[Python] ImportError: Start directory is not importable

every time that i import this command

python3 -m unittest discover -s emotion_detection/test_emotion_detection -p "*.py"

this pops up

Traceback (most recent call last):
File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/usr/lib/python3.10/unittest/__main__.py", line 18, in <module>
main(module=None)
File "/usr/lib/python3.10/unittest/main.py", line 100, in __init__
self.parseArgs(argv)
File "/usr/lib/python3.10/unittest/main.py", line 124, in parseArgs
self._do_discovery(argv[2:])
File "/usr/lib/python3.10/unittest/main.py", line 244, in _do_discovery
self.createTests(from_discovery=True, Loader=Loader)
File "/usr/lib/python3.10/unittest/main.py", line 154, in createTests
self.test = loader.discover(self.start, self.pattern, self.top)
File "/usr/lib/python3.10/unittest/loader.py", line 346, in discover
raise ImportError('Start directory is not importable: %r' % start_dir)
ImportError: Start directory is not importable: 'emotion_detection/test_emotion_detection'


all i want is to unit test the code i have never done it before so i cant really provide an example of what's supposed to happen here is what the class wants to happen.

With a functional application being available, you now need to run unit tests to validate the application output.

To run unit tests, create a new file, test_emotion_detection.py that calls the required application function from the package and tests it for the following statements and dominant emotions.

Statement Dominant Emotion
I am glad this happened joy
I am really mad about this anger
I feel disgusted just hearing about this disgust
I am so sad about this sadness
I am really afraid that this will happen fear

heres the code


import requests
import json

def emotion_detector(text_to_analyze):
# Define the URL and headers for the Watson NLP service
url = 'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'
headers = {
"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock",
"Content-Type": "application/json"
}

# Prepare the input JSON
input_json = { "raw_document": { "text": text_to_analyze } }

# Send a POST request to the Watson NLP service
response = requests.post(url, headers=headers, json=input_json)

# Debugging: Print the request and response details
print("Request JSON:", json.dumps(input_json, indent=2))
print("Response Status Code:", response.status_code)
print("Response Text:", response.text)

# Check if the request was successful
if response.status_code == 200:
# Convert the response text into a dictionary
result = response.json()

# Debugging: Print the full response dictionary
print("Response Dictionary:", json.dumps(result, indent=2))

# Extract the emotions and their scores
emotions_data = result.get('emotionPredictions', [{}])[0]
emotion_scores = emotions_data.get('emotion', {})

anger_score = emotion_scores.get('anger', 0)
disgust_score = emotion_scores.get('disgust', 0)
fear_score = emotion_scores.get('fear', 0)
joy_score = emotion_scores.get('joy', 0)
sadness_score = emotion_scores.get('sadness', 0)

# Find the dominant emotion
emotions = {
'anger': anger_score,
'disgust': disgust_score,
'fear': fear_score,
'joy': joy_score,
'sadness': sadness_score
}
dominant_emotion = max(emotions, key=emotions.get)

# Return the output in the specified format
return {
'anger': anger_score,
'disgust': disgust_score,
'fear': fear_score,
'joy': joy_score,
'sadness': sadness_score,
'dominant_emotion': dominant_emotion
}
else:
# Handle errors
return {
'error': f"Request failed with status code {response.status_code}",
'details': response.text
}

# Example usage
text = "I hate working long hours."
result = emotion_detector(text)

# Print the simplified result
print(json.dumps(result, indent=2))



screen shot of my file directory

Continue reading...