Update MIBI consumer to inherit from ImageFileConsumer. (#119)

* Improved testing coverage using fakeredis and pytest-mock (#117)

* install pytest-mock and replace monkeypatching with `mock` library.

* move testing reqs into requirements-test.txt and add 3.8 to test suite.

* update RedisClient tests to use fakeredis.

* directly patch boto3.client

* no need to alias google.cloud.storage in imports.

* Fix storage tests to use a Singleton dummy class instead of global variables.

* proper string fomatting using {} instead of %s

* move DummyStorage and DummyRedis into utils/testing_utils.py to DRY out the tests

* Update tests to use fakeredis client and fewer global variables.

* use save_output for ImageConsumer and MibiConsumer.

pass save_name into the function directly instead of calling HGETALL inside the save_output function.

* inherit from ImageFileConsumer to make better use of the pre/post-process functions.

* add keys for the mibi pre and postprocessing.

* adapt the mibi consumer tests to use the testing_utils.py helpers.

* remove unused imports.

* Fix a few license URLs. (#118)

.coveragerc

@@ -15,4 +15,4 @@ show_missing = True
 omit =
     **/*_test.py
     redis_consumer/pbs/*
-    redis_consumer/grpc_clients.py
+    redis_consumer/testing_utils.py

.travis.yml

@@ -1,4 +1,3 @@
-sudo: true
 dist: xenial
 
 git:
@@ -11,12 +10,13 @@ python:
   - 3.5
   - 3.6
   - 3.7
+  - 3.8
 
 cache: pip
 
 install:
   - travis_retry pip install -r requirements.txt
-  - travis_retry pip install pytest pytest-cov==2.5.1 pytest-pep8 coveralls
+  - travis_retry pip install -r requirements-test.txt
   # install documentation requirements
   - if [[ "$TRAVIS_PYTHON_VERSION" == "3.7" ]]; then
       travis_retry pip install -r docs/rtd-requirements.txt;

redis_consumer/consumers/base_consumer.py

@@ -121,7 +121,7 @@ def get_redis_hash(self):
             # Update redis with failed status
             self.update_key(redis_hash, {
                 'status': self.failed_status,
-                'reason': 'Invalid filetype for "%s" job.'.format(self.queue),
+                'reason': 'Invalid filetype for "{}" job.'.format(self.queue),
             })
 
     def _handle_error(self, err, redis_hash):
@@ -496,9 +496,10 @@ def predict(self, image, model_name, model_version, untile=True):
 
         # TODO: generalize for more than a single input.
         if len(model_metadata) > 1:
-            raise ValueError('Model %s:%s has %s required inputs but was only '
-                             'given %s inputs.', model_name, model_version,
-                             len(model_metadata), len(image))
+            raise ValueError('Model {}:{} has {} required inputs but was only '
+                             'given {} inputs.'.format(
+                                 model_name, model_version,
+                                 len(model_metadata), len(image)))
         model_metadata = model_metadata[0]
 
         model_input_name = model_metadata['in_tensor_name']
@@ -552,11 +553,9 @@ def predict(self, image, model_name, model_version, untile=True):
 
         return image
 
-    def save_output(self, image, redis_hash, fname, scale):
-        hvals = self.redis.hgetall(redis_hash)
+    def save_output(self, image, redis_hash, save_name, scale):
         with utils.get_tempdir() as tempdir:
             # Save each result channel as an image file
-            save_name = hvals.get('original_name', fname)
             subdir = os.path.dirname(save_name.replace(tempdir, ''))
             name = os.path.splitext(os.path.basename(save_name))[0]