Datasets:
Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,115 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
task_categories:
|
3 |
+
- summarization
|
4 |
+
- text2text-generation
|
5 |
+
language:
|
6 |
+
- en
|
7 |
+
tags:
|
8 |
+
- code
|
9 |
+
size_categories:
|
10 |
+
- 10K<n<100K
|
11 |
+
---
|
12 |
+
|
13 |
+
# Overview
|
14 |
+
|
15 |
+
This dataset contains Python code-docstring pairs, whereas the docstrings are in Google style. A Google style docstring is structured as follows:
|
16 |
+
```
|
17 |
+
<Description of the code>
|
18 |
+
|
19 |
+
Args:
|
20 |
+
<var1> (<data-type>) : <description of var1>
|
21 |
+
<var2> (<data_type>) : <description of var2>
|
22 |
+
|
23 |
+
Returns:
|
24 |
+
<var3> (<data-type>) : <description of var3>
|
25 |
+
|
26 |
+
Raises:
|
27 |
+
<var4> (<data-type>) : <description of var4>
|
28 |
+
```
|
29 |
+
|
30 |
+
The format varies widely (like additional sections such as Examples, Notes, etc) but generally speaking, it should contain an Args/Parameters and Returns section.
|
31 |
+
|
32 |
+
# Source
|
33 |
+
|
34 |
+
The dataset was gathered from 3 different sources:
|
35 |
+
|
36 |
+
## CodeSearchNet
|
37 |
+
|
38 |
+
From their Python split of ~250k samples, ~23k samples was extracted. A less than 10% sample retention, most samples from CodeSearchNet contained informal docstrings that
|
39 |
+
only contained descriptions and no sections.
|
40 |
+
|
41 |
+
## Repositories Under Google's GitHub Organization Page
|
42 |
+
|
43 |
+
You can find the specified page here [here](https://github.com/search?q=topic%3Apython+org%3Agoogle+fork%3Atrue&type=repositories). These repos are dictated by the list:
|
44 |
+
|
45 |
+
```
|
46 |
+
repos = [
|
47 |
+
"https://github.com/google/python-fire",
|
48 |
+
"https://github.com/google/yapf",
|
49 |
+
"https://github.com/google/pytype",
|
50 |
+
"https://github.com/google/tf-quant-finance",
|
51 |
+
"https://github.com/google/budoux",
|
52 |
+
"https://github.com/google/mobly",
|
53 |
+
"https://github.com/google/temporian",
|
54 |
+
"https://github.com/google/pyglove",
|
55 |
+
"https://github.com/google/subpar",
|
56 |
+
"https://github.com/google/weather-tools",
|
57 |
+
"https://github.com/google/ci_edit",
|
58 |
+
"https://github.com/google/etils",
|
59 |
+
"https://github.com/google/pcbdl",
|
60 |
+
"https://github.com/google/starthinker",
|
61 |
+
"https://github.com/google/pytruth",
|
62 |
+
"https://github.com/google/nsscache",
|
63 |
+
"https://github.com/google/megalista",
|
64 |
+
"https://github.com/google/fhir-py",
|
65 |
+
"https://github.com/google/chatbase-python",
|
66 |
+
"https://github.com/tensorflow/tensorflow",
|
67 |
+
"https://github.com/google/project-OCEAN",
|
68 |
+
"https://github.com/google/qhbm-library",
|
69 |
+
"https://github.com/google/data-quality-monitor",
|
70 |
+
"https://github.com/google/genai-processors",
|
71 |
+
"https://github.com/google/python-proto-converter",
|
72 |
+
"https://github.com/google/sprockets",
|
73 |
+
"https://github.com/keras-team/keras",
|
74 |
+
"https://github.com/scikit-learn/scikit-learn",
|
75 |
+
"https://github.com/apache/beam",
|
76 |
+
"https://github.com/huggingface/transformers"
|
77 |
+
]
|
78 |
+
```
|
79 |
+
|
80 |
+
A total of ~11k samples was gathered from this source.
|
81 |
+
|
82 |
+
## Juraj's Python Google-style Docstrings Dataset
|
83 |
+
|
84 |
+
I found this dataset here and is made my user Juraj-juraj. You can find the dataset [here](https://huggingface.co/datasets/juraj-juraj/python_googlestyle_docstrings).
|
85 |
+
A total of ~25k samples was gathered from this source, after further preprocessing.
|
86 |
+
|
87 |
+
# Preprocessing Steps
|
88 |
+
|
89 |
+
The following cleaning, normalizing and preprocessing steps were performed:
|
90 |
+
|
91 |
+
1. Removed duplicates based on both code and docstring
|
92 |
+
2. Remove samples with empty code and docstrings
|
93 |
+
3. Remove samples with extremely short entries (<20 chars)
|
94 |
+
4. Remove samples with extremely long entries (>5000 chars)
|
95 |
+
5. Removed comments and docstring from the code
|
96 |
+
6. Removed samples where docstring isn't in English (using langdetect)
|
97 |
+
7. Removed samples where docstring contained special characters like html tags or URLS
|
98 |
+
8. Using CodeT5+ tokenizer, removed samples where docstring tokens are < 12 or > 256
|
99 |
+
9. Normalized all docstring entries by removing any indentions
|
100 |
+
|
101 |
+
# Data Structure
|
102 |
+
|
103 |
+
The data structure of the dataset is as follows:
|
104 |
+
|
105 |
+
```
|
106 |
+
<code> : <The code, removed of docstrings and comments>,
|
107 |
+
<docstring> : <The corresponding docstring of the code>,
|
108 |
+
<source> : <The source which the code came from>
|
109 |
+
```
|
110 |
+
|
111 |
+
The sources are:
|
112 |
+
|
113 |
+
**CodeSearcNet** - from the CodeSearchNet dataset
|
114 |
+
**github-repos** - from the repositories under Google's Organization GitHub page
|
115 |
+
**juraj-google-style** - from Juraj's Python Google-style docstring dataset
|