Introduction:
Hello, iron juice ~ I brushed such a short video on the subway today. I wonder if I can write a similar class roll call program. The idea can't stand waiting. Just write it~
1, Preparatory work
1.Tkinter
Tkinter is Python's built-in TK GUI tool set. TK is the native GUI Library of Tcl language. As a graphic design tool of python, the Tcl language environment it uses has been completely embedded in the Python interpreter.
We use Tkinter to develop the GUI interface.
2.PIL
PIL(Python Image Library) library is a third-party library of Python language, which needs to be installed through pip tool. The method of installing the PIL library is as follows. Note that the name of the installation library is pilot.
PIL library supports image storage, display and processing. It can process almost all image formats, and can complete the operations of image scaling, clipping, superposition, and adding lines, images and text to images.
Use image and imagetk in PIL to process and introduce a picture. You can use the following code to install it.
pip install pillow
2, Preview
1. Start
Double click to open it and enter the main interface of the software. All functions are clear at a glance. The program will automatically identify the names in the software directory Txt, import the name inside.
2. Start roll call - sequential roll call
After selecting the sequence roll call, click start, and the screen will begin to scroll. The probability of the appearance of the person name is the same. Click stop, the person name will stop scrolling, and the roll call is over.
3. Start roll call - random roll call
Click random roll call, the program will conduct random roll call, and the probability of the appearance of person name is random.
4. Manually load person list
You can manually select the person list, provided that the person list format is txt and each name occupies one line.
5. Start roll call sequence roll call Pyqt5 version
A version is also written with Pyqt5. The implementation logic is the same as the TK version. The interface may be better, but the file is much larger. You can get it yourself in the summary later. In addition, search for official account Java architect's technical background to answer "interview questions" and get a surprise gift package.
3, Train of thought
1. Overall realization idea
2. Roll call implementation ideas
4, Source code
point_names-GUI.py (main program GUI)
import random
import re
import time
import threading
from tkinter import *
from tkinter import ttk
from base64 import b64decode
from PIL import Image,ImageTk
from tkinter import messagebox
from tkinter.filedialog import askopenfilename
""""
2021-11-10 Roll call/Lottery procedure
Key highlights:
1.Two modes:
①Sequential roll call
②Random roll call
2.Automatic identification list
3.Manual import of person list is supported
4.Import verification of person list
5.Automatic correction of person name display position
6.Up to five large characters are displayed
"""
imgs=['./point_name.png']
class APP:
def __init__(self):
self.root = Tk()
self.running_flag=False #Start flag
self.time_span=0.05 #Name display interval
self.root.title('Point_name-V1.0')
width = 680
height = 350
left = (self.root.winfo_screenwidth() - width) / 2
top = (self.root.winfo_screenheight() - height) / 2
self.root.geometry("%dx%d+%d+%d" % (width, height, left, top))
self.root.resizable(0,0)
self.create_widget()
self.set_widget()
self.place_widget()
self.root.mainloop()
def create_widget(self):
self.label_show_name_var=StringVar()
self.label_show_name=ttk.Label(self.root,textvariable=self.label_show_name_var,font=('Arial', 100,"bold"),foreground = '#1E90FF')
self.btn_start=ttk.Button(self.root,text="start",)
self.btn_load_names=ttk.Button(self.root,text="Manually load person list",)
self.lf1=ttk.LabelFrame(self.root,text="Roll call method")
self.radioBtn_var=IntVar()
self.radioBtn_var.set(1)
self.radioBtn_sequence=ttk.Radiobutton(self.lf1,text="Sequential roll call",variable=self.radioBtn_var, value=1)
self.radioBtn_random=ttk.Radiobutton(self.lf1,text="Random roll call",variable=self.radioBtn_var, value=2)
self.label_show_name_num=ttk.Label(self.root,font=('Arial', 20),foreground = '#FF7F50')
paned = PanedWindow(self.root)
self.img = imgs
img_=b'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'
the_img = b64decode(img_)#Hard code pictures to GUI
paned.image = ImageTk.PhotoImage(data=the_img)
self._img = Label(self.root, image=paned.image,background='black')
def set_widget(self):
default_name_="Who could it be?"
self.label_show_name_var.set(default_name_)
self.label_show_name_adjust(default_name_)
self.btn_start.config(command=lambda :self.thread_it(self.start_point_name))
self.btn_load_names.config(command=self.load_names)
init_names=self.load_names_txt("./names.txt")
self.root.protocol('WM_DELETE_WINDOW',self.quit_window)
self.root.bind('<Escape>',self.quit_window)
if init_names:
self.default_names=init_names #1. The file exists but has no content. 2. The file does not exist
self.label_show_name_num.config(text=f"A total of{len(self.default_names)}Names")
else:
self.btn_start.config(state=DISABLED)
self.label_show_name_num.config(text=f"Please import the person list manually first!")
def place_widget(self):
self.lf1.place(x=300,y=160,width=250,height=50)
self.radioBtn_sequence.place(x=20,y=0)
self.radioBtn_random.place(x=150,y=0)
self.btn_start.place(x=300,y=220,width=100,height=30)
self.btn_load_names.place(x=450,y=220,width=100,height=30)
self._img.place(x=90, y=165, height=120, width=180)
self.label_show_name_num.place(x=300,y=260)
def label_show_name_adjust(self,the_name):
if len (the_name)==1:
self.label_show_name.place(x=280, y=10)
elif len(the_name) == 2:
self.label_show_name.place(x=180, y=10)
elif len(the_name) == 3:
self.label_show_name.place(x=120, y=10)
elif len(the_name) == 4:
self.label_show_name.place(x=80, y=10)
else:
self.label_show_name.place(x=0, y=10)
def start_point_name(self):
"""
Judge before startup to obtain roll call mode
:return:
"""
if len(self.default_names)==1:
messagebox.showinfo("Tips",'There's only one person on the list. Don't choose!')
self.label_show_name_var.set(self.default_names[0])
self.label_show_name_adjust(self.default_names[0])
return
if self.btn_start["text"]=="start":
self.btn_load_names.config(state=DISABLED)
self.running_flag=True
if isinstance(self.default_names,list):
self.btn_start.config(text="Just you")
if self.radioBtn_var.get()==1:
mode="sequence"
elif self.radioBtn_var.get()==2:
mode="random"
else:
pass
self.thread_it(self.point_name_begin(mode))
else:
messagebox.showwarning("warning","Please import the person list first!")
else:
self.running_flag=False
self.btn_load_names.config(state=NORMAL)
self.btn_start.config(text="start")
def point_name_begin(self,mode):
"""
Start roll call, roll call main function
:param mode:
:return:
"""
if mode == "sequence":
if self.running_flag:
self.always_ergodic()
elif mode=="random":
while True:
if self.running_flag:
random_choice_name=random.choice(self.default_names)
self.label_show_name_var.set(random_choice_name)
self.label_show_name_adjust(random_choice_name)
time.sleep(self.time_span)
else:
break
def always_ergodic(self):
"""
Keep walking through this list,Using an endless loop can cause thread blocking
:return:
"""
for i in self.default_names:
if self.running_flag:
self.label_show_name_var.set(i)
self.label_show_name_adjust(i)
time.sleep(self.time_span)
if i==self.default_names[-1]:
self.always_ergodic()
else:
break
def load_names(self):
"""
Manual loading txt List of formers
:return:
"""
filename = askopenfilename(
filetypes = [('text file', '.TXT'), ],
title = "Select a text file",
initialdir="./"
)
if filename:
names=self.load_names_txt(filename)
if names:
self.default_names=names
no_Chinese_name_num=len([n for n in names if not self.load_name_check(n)])
if no_Chinese_name_num==0:
pass
else:
messagebox.showwarning("Please note that",f'Import list has{no_Chinese_name_num}It's not a Chinese name')
self.label_show_name_num.config(text=f"A total of{len(self.default_names)}Names")
default_name_ = "Who could it be?"
self.label_show_name_var.set(default_name_)
self.label_show_name_adjust(default_name_)
self.btn_start.config(state=NORMAL)
else:
messagebox.showwarning("warning","Import failed, please check!")
def load_names_txt(self,txt_file):
"""
read txt List of people in format
:param txt_file:
:return:
"""
try:
with open(txt_file,'r',encoding="utf-8")as f:
names=[name.strip() for name in f.readlines()]
if len(names)==0:
return False
else:
return names
except:
return False
def load_name_check(self,name):
"""
yes txt Verify the person name in the text
Chinese characters->True
Non Chinese characters->False
:param name:
:return:
"""
regex = r'[\u4e00-\u9fa5]+'
if re.match(regex,name):
return True
else:
return False
def thread_it(self,func,*args):
t=threading.Thread(target=func,args=args)
t.setDaemon(True)
t.start()
def quit_window(self,*args):
"""
Program exit triggers this function
:param args:
:return:
"""
ret=messagebox.askyesno('sign out','Are you sure you want to exit?')
if ret:
self.root.destroy()
if __name__ == '__main__':
a=APP()5, Summary
Tkinter has developed a roll call program for class this time. This program can be used for roll call and lucky draw... The code is less than 200 lines. The program is simple and practical. It mainly has the following six highlights:
1. Two modes: sequential roll call and random roll call
2. Automatic identification list
3. Support manual import of person list
4. Import verification of person list
5. Automatic correction of person name display position
6. Display up to five large characters
end
This issue is shared here ~ I hope it will be helpful to you! If you like, remember three times in a row!! The support of family members is the biggest driving force for Xiaobian to update 💪💪