+    time.sleep(2)
+    response2_df = pf.breeds('cat', return_df=True)
+    time.sleep(2)
+    response3 = pf.breeds(['cat', 'dog'])
+    time.sleep(2)
+    response3_df = pf.breeds(['cat', 'dog'], return_df=True)
 
     assert isinstance(response1, dict)
     assert len(list(set(list(response1['breeds'].keys())).difference(animal_types))) == 0
@@ -81,44 +93,55 @@ def test_breeds():
     assert isinstance(response3_df, DataFrame)
 
     with pytest.raises(ValueError):
-        petf.breeds(types='elephant')
+        time.sleep(2)
+        pf.breeds(types='elephant')
     with pytest.raises(ValueError):
-        petf.breeds(types=['dragon', 'unicorn'])
+        time.sleep(2)
+        pf.breeds(types=['dragon', 'unicorn'])
     with pytest.raises(TypeError):
-        petf.breeds(types={})
+        time.sleep(2)
+        pf.breeds(types={})
 
 
 @vcr.use_cassette('tests/cassettes/animals.yml')
 def test_animals():
-    response1 = petf.animals()
-    response1_df = petf.animals(return_df=True)
-    response2 = petf.animals(results_per_page=50, pages=3)
-    response2_df = petf.animals(results_per_page=50, pages=3, return_df=True)
+    response1 = pf.animals()
+    time.sleep(2)
+    response1_df = pf.animals(return_df=True)
+    time.sleep(2)
+    response2 = pf.animals(results_per_page=50, pages=3)
+    time.sleep(2)
+    response2_df = pf.animals(results_per_page=50, pages=3, return_df=True)
 
     animal_ids = []
     for i in response1['animals'][0:3]:
         animal_ids.append(i['id'])
-
-    response3 = petf.animals(animal_id=animal_ids, results_per_page=5)
-    response3_df = petf.animals(animal_id=animal_ids, return_df=True, results_per_page=5)
-
-    response4 = petf.animals(animal_id=animal_ids[0], results_per_page=5)
-    response4_df = petf.animals(animal_id=animal_ids[0], return_df=True, results_per_page=5)
-
-    response5 = petf.animals(good_with_children=1, good_with_cats=1, results_per_page=5)
-
-    response6 = petf.animals(before_date='2020-06-30', after_date='2020-01-01', results_per_page=5)
-    response7 = petf.animals(before_date='2020-06-30 0:0:0', after_date='2020-01-01 12:00:00', results_per_page=5)
-
-    response8 = petf.animals(good_with_dogs=1, results_per_page=5)
-    response9 = petf.animals(good_with_dogs=1, good_with_cats=1, good_with_children=1, return_df=True,
-                results_per_page=5)
-    response10 = petf.animals(special_needs=1, house_trained=1, declawed=1, return_df=True, results_per_page=5)
-
+    time.sleep(2)
+    response3 = pf.animals(animal_id=animal_ids, results_per_page=5)
+    time.sleep(2)
+    response3_df = pf.animals(animal_id=animal_ids, return_df=True, results_per_page=5)
+    time.sleep(2)
+    response4 = pf.animals(animal_id=animal_ids[0], results_per_page=5)
+    time.sleep(2)
+    response4_df = pf.animals(animal_id=animal_ids[0], return_df=True, results_per_page=5)
+    time.sleep(2)
+    response5 = pf.animals(good_with_children=1, good_with_cats=1, results_per_page=5)
+    time.sleep(2)
+    response6 = pf.animals(before_date='2020-06-30', after_date='2020-01-01', results_per_page=5)
+    time.sleep(2)
+    response7 = pf.animals(before_date='2020-06-30 0:0:0', after_date='2020-01-01 12:00:00', results_per_page=5)
+    time.sleep(2)
+    response8 = pf.animals(good_with_dogs=1, results_per_page=5)
+    time.sleep(2)
+    response9 = pf.animals(good_with_dogs=1, good_with_cats=1, good_with_children=1, return_df=True,
+                           results_per_page=5)
+    time.sleep(2)
+    response10 = pf.animals(special_needs=1, house_trained=1, declawed=1, return_df=True, results_per_page=5)
+    time.sleep(2)
     with pytest.raises(ValueError):
-        petf.animals(after_date='2021-07-02', before_date='2021-07-01', results_per_page=5)
-
-    response11 = petf.animals(status=['found', 'adoptable'], results_per_page=5)
+        pf.animals(after_date='2021-07-02', before_date='2021-07-01', results_per_page=5)
+    time.sleep(2)
+    response11 = pf.animals(status=['found', 'adoptable'], results_per_page=5)
 
     assert isinstance(response1, dict)
     assert len(response1['animals']) == 20
@@ -164,20 +187,19 @@ def test_animals():
 
 @vcr.use_cassette('tests/cassettes/organizations.yml')
 def test_organizations():
-    response1 = petf.organizations()
-    response1_df = petf.organizations(return_df=True)
-    response2 = petf.organizations(results_per_page=50, pages=3)
-    response2_df = petf.organizations(results_per_page=50, pages=3, return_df=True)
+    response1 = pf.organizations()
+    response1_df = pf.organizations(return_df=True)
+    response2 = pf.organizations(results_per_page=50, pages=3)
+    response2_df = pf.organizations(results_per_page=50, pages=3, return_df=True)
 
     org_ids = []
     for i in response1['organizations'][0:3]:
         org_ids.append(i['id'])
-
-    response3 = petf.organizations(organization_id=org_ids)
-    response3_df = petf.organizations(organization_id=org_ids, return_df=True)
-
-    response4 = petf.organizations(organization_id=org_ids[0])
-    response4_df = petf.organizations(organization_id=org_ids[0], return_df=True)
+
+    response3 = pf.organizations(organization_id=org_ids)
+    response3_df = pf.organizations(organization_id=org_ids, return_df=True)
+    response4 = pf.organizations(organization_id=org_ids[0])
+    response4_df = pf.organizations(organization_id=org_ids[0], return_df=True)
 
     assert isinstance(response1, dict)
     assert len(response1['organizations']) == 20
@@ -216,42 +238,42 @@ def test_check_parameters():
     good_with_dogs = 'yes'
 
     with pytest.raises(ValueError):
-        petf.animals(size=size1)
+        pf.animals(size=size1)
     with pytest.raises(ValueError):
-        petf.animals(size=[size1, size2])
+        pf.animals(size=[size1, size2])
     with pytest.raises(ValueError):
-        petf.animals(gender=gender1)
+        pf.animals(gender=gender1)
     with pytest.raises(ValueError):
-        petf.animals(gender=[gender1, gender2])
+        pf.animals(gender=[gender1, gender2])
     with pytest.raises(ValueError):
-        petf.animals(age=age1)
+        pf.animals(age=age1)
     with pytest.raises(ValueError):
-        petf.animals(age=[age1, age2])
+        pf.animals(age=[age1, age2])
     with pytest.raises(ValueError):
-        petf.animals(coat=coat1)
+        pf.animals(coat=coat1)
     with pytest.raises(ValueError):
-        petf.animals(coat=[coat1, coat2])
+        pf.animals(coat=[coat1, coat2])
     with pytest.raises(ValueError):
-        petf.animals(status=status)
+        pf.animals(status=status)
     with pytest.raises(ValueError):
-        petf.animals(sort=sort)
+        pf.animals(sort=sort)
     with pytest.raises(ValueError):
-        petf.animals(distance=distance_int)
+        pf.animals(distance=distance_int)
     with pytest.raises(ValueError):
-        petf.animals(distance=distance_str)
+        pf.animals(distance=distance_str)
     with pytest.raises(ValueError):
-        petf.animals(results_per_page=limit_int)
+        pf.animals(results_per_page=limit_int)
     with pytest.raises(ValueError):
-        petf.animals(results_per_page=limit_str)
+        pf.animals(results_per_page=limit_str)
     with pytest.raises(ValueError):
-        petf.animals(declawed=declawed)
+        pf.animals(declawed=declawed)
     with pytest.raises(ValueError):
-        petf.animals(house_trained=house_trained)
+        pf.animals(house_trained=house_trained)
     with pytest.raises(ValueError):
-        petf.animals(special_needs=special_needs)
+        pf.animals(special_needs=special_needs)
     with pytest.raises(ValueError):
-        petf.animals(good_with_cats=good_with_cats)
+        pf.animals(good_with_cats=good_with_cats)
     with pytest.raises(ValueError):
-        petf.animals(good_with_dogs=good_with_dogs)
+        pf.animals(good_with_dogs=good_with_dogs)
     with pytest.raises(ValueError):
-        petf.animals(good_with_children=good_with_children)
+        pf.animals(good_with_children=good_with_children)