aws-samples / aws-iot-greengrass-v2-deploy-nvidia-deepstream
Unit Size

The distribution of size of units (measured in lines of code).

Intro
  • Unit size measurements show the distribution of size of units of code (methods, functions...).
  • Units are classified in four categories based on their size (lines of code): 1-20 (small units), 20-50 (medium size units), 51-100 (long units), 101+ (very long units).
  • You should aim at keeping units small (< 20 lines). Long units may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.
Learn more...
Unit Size Overall
  • There are 9 units with 149 lines of code in units (6.9% of code).
    • 0 very long units (0 lines of code)
    • 0 long units (0 lines of code)
    • 4 medium size units (104 lines of code)
    • 2 small units (26 lines of code)
    • 3 very small units (19 lines of code)
0% | 0% | 69% | 17% | 12%
Legend:
101+
51-100
21-50
11-20
1-10
Unit Size per Extension
101+
51-100
21-50
11-20
1-10
py0% | 0% | 69% | 17% | 12%
Unit Size per Logical Component
primary logical decomposition
101+
51-100
21-50
11-20
1-10
aws.greengrass.JetsonDLRImageClassification/1.0.00% | 0% | 69% | 17% | 12%
Alternative Visuals
Longest Units
Top 9 longest units
Unit# linesMcCabe index# params
def predict()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 31 5 1
def main()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/jetson_inference.py
 30 3 0
def predict_from_cam()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 22 7 0
def connect()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/IPCUtils.py
 21 1 1
def enable_camera()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 14 4 0
def load_image()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 12 6 1
def send_mqtt_message()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 9 1 1
def exec_full()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/jetson_inference.py
 7 1 1
def predict_from_image()
in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py
 3 1 1