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 282 files with 27,748 lines of code.
- 3 very long files (4,189 lines of code)
- 4 long files (2,840 lines of code)
- 30 medium size files (9,637 lines of codeclsfd_ftr_w_mp_ins)
- 37 small files (5,470 lines of code)
- 208 very small files (5,612 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 50)
| File | # lines | # units |
|---|---|---|
 abstract_trainer.py in core/src/autogluon/core/trainer |
1803 | 83 |
predictor.py in tabular/src/autogluon/tabular/predictor |
1239 | 69 |
models.py in text/src/autogluon/text/text_prediction/mx |
1147 | 33 |
bagged_ensemble_model.py in core/src/autogluon/core/models/ensemble |
837 | 53 |
abstract_learner.py in tabular/src/autogluon/tabular/learner |
693 | 40 |
abstract_model.py in core/src/autogluon/core/models/abstract |
689 | 72 |
utils.py in core/src/autogluon/core/utils |
621 | 32 |
tab_transformer_encoder.py in tabular/src/autogluon/tabular/models/tab_transformer |
495 | 67 |
modules.py in text/src/autogluon/text/text_prediction/mx |
485 | 16 |
tabular_nn_torch.py in tabular/src/autogluon/tabular/models/tabular_nn/torch |
455 | 22 |
predictor.py in vision/src/autogluon/vision/predictor |
437 | 17 |
tabular_nn_mxnet.py in tabular/src/autogluon/tabular/models/tabular_nn/mxnet |
432 | 19 |
categorical_encoders.py in tabular/src/autogluon/tabular/models/tabular_nn/utils |
408 | 22 |
fold_fitting_strategy.py in core/src/autogluon/core/models/ensemble |
403 | 28 |
abstract.py in features/src/autogluon/features/generators |
369 | 36 |
tab_transformer_model.py in tabular/src/autogluon/tabular/models/tab_transformer |
364 | 14 |
tabular_nn_fastai.py in tabular/src/autogluon/tabular/models/fastainn |
363 | 19 |
preprocessing.py in text/src/autogluon/text/text_prediction/mx |
353 | 25 |
image_classification.py in vision/src/autogluon/vision/_gluoncv |
344 | 6 |
__init__.py in core/src/autogluon/core/metrics |
343 | 37 |
feature_selection.py in core/src/autogluon/core/utils |
329 | 13 |
presets.py in tabular/src/autogluon/tabular/trainer/model_presets |
317 | 5 |
predictor.py in text/src/autogluon/text/text_prediction/predictor |
306 | 18 |
object_detection.py in vision/src/autogluon/vision/_gluoncv |
305 | 6 |
serialization.py in core/src/autogluon/core/utils |
286 | 12 |
lgb_model.py in tabular/src/autogluon/tabular/models/lgb |
279 | 15 |
feature_metadata.py in common/src/autogluon/common/features |
271 | 22 |
label_cleaner.py in core/src/autogluon/core/data |
264 | 38 |
default_learner.py in tabular/src/autogluon/tabular/learner |
259 | 8 |
rf_model.py in tabular/src/autogluon/tabular/models/rf |
254 | 19 |
rf_quantile.py in tabular/src/autogluon/tabular/models/rf |
227 | 10 |
classification_metrics.py in core/src/autogluon/core/metrics |
222 | 4 |
knn_model.py in tabular/src/autogluon/tabular/models/knn |
221 | 21 |
torch_network_modules.py in tabular/src/autogluon/tabular/models/tabular_nn/torch |
216 | 9 |
modified_transformer.py in tabular/src/autogluon/tabular/models/tab_transformer |
215 | 14 |
detector.py in vision/src/autogluon/vision/detector |
214 | 11 |
seq_scheduler.py in core/src/autogluon/core/scheduler |
201 | 18 |
tabular_nn_dataset.py in tabular/src/autogluon/tabular/models/tabular_nn/mxnet |
196 | 13 |
text_ngram.py in features/src/autogluon/features/generators |
192 | 9 |
presets_configs.py in vision/src/autogluon/vision/configs |
185 | 3 |
stacker_ensemble_model.py in core/src/autogluon/core/models/ensemble |
184 | 15 |
utils.py in vision/src/autogluon/vision/_gluoncv |
182 | 2 |
catboost_model.py in tabular/src/autogluon/tabular/models/catboost |
181 | 12 |
xgboost_model.py in tabular/src/autogluon/tabular/models/xgboost |
175 | 16 |
_utils.py in common/src/autogluon/common/loaders |
175 | 8 |
lr_model.py in tabular/src/autogluon/tabular/models/lr |
174 | 16 |
image_predictor.py in tabular/src/autogluon/tabular/models/image_prediction |
170 | 12 |
try_import.py in core/src/autogluon/core/utils |
168 | 16 |
callbacks.py in tabular/src/autogluon/tabular/models/lgb |
164 | 1 |
ensemble_selection.py in core/src/autogluon/core/models/greedy_ensemble |
160 | 10 |
Files With Most Units (Top 20)
| File | # lines | # units |
|---|---|---|
abstract_trainer.py in core/src/autogluon/core/trainer |
1803 | 83 |
abstract_model.py in core/src/autogluon/core/models/abstract |
689 | 72 |
predictor.py in tabular/src/autogluon/tabular/predictor |
1239 | 69 |
tab_transformer_encoder.py in tabular/src/autogluon/tabular/models/tab_transformer |
495 | 67 |
bagged_ensemble_model.py in core/src/autogluon/core/models/ensemble |
837 | 53 |
abstract_learner.py in tabular/src/autogluon/tabular/learner |
693 | 40 |
label_cleaner.py in core/src/autogluon/core/data |
264 | 38 |
__init__.py in core/src/autogluon/core/metrics |
343 | 37 |
abstract.py in features/src/autogluon/features/generators |
369 | 36 |
config_helper.py in tabular/src/autogluon/tabular/configs |
151 | 34 |
models.py in text/src/autogluon/text/text_prediction/mx |
1147 | 33 |
utils.py in core/src/autogluon/core/utils |
621 | 32 |
fold_fitting_strategy.py in core/src/autogluon/core/models/ensemble |
403 | 28 |
preprocessing.py in text/src/autogluon/text/text_prediction/mx |
353 | 25 |
tabular_nn_torch.py in tabular/src/autogluon/tabular/models/tabular_nn/torch |
455 | 22 |
categorical_encoders.py in tabular/src/autogluon/tabular/models/tabular_nn/utils |
408 | 22 |
feature_metadata.py in common/src/autogluon/common/features |
271 | 22 |
knn_model.py in tabular/src/autogluon/tabular/models/knn |
221 | 21 |
tabular_nn_mxnet.py in tabular/src/autogluon/tabular/models/tabular_nn/mxnet |
432 | 19 |
rf_model.py in tabular/src/autogluon/tabular/models/rf |
254 | 19 |
Files With Long Lines (Top 20)
There are 92 files with lines longer than 120 characters. In total, there are 814 long lines.
| File | # lines | # units | # long lines |
|---|---|---|---|
abstract_trainer.py in core/src/autogluon/core/trainer |
1803 | 83 | 130 |
feature_selection.py in core/src/autogluon/core/utils |
329 | 13 | 61 |
abstract_learner.py in tabular/src/autogluon/tabular/learner |
693 | 40 | 45 |
bagged_ensemble_model.py in core/src/autogluon/core/models/ensemble |
837 | 53 | 29 |
predictor.py in tabular/src/autogluon/tabular/predictor |
1239 | 69 | 28 |
tabular_nn_mxnet.py in tabular/src/autogluon/tabular/models/tabular_nn/mxnet |
432 | 19 | 25 |
feature_metadata.py in common/src/autogluon/common/features |
271 | 22 | 22 |
utils.py in core/src/autogluon/core/utils |
621 | 32 | 21 |
default_learner.py in tabular/src/autogluon/tabular/learner |
259 | 8 | 20 |
abstract.py in features/src/autogluon/features/generators |
369 | 36 | 20 |
presets.py in tabular/src/autogluon/tabular/trainer/model_presets |
317 | 5 | 17 |
pipeline.py in features/src/autogluon/features/generators |
89 | 10 | 17 |
tab_transformer_model.py in tabular/src/autogluon/tabular/models/tab_transformer |
364 | 14 | 16 |
plots.py in core/src/autogluon/core/utils |
156 | 5 | 16 |
bulk.py in features/src/autogluon/features/generators |
132 | 7 | 15 |
text_ngram.py in features/src/autogluon/features/generators |
192 | 9 | 15 |
abstract_model.py in core/src/autogluon/core/models/abstract |
689 | 72 | 14 |
tabular_nn_torch.py in tabular/src/autogluon/tabular/models/tabular_nn/torch |
455 | 22 | 13 |
lgb_model.py in tabular/src/autogluon/tabular/models/lgb |
279 | 15 | 12 |
load_pd.py in common/src/autogluon/common/loaders |
142 | 5 | 12 |