Python开发常用工具库

Python

https://www.python.org/doc/

《Python编程：从入门到实践》速查表

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VS Code

https://code.visualstudio.com/docs#vscode

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matplotlib（画图工具）

https://matplotlib.org/contents.html

Top 50 matplotlib Visualizations – The Master Plots (with full python code)

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numpy

https://numpy.org/devdocs/

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pytorch

英文文档：https://pytorch.org/docs/stable/index.html

中文文档：https://pytorch-cn.readthedocs.io/zh/latest/package_references/torch/

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scikit-image

https://scikit-image.org/docs/stable/

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pickle

https://docs.python.org/3.5/library/pickle.html

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easydict（字典解析库）

https://pypi.org/project/easydict/1.2/

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os（操作系统接口模块）

https://docs.python.org/3/library/os.html?highlight=os#module-os

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sys

https://docs.python.org/3/library/sys.html?highlight=sys#module-sys

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argparse（解析命令行）

https://docs.python.org/3/library/argparse.html?highlight=argparse#module-argparse

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fire(命令行生成工具)

https://github.com/google/python-fire/blob/master/docs/guide.md

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logging（日志）

https://docs.python.org/3.6/howto/logging.html

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tensorboardX（网络可视化）

https://tensorboardx.readthedocs.io/en/latest/tutorial.html

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tqdm（进度条工具）

https://pypi.org/project/tqdm/

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glob(文件搜索库)

https://docs.python.org/3/library/glob.html?highlight=glob#module-glob

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re（正则化）

https://docs.python.org/3/library/re.html

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io

https://docs.python.org/3/library/io.html?highlight=io#module-io

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time

https://docs.python.org/3/library/time.html?highlight=time#module-time

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datitime

https://docs.python.org/3/library/datetime.html?highlight=datetime#module-datetime

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numba(Python加速库)

http://numba.pydata.org/

import numpy as np
import numba
from numba import jit

print(numba.__version__)

@jit(nopython=True)
'''
The nopython=True option requires that the function be fully compiled  

'''
def go_fast(a): # Function is compiled to machine code when called the first time
    trace = 0
    # assuming square input matrix
    for i in range(a.shape[0]):   # Numba likes loops
        trace += np.tanh(a[i, i]) # Numba likes NumPy functions
    return a + trace              # Numba likes NumPy broadcasting

x = np.arange(100).reshape(10, 10)
go_fast(x)

go_fast(2*x)

%timeit go_fast(x)

np.testing.assert_array_equal(go_fast(x), go_fast.py_func(x))

%timeit go_fast.py_func(x)

def go_numpy(a):
    return a + np.tanh(np.diagonal(a)).sum()

np.testing.assert_array_equal(go_numpy(x), go_fast(x))

%timeit go_numpy(x)