You can easily add numpy.ndarray.shape information to your script as comments.
Project description
Shape Commentator
About
You can easily add numpy.ndarray.shape, torch.Size, other shape and type information at runtime to your script code as comments.
NumPyやPyTorchなどの配列のshape属性や,変数の型の実行時の情報を,スクリプトにコメントとして貼り付けるツールです.
Install
pip install -U shape_commentator
-U means upgrading.
Usage
This tool has two types of usage.
このツールには2つの使い方があります.
Usage 1. Execute this as a Module
Create Commented Script
- Run this script as a module with argument of script name. Command line arguments to the target script are available.
Pythonのモジュールとしてshape_commentatorを実行してください.引数は,スクリプト名の後にスクリプトに渡したい引数を続けることもできます.
python -m shape_commentator src.py
python -m shape_commentator src.py arg1 arg2 arg3
- You get the commented script. For example, you execute shape_commentator to
src.py
, you getsrc.py.commented.py
.
src.py
というスクリプトに対して実行すると,src.py.commented.py
が生成されます.
src.py
import numpy as np
a = np.array([1,2,3,4,5,6])
b = np.array([0,1,2,3,4,5])
ab_h = np.hstack((a,b))
ab_v = np.vstack((a,b))
ab = np.dot(a,b)
AA, BB = np.meshgrid(a,b)
i = 1
f = 1.0
c = 1 + 1j
s = "string1"
class A():
pass
a = A()
src.py.commented.py
import numpy as np
a = np.array([1,2,3,4,5,6]) #_ (6,)
b = np.array([0,1,2,3,4,5]) #_ (6,)
ab_h = np.hstack((a,b)) #_ (12,)
ab_v = np.vstack((a,b)) #_ (2, 6)
ab = np.dot(a,b) #_ ()
AA, BB = np.meshgrid(a,b) #_ [(6, 6),(6, 6),]
i = 1 #_ int
f = 1.0 #_ float
c = 1 + 1j #_ complex
s = "string1" #_ str
class A():
pass
a = A() #_ A
Usage 2. IPython / Jupyter Notebook (Magic Command)
To use IPython / Jupyter Notebook magic command,
IPythonやJupyter Notebookでのマジックコマンドの使い方
import shape_commentator
Create Commented Script
コメントを付ける
%%shape
a = np.array([1,2,3,4,5,6])
output
a = np.array([1,2,3,4,5,6]) #_ (6,)
Delete Comments
コメントを消す
%%shape -d
a = np.array([1,2,3,4,5,6]) #_ (6,)
output
a = np.array([1,2,3,4,5,6])
Tested Python Version
Test scripts are written in these version of Python.
以下のバージョンがテストされています.
- 3.11.3
- 3.10.11
- 3.9.16
- 3.8.16
- 3.7.16
- 3.6.15
- 3.5.10
- 2.7.17
Blog
作った経緯などを書いた解説ブログはこちらにあります.
NumPyやPyTorchで使える超便利ツールを作った
Project details
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