本篇文章給大家分享的內容是python3將python程式碼打包成exe檔的方法,有需要的朋友可以參考一下
基本配置:
# #Anaconda 3 4.2.0(python3.5)注意:
1、程式碼存放至全英文目錄下;2、電腦管家之類的安全軟體暫時關閉(因為發佈出來的exe文件屬於可執行文件,電腦管家可能會認為發佈出來的文件為病毒,自動刪除)具體操作步驟如下:
1、寫好的python程式碼,存放至全英文的目錄下:import keras from keras.models import Sequential import numpy as np import pandas as pd from keras.layers import Dense import random import matplotlib.pyplot as plt from tensorflow.examples.tutorials.mnist import input_data from tkinter import filedialog import tkinter.messagebox #这个是消息框,对话框的关键 file_path = filedialog.askdirectory() mnist = input_data.read_data_sets(file_path, validation_size=0) #随机挑选其中一个手写数字并画图 num = random.randint(1, len(mnist.train.images)) img = mnist.train.images[num] plt.imshow(img.reshape((28, 28)), cmap='Greys_r') plt.show() x_train = mnist.train.images y_train = mnist.train.labels x_test = mnist.test.images y_test = mnist.test.labels #reshaping the x_train, y_train, x_test and y_test to conform to MLP input and output dimensions x_train = np.reshape(x_train, (x_train.shape[0], -1)) x_test = np.reshape(x_test, (x_test.shape[0], -1)) y_train = pd.get_dummies(y_train) y_test = pd.get_dummies(y_test) #performing one-hot encoding on target variables for train and test y_train=np.array(y_train) y_test=np.array(y_test) #defining model with one input layer[784 neurons], 1 hidden layer[784 neurons] with dropout rate 0.4 and 1 output layer [10 #neurons] model=Sequential() model.add(Dense(784, input_dim=784, activation='relu')) keras.layers.core.Dropout(rate=0.4) model.add(Dense(10,input_dim=784,activation='softmax')) # compiling model using adam optimiser and accuracy as metric model.compile(loss='categorical_crossentropy', optimizer="adam", metrics=['accuracy']) # fitting model and performing validation model.fit(x_train, y_train, epochs=20, batch_size=200, validation_data=(x_test, y_test)) y_test1 = pd.DataFrame(model.predict(x_test, batch_size=200)) y_pre = y_test1.idxmax(axis = 1) result = pd.DataFrame({'test': y_test, 'pre': y_pre}) tkinter.messagebox.showinfo('Message', 'Completed!')2、透過命令列,依照pyinstallerpip install pyinstaller3、命令列打包檔案
先切換路徑至python程式碼所在目錄,執行語句:#pyinstaller -F -w xxx.py4、
等待打包完成,會產生一個build資料夾和一個dist資料夾,exe可執行檔就在dist資料夾裡,如果程式引用有資源,則要把資源檔案放在這個exe正確的相對目錄下。
5、執行exe檔。
有時執行檔會出錯,此時需要拷貝下圖所示的資料夾到exe檔所在目錄
運行成功!
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