• 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.

• There are 1,501 files with 188,951 lines of code.
• 25 very long files (33,329 lines of code)
• 15 long files (9,789 lines of code)
• 193 medium size files (60,526 lines of codeclsfd_ftr_w_mp_ins)
• 402 small files (52,672 lines of code)
• 866 very small files (32,635 lines of code)

There are 107 files with lines longer than 120 characters. In total, there are 500 long lines.

File	# lines	# units	# long lines
label_arn.py in ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/src/lambda_src/shared	326	5	64
model_package_arns.py in aws_marketplace/using_model_packages/improving_industrial_workplace_safety/src	73	4	52
model_package_arns.py in aws_marketplace/using_model_packages/evaluating_aws_marketplace_models_for_person_counting_use_case/src	43	2	32
model_package_arns.py in aws_marketplace/using_model_packages/auto_insurance/src	37	2	26
main-packaged.yml in ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/deploy	1145	-	23
model_package_arns.py in aws_marketplace/using_model_packages/data_quality_monitoring/src	22	1	16
model_package_arns.py in aws_marketplace/using_model_packages/creative-writing-using-gpt-2-text-generation/src	22	1	16
scikit_product_arns.py in aws_marketplace/using_model_packages/amazon_demo_product/src	19	1	13
algorithm_arns.py in aws_marketplace/using_algorithms/automl/src	19	1	13
scikit_product_arns.py in aws_marketplace/using_algorithms/amazon_demo_product/src	19	1	13
train_gpt_simple.py in training/distributed_training/pytorch/model_parallel/gpt2	1012	15	8
fp16.py in training/distributed_training/pytorch/model_parallel/gpt2/fp16	560	40	7
main-merged.yml in ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/cloudformation	1030	-	5
create_datasets.py in end_to_end/music_recommendation/code	112	1	5
demo_helpers.py in end_to_end/music_recommendation/code	168	4	5
inference_specification.py in end_to_end/music_recommendation/code	21	3	5
reporting.yml in ground_truth_labeling_jobs/multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions/cloudformation	255	-	4
Rmd breast_cancer_eda.Rmd in r_examples/rsconnect_rmarkdown	67	-	4
template.yaml in ground_truth_labeling_jobs/bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning/src	575	-	3
cloudwatch_logger.py in reinforcement_learning/bandits_statlog_vw_customEnv/common/sagemaker_rl/orchestrator/utils	228	8	3