The distribution of size of files (measured in lines of code).
Intro
- File size measurements show the distribution of size of files.
- Files are classified in four categories based on their size (lines of code): 1-100 (very small files), 101-200 (small files), 201-500 (medium size files), 501-1000 (long files), 1001+(very long files).
- It is a good practice to keep files small. Long files may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.
File Size Overall
- There are 36 files with 877 lines of code.
- 0 very long files (0 lines of code)
- 0 long files (0 lines of code)
- 0 medium size files (0 lines of codeclsfd_ftr_w_mp_ins)
- 0 small files (0 lines of code)
- 36 very small files (877 lines of code)
Legend:
1001+
501-1000
201-500
101-200
1-100
explore: zoomable circles | sunburst | 3D view
File Size per Extension
1001+
501-1000
201-500
101-200
1-100
File Size per Logical Decomposition
primary
Longest Files (Top 36)
| File | # lines | # units |
|---|---|---|
 template.yml in online-machine-learning-aws-lambda |
69 | - |
 app.py in online-machine-learning-aws-lambda/app/lambda_training |
68 | 5 |
 App.java in djl-object-detection-inference-docker-lambda/src/main/java/com/example |
63 | 2 |
invoke_x86_64_arm64_lambdas.py in xgboost-inference-arm64-docker-lambda |
52 | 3 |
App.java in djl-tensorflow-lite-inference-docker-lambda/src/main/java/com/example |
51 | 2 |
mnist-2.py in tensorflow-train-in-sagemaker-deploy-with-lambda |
41 | 4 |
app.py in online-machine-learning-aws-lambda/app/lambda_inference |
38 | 2 |
app.py in pytorch-inference-docker-lambda/app |
28 | 1 |
app.py in tensorflow-inference-docker-lambda/app |
27 | 1 |
bc_xgboost_train.py in xgboost-inference-docker-lambda/train-code |
25 | - |
template.yaml in xgboost-built-in-algo-train-in-sagemaker-deploy-with-lambda |
25 | - |
template.yaml in xgboost-inference-arm64-docker-lambda |
25 | - |
bc_xgboost_train.py in xgboost-inference-arm64-docker-lambda/train-code |
25 | - |
app.py in tensorflow-train-in-sagemaker-deploy-with-lambda/container/app |
24 | 1 |
template.yaml in xgboost-inference-docker-lambda |
23 | - |
template.yaml in hebert-sentiment-analysis-inference-docker-lambda |
23 | - |
template.yaml in pytorch-inference-docker-lambda |
23 | - |
template.yaml in scikit-learn-inference-docker-lambda |
23 | - |
template.yaml in djl-tensorflow-lite-inference-docker-lambda |
23 | - |
template.yaml in tensorflow-train-in-sagemaker-deploy-with-lambda |
23 | - |
template.yaml in tensorflow-inference-docker-lambda |
23 | - |
template.yaml in djl-object-detection-inference-docker-lambda |
23 | - |
scikit_learn_iris.py in scikit-learn-inference-docker-lambda/train-code |
18 | - |
app.py in xgboost-built-in-algo-train-in-sagemaker-deploy-with-lambda/app |
18 | 1 |
app.py in hebert-sentiment-analysis-inference-docker-lambda/app |
14 | 1 |
app.py in xgboost-inference-docker-lambda/app |
13 | 1 |
app.py in xgboost-inference-arm64-docker-lambda/app |
13 | 1 |
app.py in scikit-learn-inference-docker-lambda/app |
11 | 1 |
Request.java in djl-tensorflow-lite-inference-docker-lambda/src/main/java/com/example |
10 | 2 |
Request.java in djl-object-detection-inference-docker-lambda/src/main/java/com/example |
10 | 2 |
hebert_model.py in hebert-sentiment-analysis-inference-docker-lambda |
8 | - |
app.py in blazingtext-text-classification-train-in-sagemaker-deploy-with-lambda/container/app |
8 | 1 |
resnet.py in pytorch-inference-docker-lambda/model |
6 | - |
__init__.py in online-machine-learning-aws-lambda |
1 | - |
__init__.py in online-machine-learning-aws-lambda/app/lambda_training |
1 | - |
__init__.py in online-machine-learning-aws-lambda/app/lambda_inference |
1 | - |
Files With Most Units (Top 17)
| File | # lines | # units |
|---|---|---|
app.py in online-machine-learning-aws-lambda/app/lambda_training |
68 | 5 |
mnist-2.py in tensorflow-train-in-sagemaker-deploy-with-lambda |
41 | 4 |
invoke_x86_64_arm64_lambdas.py in xgboost-inference-arm64-docker-lambda |
52 | 3 |
Request.java in djl-tensorflow-lite-inference-docker-lambda/src/main/java/com/example |
10 | 2 |
App.java in djl-tensorflow-lite-inference-docker-lambda/src/main/java/com/example |
51 | 2 |
Request.java in djl-object-detection-inference-docker-lambda/src/main/java/com/example |
10 | 2 |
App.java in djl-object-detection-inference-docker-lambda/src/main/java/com/example |
63 | 2 |
app.py in online-machine-learning-aws-lambda/app/lambda_inference |
38 | 2 |
app.py in xgboost-inference-docker-lambda/app |
13 | 1 |
app.py in hebert-sentiment-analysis-inference-docker-lambda/app |
14 | 1 |
app.py in pytorch-inference-docker-lambda/app |
28 | 1 |
app.py in scikit-learn-inference-docker-lambda/app |
11 | 1 |
app.py in tensorflow-train-in-sagemaker-deploy-with-lambda/container/app |
24 | 1 |
app.py in xgboost-built-in-algo-train-in-sagemaker-deploy-with-lambda/app |
18 | 1 |
app.py in tensorflow-inference-docker-lambda/app |
27 | 1 |
app.py in blazingtext-text-classification-train-in-sagemaker-deploy-with-lambda/container/app |
8 | 1 |
app.py in xgboost-inference-arm64-docker-lambda/app |
13 | 1 |
Files With Long Lines (Top 2)
There are 2 files with lines longer than 120 characters. In total, there are 2 long lines.
| File | # lines | # units | # long lines |
|---|---|---|---|
bc_xgboost_train.py in xgboost-inference-docker-lambda/train-code |
25 | - | 1 |
bc_xgboost_train.py in xgboost-inference-arm64-docker-lambda/train-code |
25 | - | 1 |