openai / openai-cookbook
File Size

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.
Learn more...
File Size Overall
  • There are 8 files with 7,716 lines of code.
    • 3 very long files (6,052 lines of code)
    • 1 long files (673 lines of code)
    • 3 medium size files (952 lines of code)
    • 0 small files (0 lines of code)
    • 1 very small files (39 lines of code)
78% | 8% | 12% | 0% | <1%
Legend:
1001+
501-1000
201-500
101-200
1-100


explore: grouped by folders | grouped by size | sunburst | 3D view
File Size per Extension
1001+
501-1000
201-500
101-200
1-100
yaml86% | 0% | 13% | 0% | 0%
ipynb71% | 16% | 11% | 0% | 0%
py0% | 0% | 0% | 0% | 100%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
ROOT86% | 0% | 13% | 0% | 0%
articles71% | 16% | 11% | 0% | 0%
.github0% | 0% | 0% | 0% | 100%
Longest Files (Top 8)
File# lines# units
3221 -
1635 -
fine-tune-korean.ipynb
in articles/gpt-oss
1196 -
fine-tune-transfomers.ipynb
in articles/gpt-oss
673 -
496 -
run-colab.ipynb
in articles/gpt-oss
247 -
run-nvidia.ipynb
in articles/gpt-oss
209 -
check_notebooks.py
in .github/scripts
39 3
Files With Most Units (Top 1)
File# lines# units
check_notebooks.py
in .github/scripts
39 3
Files With Long Lines (Top 7)

There are 7 files with lines longer than 120 characters. In total, there are 305 long lines.

File# lines# units# long lines
1635 - 187
fine-tune-transfomers.ipynb
in articles/gpt-oss
673 - 52
fine-tune-korean.ipynb
in articles/gpt-oss
1196 - 21
run-nvidia.ipynb
in articles/gpt-oss
209 - 14
3221 - 13
496 - 10
run-colab.ipynb
in articles/gpt-oss
247 - 8
Correlations

File Size vs. Commits (all time): 8 points

registry.yaml x: 331 commits (all time) y: 3221 lines of code authors.yaml x: 135 commits (all time) y: 496 lines of code articles/gpt-oss/build-your-own-fact-checker-cerebras.ipynb x: 2 commits (all time) y: 1635 lines of code articles/gpt-oss/fine-tune-korean.ipynb x: 1 commits (all time) y: 1196 lines of code articles/gpt-oss/run-nvidia.ipynb x: 1 commits (all time) y: 209 lines of code articles/gpt-oss/run-colab.ipynb x: 3 commits (all time) y: 247 lines of code articles/gpt-oss/fine-tune-transfomers.ipynb x: 2 commits (all time) y: 673 lines of code .github/scripts/check_notebooks.py x: 1 commits (all time) y: 39 lines of code
3221.0
lines of code
  min: 39.0
  average: 964.5
  25th percentile: 218.5
  median: 584.5
  75th percentile: 1525.25
  max: 3221.0
0 331.0
commits (all time)
min: 1.0 | average: 59.5 | 25th percentile: 1.0 | median: 2.0 | 75th percentile: 102.0 | max: 331.0

File Size vs. Contributors (all time): 8 points

registry.yaml x: 113 contributors (all time) y: 3221 lines of code authors.yaml x: 95 contributors (all time) y: 496 lines of code articles/gpt-oss/build-your-own-fact-checker-cerebras.ipynb x: 2 contributors (all time) y: 1635 lines of code articles/gpt-oss/fine-tune-korean.ipynb x: 1 contributors (all time) y: 1196 lines of code articles/gpt-oss/run-nvidia.ipynb x: 1 contributors (all time) y: 209 lines of code articles/gpt-oss/run-colab.ipynb x: 2 contributors (all time) y: 247 lines of code articles/gpt-oss/fine-tune-transfomers.ipynb x: 2 contributors (all time) y: 673 lines of code .github/scripts/check_notebooks.py x: 1 contributors (all time) y: 39 lines of code
3221.0
lines of code
  min: 39.0
  average: 964.5
  25th percentile: 218.5
  median: 584.5
  75th percentile: 1525.25
  max: 3221.0
0 113.0
contributors (all time)
min: 1.0 | average: 27.13 | 25th percentile: 1.0 | median: 2.0 | 75th percentile: 71.75 | max: 113.0

File Size vs. Commits (30 days): 2 points

registry.yaml x: 11 commits (30d) y: 3221 lines of code authors.yaml x: 4 commits (30d) y: 496 lines of code
3221.0
lines of code
  min: 496.0
  average: 1858.5
  25th percentile: 496.0
  median: 1858.5
  75th percentile: 3221.0
  max: 3221.0
0 11.0
commits (30d)
min: 4.0 | average: 7.5 | 25th percentile: 4.0 | median: 7.5 | 75th percentile: 11.0 | max: 11.0

File Size vs. Contributors (30 days): 2 points

registry.yaml x: 4 contributors (30d) y: 3221 lines of code authors.yaml x: 4 contributors (30d) y: 496 lines of code
3221.0
lines of code
  min: 496.0
  average: 1858.5
  25th percentile: 496.0
  median: 1858.5
  75th percentile: 3221.0
  max: 3221.0
0 4.0
contributors (30d)
min: 4.0 | average: 4.0 | 25th percentile: 4.0 | median: 4.0 | 75th percentile: 4.0 | max: 4.0

File Size vs. Commits (90 days): 2 points

registry.yaml x: 29 commits (90d) y: 3221 lines of code authors.yaml x: 12 commits (90d) y: 496 lines of code
3221.0
lines of code
  min: 496.0
  average: 1858.5
  25th percentile: 496.0
  median: 1858.5
  75th percentile: 3221.0
  max: 3221.0
0 29.0
commits (90d)
min: 12.0 | average: 20.5 | 25th percentile: 12.0 | median: 20.5 | 75th percentile: 29.0 | max: 29.0

File Size vs. Contributors (90 days): 2 points

registry.yaml x: 16 contributors (90d) y: 3221 lines of code authors.yaml x: 11 contributors (90d) y: 496 lines of code
3221.0
lines of code
  min: 496.0
  average: 1858.5
  25th percentile: 496.0
  median: 1858.5
  75th percentile: 3221.0
  max: 3221.0
0 16.0
contributors (90d)
min: 11.0 | average: 13.5 | 25th percentile: 11.0 | median: 13.5 | 75th percentile: 16.0 | max: 16.0