大家好，我是讯享网，很高兴认识大家。

我不确定是否有人问过这个问题-到目前为止还没有找到一个好的实践。在

我有两个python文件，它们具有完全相同的包导入，以及许多不同的方法。一些变量只是变化的，其他变量是相同的。在

如果我需要对一个文件进行更改，我必须转到另一个文件来应用相同的更改，这似乎不是一个可靠的方法。在

我真的想把这些文件分开(放在两个文件中)。我对class这个概念一直没有很好的理解。如果我需要在第一个文件中生成一个class，并在第二个文件中调用它，那么如果需要，我可以覆盖这些变量？在

这是我的第一个文件的样子，抱歉，我应该花一些时间让它可读，但它只是给你一个关于结构的想法。这段代码实际上绘制了许多matplotlib图形。第二个文件将有不同的输入文件(CSV文件)，然后绘制出不同的图形。在import csv

import datetime

import pylab

import sys

import time

from inspect import getsourcefile

from os.path import abspath

import matplotlib.dates as mdates

import matplotlib.pyplot as plt

import numpy as np

from matplotlib import style

from matplotlib.backends.backend_pdf import PdfPages

def get_mul_list(*args):

return map(list, zip(*args))

def str2float(s):

if not s == '':

s = (float(s))

else:

s = np.nan

return s

def clean_nans(x, y, num_nan_gap=24):

x_clean, y_clean = [], []

cnt = 0

for _x, _y in zip(x, y):

if np.isnan(_y):

cnt += 1

if cnt == num_nan_gap:

# on the 5th nan, put it in the list to break line

x_clean.append(_x)

y_clean.append(_y)

continue

cnt = 0

x_clean.append(_x)

y_clean.append(_y)

return x_clean, y_clean

def csv_store_in_dict(filepath, mode):

csv_data = open(filepath, mode)

data = list(csv.reader(csv_data))

csv_imported_in_dict = dict(zip(data[0], get_mul_list(*data[1:])))

return csv_imported_in_dict

colors_list = ['deeppink', 'aquamarine', 'yellowgreen', 'orangered', 'darkviolet',

'darkolivegreen', 'lightskyblue', 'teal', 'seagreen', 'olivedrab', 'red', 'indigo', 'goldenrod', 'firebrick',

'slategray', 'cornflowerblue', 'darksalmon', 'blue', 'khaki', 'wheat', 'dodgerblue', 'moccasin', 'sienna',

'darkcyan']

current_py_filepath = abspath(getsourcefile(lambda: 0)) # python source file path for figure footnote

kkk_dict = csv_store_in_dict('CSV/qry_WatLvl_kkk_xlsTS_1c_v4.csv', 'r') # all WL kkk data stored in a dictionary

yyyddd_dict = csv_store_in_dict('CSV/qry_WatLvl_TimeSeries2_v2.csv', 'r') # all WL kkk data stored in a dictionary

XX_info_dict = csv_store_in_dict('CSV/XX_info.csv', 'r') # XX_name, XX_group_name, BB_Main, CC, dddd

XX_groups_chartE = ('XXH_05',

'XXH_16',

'XXH_11',

'DXX_27',

'DXX_22',

'DXX_21',

'DXX_09',

'DXX_07',

'DXX_01',

'DXX_05',)

y_range = [[5,10], # chart 1

[7,12], # chart 2

[3,8], # chart 3

讯享网

[7,12], # chart 4

[5,10], # chart 5

[20,50], # chart 6

[12,22], # chart 7

[5,25], # chart 8

[10,15], # chart 9

[22,42]] # chart 10

# Date conversion

x_kkk_date = []

x_yyy_date = []

x_kkk = kkk_dict["DateTime"]

x_yyyddd = yyyddd_dict["DateTime"]

for i in x_kkk:

x_kkk_date.append(datetime.datetime.strptime(i, "%d/%m/%Y %H:%M:%S"))

for i in x_yyyddd:

x_yyy_date.append(datetime.datetime.strptime(i, "%d/%m/%Y %H:%M:%S"))

# plotting XX groups

XXs_curr_grp = []

chart_num = 1

for XX_gr_nam in XX_groups_chartE:

for count, elem in enumerate(XX_info_dict['XX_group_name']):

if elem == XX_gr_nam:

XXs_curr_grp.append(XX_info_dict['XX_name'][count])

fig = plt.figure(figsize=(14, 11))

col_ind = 0

for XX_v in XXs_curr_grp:

y_kkk = kkk_dict[XX_v]

y_yyyddd = yyyddd_dict[XX_v]

y_kkk_num = [str2float(i) for i in y_kkk]

y_yyyddd_num = [str2float(i) for i in y_yyyddd]

ind_XX = XX_info_dict["XX_name"].index(XX_v)

BB_Main = XX_info_dict["BB_Main"][ind_XX]

CC = XX_info_dict["CC"][ind_XX]

dddd = XX_info_dict["dddd"][ind_XX]

def label_pl(d_type):

label_dis = "%s (%s, %s / %s)" % (XX_v, BB_Main, CC, d_type)

return label_dis

x_kkk_date_nan_cln, y_kkk_num_nan_cln = clean_nans(x_kkk_date, y_kkk_num, 200)

plt.plot_date(x_kkk_date_nan_cln, y_kkk_num_nan_cln, '-', markeredgewidth=0,

label=label_pl("kkk data"), color=colors_list[col_ind]) # c = col_rand

plt.scatter(x_yyy_date, y_yyyddd_num, label=label_pl("yyy ddds"), marker='x', linewidths=2,

s=50, color=colors_list[col_ind])

col_ind += 1

XX_grp_title = XX_gr_nam.replace("_", "-")

plt.title("kkk Levels \n" + XX_grp_title + " Group", fontsize=20)

plt.ylabel('wwL (mmm)')

plt.legend(loc=9, ncol=2, prop={'size': 8})

plt.figtext(0.05, 0.05, current_py_filepath, horizontalalignment='left', fontsize=8) # footnote for file path

plt.figtext(0.95, 0.05, 'Chart E%s' % (chart_num,), horizontalalignment='right', fontsize=12) # chart number

plt.figtext(0.95, 0.95, datetime.date.today(), horizontalalignment='right', fontsize=8)

# FIGURE FORMATTING

myFmt = mdates.DateFormatter('%d/%m/%Y')

ax = plt.gca()

ax.xaxis.set_major_formatter(myFmt)

plt.gcf().autofmt_xdate()

ax.set_ylim(y_range[chart_num-1])

plt.grid()

fig.tight_layout()

plt.subplots_adjust(left=0.05, right=0.95, top=0.9, bottom=0.15)

fig_pdf_file = "PDF/OXX_grp_page %s.pdf" % (chart_num,)

fig.savefig(fig_pdf_file)

XXs_curr_grp = []

chart_num += 1 # assumed charts numbering is the same as the order of plotting

plt.show()