fix: added timezone to InputObservation, updated tests

src/input/input_handling.py

@@ -257,7 +257,7 @@ def metadata_inputs_one_file(file:UploadedFile, image_hash:str, dbg_ix:int=0) ->
 
     observation = InputObservation(image=image, latitude=latitude, longitude=longitude,
                                 author_email=author_email, image_datetime_raw=image_datetime_raw, 
-                                date=date, time=time,
+                                date=date, time=time, timezone=tz_str,
                                 uploaded_file=file, image_md5=image_hash
                                 )
 

src/input/input_observation.py

@@ -26,6 +26,8 @@ class InputObservation:
             Date of the observation
         time (datetime.time): 
             Time of the observation
+        timezone (str):
+            Timezone of the observation (e.g. +0300)
         uploaded_file (UploadedFile): 
             The uploaded file associated with the observation.
         image_md5 (str):
@@ -57,6 +59,7 @@ class InputObservation:
         author_email:str=None, image_datetime_raw:str=None, 
         date:datetime.date=None, 
         time:datetime.time=None, 
+        timezone:str=None,
         uploaded_file:UploadedFile=None, image_md5:str=None):
 
         self.image = image
@@ -66,6 +69,7 @@ class InputObservation:
         self.image_datetime_raw = image_datetime_raw
         self.date = date
         self.time = time
+        self.timezone = timezone
         self.uploaded_file = uploaded_file
         self.image_md5 = image_md5
         # attributes that get set after predictions/processing
@@ -121,7 +125,7 @@ class InputObservation:
         return (
             f"Observation: {_im_str}, {self.latitude}, {self.longitude}, "
             f"{self.author_email}, {self.image_datetime_raw}, {self.date}, " 
-            f"{self.time}, {self.uploaded_file}, {self.image_md5}"
+            f"{self.time}, {self.timezone}, {self.uploaded_file}, {self.image_md5}"
         )
 
     def __repr__(self):
@@ -135,6 +139,7 @@ class InputObservation:
             f"raw timestamp: {self.image_datetime_raw}, "
             f"Date: {self.date}, "
             f"Time: {self.time}, "
+            f"Timezone: {self.timezone}, "
             f"Uploaded Filename: {self.uploaded_file}"
             f"Image MD5 hash: {self.image_md5}"
         )
@@ -158,6 +163,7 @@ class InputObservation:
             self.date == other.date and
             # temporarily skip time, it is followed by the clock and that is always differnt 
             #self.time == other.time and 
+            self.timezone == other.timezone and
             self.uploaded_file == other.uploaded_file and 
             self.image_md5 == other.image_md5
             )
@@ -167,7 +173,7 @@ class InputObservation:
     # only highlight the differences, if element is the same don't show it
     # have a summary at the top that shows if the observations are the same or not
 
-    def show_diff(self, other):
+    def show_diff(self, other: 'InputObservation'):
         """Show the differences between two observations"""
         differences = []
         if self.image is None or other.image is None:
@@ -189,6 +195,8 @@ class InputObservation:
             differences.append(f"   Date is different. (self: {self.date}, other: {other.date})")
         if self.time != other.time:
             differences.append(f"   Time is different. (self: {self.time}, other: {other.time})")
+        if self.timezone != other.timezone:
+            differences.append(f"   Timezone is different. (self: {self.timezone}, other: {other.timezone})")
         if self.uploaded_file != other.uploaded_file:
             differences.append("   Uploaded filename is different.")
         if self.image_md5 != other.image_md5:
@@ -216,6 +224,7 @@ class InputObservation:
             "image_datetime_raw": self.image_datetime_raw,
             "date": str(self.date),
             "time": str(self.time),
+            "timezone": str(self.timezone),
             "selected_class": self._selected_class,
             "top_prediction": self._top_predictions[0] if len(self._top_predictions) else None,
             "class_overriden": self._class_overriden,
@@ -233,12 +242,13 @@ class InputObservation:
             image_datetime_raw=data.get("image_datetime_raw"),
             date=data.get("date"),
             time=data.get("time"),
+            timezone=data.get("timezone"),
             uploaded_file=data.get("uploaded_file"),
             image_hash=data.get("image_md5")
         )
 
     @classmethod
-    def from_input(cls, input):
+    def from_input(cls, input: 'InputObservation'):
         return cls(
             image=input.image,
             latitude=input.latitude,
@@ -247,8 +257,9 @@ class InputObservation:
             image_datetime_raw=input.image_datetime_raw,
             date=input.date,
             time=input.time,
+            timezone=input.timezone,
             uploaded_file=input.uploaded_file,
-            image_hash=input.image_hash
+            image_md5=input.image_md5
         )
 
 

tests/test_input_observation.py

@@ -89,11 +89,12 @@ def test_input_observation_valid(mock_uploadedFile):
     
     _date="2023-10-10"
     _time="10:10:10"
-    image_datetime_raw = _date + " " + _time
-    dt = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S")
+    _timezone = "+04:00"
+    image_datetime_raw = _date + " " + _time + " " + _timezone
+    dt = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
     date = dt.date()    
     time = dt.time()
-
+    tz_str = dt.strftime('%z')
     ## make a random image with dtype uint8 using np.random.randint
     image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
     image_md5 = 'd1d2515e6f6ac4c5ca6dd739d5143cd4' # 32 hex chars.
@@ -101,7 +102,7 @@ def test_input_observation_valid(mock_uploadedFile):
     obs = InputObservation(
         image=image, 
         latitude=12.34, longitude=56.78, author_email=author_email,
-        time=time, date=date,
+        time=time, date=date, timezone=tz_str,
         uploaded_file=mock_file,
         image_md5=image_md5,
         )
@@ -116,6 +117,7 @@ def test_input_observation_valid(mock_uploadedFile):
     assert isinstance(obs.time, datetime.time)
     assert str(obs.date) == "2023-10-10"
     assert str(obs.time) == "10:10:10"
+    assert obs.timezone == tz_str
 
     assert obs.uploaded_file.name == image_name
     assert obs.uploaded_file.size == 123456
@@ -274,16 +276,20 @@ def good_datadict_for_input_observation(mock_uploadedFile) -> dict:
     # set up the good and bad inputs
     _date="2023-10-10"
     _time="10:10:10"
-    image_datetime_raw = _date + " " + _time
+    _timezone = "+04:00"
+    image_datetime_raw = _date + " " + _time + " " + _timezone
+    #dt = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
     fname = "test_image.jpg"
     image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
     
-    dt_ok = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S")
+    dt_ok = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
+    tz_str = dt_ok.strftime('%z')
     valid_inputs = {
         "author_email": "test@example.com",
         "uploaded_file": mock_uploadedFile(name=fname).get_data(),
         "date": dt_ok.date(),
         "time": dt_ok.time(),
+        "timezone": tz_str,
         "image": image,
         "image_md5": 'd1d2515e6f6ac4c5ca6dd739d5143cd4', # 32 hex chars.
         "image_datetime_raw": image_datetime_raw,