import...
这几乎是我们写python代码时必备的开头。但实际上很多时候是重复性的工作，比如数据分析时我们会：
import pandas as pd
import sklearn
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
...
1. 解决之道
那么，有没有一种方法能够免除这些重复性的工作呢？有的！那就是pyforest库。你只需要打开Anaconda Prompt，输入以下代码：
pip install pyforest
这时，你只需要使用
from pyforest import *
就可以导入所有的库了！
2. IPython 自启动
如果你使用的是IPython，例如Jupyter Notebook 或者是 Spyder，你甚至可以直接使用，而不需要大部分的import——pyforest会把它添加到IPython的自动启动中去。
3. 哪些库支持自动导入？
找到你的库安装的位置，例如我的是：D:\Softwares\Anaconda\Lib\site-packages\pyforest,并且打开_imports.py，你就可以看到默认被导入的库了。
以下是一些示例，完整版贴在文末附录：
pd = LazyImport("import pandas as pd")
np = LazyImport("import numpy as np")
dd = LazyImport("from dask import dataframe as dd")
SparkContext = LazyImport("from pyspark import SparkContext")
load_workbook = LazyImport("from openpyxl import load_workbook")
wr = LazyImport("import awswrangler as wr")
4. 个性化编辑
如果你希望一些库能够被自动导入，你可以找到pyforest库中的user_imports.py文件，来进行个性化的编辑。对于我而言，这个文件位于C:\Users\Sphaera\.pyforest\user_imports.py
# Add your imports here, line by line
# e.g
# import pandas as pd
# from pathlib import Path
# import re
5. 其他功能
导出所有的import语句。
active_imports()
例如你只使用了pandas这个库，他就会输出
['import pandas as pd']
6. 附录
6.1 _import.py的所有内容
from ._importable import LazyImport, _get_import_statements
from .user_specific_imports import _load_user_specific_imports
# If you are missing an import and you think it is a common import, please contribute
# via creating a pull request.
# If you contribute, we can quickly collect the 80% most frequent imports
# Before you create a pull request, PLEASE READ THE FOLLOWING:
# 0) It is always best to first create a GitHub issue before creating a pull request.
# This way you can be sure that your proposal is valid and will be integrated.
# 1) The imported name should be an unambiguous standard convention and highly specific.
# Usually, you want to use the names that are proposed in the library's documentation.
# However, there should be no or little confusion with other libraries
# Good example:
# 'import pandas as pd'
# Bad example:
# 'import dash_html_components as html'
# because 'html' is not specific enough for the dash context.
# Also, it is ambiguous with e.g. IPython.display.HTML.
# A potential resolution might be 'import dash_html_components as dhc'
# 2) General, implicit imports e.g. 'from sklearn.preprocessing import *' are not possible
# because we want to make sure that there is no accidental masking of imported names
# 3) If you disagree with the conventions or you are using rare packages, you can save
# your user-specific imports in ~/.pyforest/user_imports.py
### Data Wrangling
pd = LazyImport("import pandas as pd")
np = LazyImport("import numpy as np")
dd = LazyImport("from dask import dataframe as dd")
SparkContext = LazyImport("from pyspark import SparkContext")
load_workbook = LazyImport("from openpyxl import load_workbook")
wr = LazyImport("import awswrangler as wr")
### Data Visualization and Plotting
mpl = LazyImport("import matplotlib as mpl")
plt = LazyImport("import matplotlib.pyplot as plt")
sns = LazyImport("import seaborn as sns")
py = LazyImport("import plotly as py")
go = LazyImport("import plotly.graph_objs as go")
px = LazyImport("import plotly.express as px")
dash = LazyImport("import dash")
bokeh = LazyImport("import bokeh")
alt = LazyImport("import altair as alt")
pydot = LazyImport("import pydot")
# statistics
statistics = LazyImport("import statistics")
### Machine Learning
sklearn = LazyImport("import sklearn")
OneHotEncoder = LazyImport("from sklearn.preprocessing import OneHotEncoder")
TSNE = LazyImport("from sklearn.manifold import TSNE")
train_test_split = LazyImport("from sklearn.model_selection import train_test_split")
svm = LazyImport("from sklearn import svm")
GradientBoostingClassifier = LazyImport(
"from sklearn.ensemble import GradientBoostingClassifier"
)
GradientBoostingRegressor = LazyImport(
"from sklearn.ensemble import GradientBoostingRegressor"
)
RandomForestClassifier = LazyImport(
"from sklearn.ensemble import RandomForestClassifier"
)
RandomForestRegressor = LazyImport("from sklearn.ensemble import RandomForestRegressor")
TfidfVectorizer = LazyImport(
"from sklearn.feature_extraction.text import TfidfVectorizer"
)
# Gradient Boosting Decision Tree
xgb = LazyImport("import xgboost as xgb")
lgb = LazyImport("import lightgbm as lgb")
# TODO: add all the other most important sklearn objects
# TODO: add separate sections within machine learning viz. Classification, Regression, Error Functions, Clustering
# Deep Learning
tf = LazyImport("import tensorflow as tf")
keras = LazyImport("import keras")
# NLP
nltk = LazyImport("import nltk")
gensim = LazyImport("import gensim")
spacy = LazyImport("import spacy")
re = LazyImport("import re")
### Helper
sys = LazyImport("import sys")
os = LazyImport("import os")
re = LazyImport("import re")
glob = LazyImport("import glob")
Path = LazyImport("from pathlib import Path")
pickle = LazyImport("import pickle")
dt = LazyImport("import datetime as dt")
tqdm = LazyImport("import tqdm")
##################################################
### dont make adjustments below this line ########
##################################################
#############################
### User-specific imports ###
#############################
# You can save your own imports in ~/.pyforest/user_imports.py
# Please note: imports in ~/.pyforest/user_imports.py take precedence over the
# imports above.
_load_user_specific_imports(globals())
# don't want to blow up the namespace
del _load_user_specific_imports
# #######################################
# ### Complementary, optional imports ###
# #######################################
# # Why is this needed? Some libraries patch existing libraries
# # Please note: these imports are only executed if you already have the library installed
# # If you want to deactivate specific complementary imports, do the following:
# # - uncomment the lines which contain `.__on_import__` and the library you want to deactivate
# pandas_profiling = LazyImport("import pandas_profiling")
# pd.__on_import__(pandas_profiling) # adds df.profile_report attribute to pd.DataFrame
# bam = LazyImport("import bamboolib as bam")
# pd.__on_import__(bam) # adds GUI to pd.DataFrame when IPython frontend can display it
def lazy_imports():
return _get_import_statements(globals(), was_imported=False)
def active_imports(print_statements=True):
statements = _get_import_statements(globals(), was_imported=True)
if print_statements:
print("\n".join(statements))
return statements
