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open file python

In this short tutorial you will learn how to create a file dialog and load its file contents. The file dialog is needed in many applications that use file access.

Related course:

File Dialog Example
To get a filename (not file data) in PyQT you can use the line:

filename = QFileDialog.getOpenFileName(w, 'Open File', '/')

If you are on Microsoft Windows use

filename = QFileDialog.getOpenFileName(w, 'Open File', 'C:\')

An example below (includes loading file data):

#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
import sys
from PyQt4.QtGui import *

# Create an PyQT4 application object.
a = QApplication(sys.argv)

# The QWidget widget is the base class of all user interface objects in PyQt4.
w = QWidget()

# Set window size.
w.resize(320, 240)

# Set window title
w.setWindowTitle("Hello World!")

# Get filename using QFileDialog
filename = QFileDialog.getOpenFileName(w, 'Open File', '/')
print(filename)

# print file contents
with open(filename, 'r') as f:
    print(f.read())

# Show window
w.show()

sys.exit(a.exec_())

Result (output may vary depending on your operating system):

pyqt_file_open PyQt File Open Dialog.

Download PyQT Code (Bulk Collection)

progressbar python

python browser

snake ai

In this article we will show you how to create basic game AI (Artificial Intelligence). This article will describe an AI for the game snake.


In this game (snake) both the computer and you play a snake, and the computer snake tries to catch you. In short: the opponent AI tries to determine and go to the destination point based on your location on the board.

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Adding the computer player:
We extend the code with a new class called Computer which will be our computer player. This contains routines to draw and move the computer snake.

class Computer:
    x = [0]
    y = [0]
    step = 44
    direction = 0
    length = 3
 
    updateCountMax = 2
    updateCount = 0

    def __init__(self, length):
       self.length = length
       for i in range(0,2000):
           self.x.append(-100)
           self.y.append(-100)

       # initial positions, no collision.
       self.x[0] = 1*44
       self.y[0] = 4*44

    def update(self):

        self.updateCount = self.updateCount + 1
        if self.updateCount > self.updateCountMax:

            # update previous positions
            for i in range(self.length-1,0,-1):
                self.x[i] = self.x[i-1]
                self.y[i] = self.y[i-1]

            # update position of head of snake
            if self.direction == 0:
                self.x[0] = self.x[0] + self.step
            if self.direction == 1:
                self.x[0] = self.x[0] - self.step
            if self.direction == 2:
                self.y[0] = self.y[0] - self.step
            if self.direction == 3:
                self.y[0] = self.y[0] + self.step

            self.updateCount = 0


    def moveRight(self):
        self.direction = 0

    def moveLeft(self):
        self.direction = 1

    def moveUp(self):
        self.direction = 2

    def moveDown(self):
        self.direction = 3 

    def draw(self, surface, image):
        for i in range(0,self.length):
            surface.blit(image,(self.x[i],self.y[i]))

We then call the update and drawing method of the computer.

    def on_loop(self):
        self.player.update()
        self.computer.update()

....
    
    def on_render(self):
        self._display_surf.fill((0,0,0))
        self.player.draw(self._display_surf, self._image_surf)
        self.apple.draw(self._display_surf, self._apple_surf)
        self.computer.draw(self._display_surf, self._image_surf)
        pygame.display.flip()

This will make the computer snake move and be drawn on the screen. It has the same properties as the human player.

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Adding the intelligence to the computer player
Because this is a simple game, we do not need to create a complete thinking machine inside the game. We simply need some basic intelligence exhibited by our computer player. Intelligence in games is often quite limited because most of the time more complexity is not neccesary or there simply is not the time available to implement clever algorithms.

The algorithm we will add will simply go to the destination. It will neglect any obstacles (the human player).

def target(self,dx,dy):
    if self.x[0] > dx:
        self.moveLeft()

    if self.x[0] < dx:
        self.moveRight()

    if self.x[0] == dx:
        if self.y[0] < dy:
            self.moveDown()

        if self.y[0] > dy:
            self.moveUp()

Complete code
We end up with this complete code:

from pygame.locals import *
from random import randint
import pygame
import time

class Apple:
    x = 0
    y = 0
    step = 44

    def __init__(self,x,y):
        self.x = x * self.step
        self.y = y * self.step

    def draw(self, surface, image):
        surface.blit(image,(self.x, self.y)) 


class Player:
    x = [0]
    y = [0]
    step = 44
    direction = 0
    length = 3
 
    updateCountMax = 2
    updateCount = 0

    def __init__(self, length):
       self.length = length
       for i in range(0,2000):
           self.x.append(-100)
           self.y.append(-100)

       # initial positions, no collision.
       self.x[0] = 1*44
       self.x[0] = 2*44

    def update(self):

        self.updateCount = self.updateCount + 1
        if self.updateCount > self.updateCountMax:

            # update previous positions
            for i in range(self.length-1,0,-1):
                self.x[i] = self.x[i-1]
                self.y[i] = self.y[i-1]

            # update position of head of snake
            if self.direction == 0:
                self.x[0] = self.x[0] + self.step
            if self.direction == 1:
                self.x[0] = self.x[0] - self.step
            if self.direction == 2:
                self.y[0] = self.y[0] - self.step
            if self.direction == 3:
                self.y[0] = self.y[0] + self.step

            self.updateCount = 0


    def moveRight(self):
        self.direction = 0

    def moveLeft(self):
        self.direction = 1

    def moveUp(self):
        self.direction = 2

    def moveDown(self):
        self.direction = 3 

    def draw(self, surface, image):
        for i in range(0,self.length):
            surface.blit(image,(self.x[i],self.y[i])) 



class Computer:
    x = [0]
    y = [0]
    step = 44
    direction = 0
    length = 3
 
    updateCountMax = 2
    updateCount = 0

    def __init__(self, length):
       self.length = length
       for i in range(0,2000):
           self.x.append(-100)
           self.y.append(-100)

       # initial positions, no collision.
       self.x[0] = 1*44
       self.y[0] = 4*44

    def update(self):

        self.updateCount = self.updateCount + 1
        if self.updateCount > self.updateCountMax:

            # update previous positions
            for i in range(self.length-1,0,-1):
                self.x[i] = self.x[i-1]
                self.y[i] = self.y[i-1]

            # update position of head of snake
            if self.direction == 0:
                self.x[0] = self.x[0] + self.step
            if self.direction == 1:
                self.x[0] = self.x[0] - self.step
            if self.direction == 2:
                self.y[0] = self.y[0] - self.step
            if self.direction == 3:
                self.y[0] = self.y[0] + self.step

            self.updateCount = 0


    def moveRight(self):
        self.direction = 0

    def moveLeft(self):
        self.direction = 1

    def moveUp(self):
        self.direction = 2

    def moveDown(self):
        self.direction = 3 

    
    def target(self,dx,dy):
        if self.x[0] > dx:
            self.moveLeft()

        if self.x[0] < dx:
            self.moveRight()

        if self.x[0] == dx:
            if self.y[0] < dy:
                self.moveDown()

            if self.y[0] > dy:
                self.moveUp()

    def draw(self, surface, image):
        for i in range(0,self.length):
            surface.blit(image,(self.x[i],self.y[i])) 


class Game:
    def isCollision(self,x1,y1,x2,y2,bsize):
        if x1 >= x2 and x1 <= x2 + bsize:
            if y1 >= y2 and y1 <= y2 + bsize:
                return True
        return False

class App:

    windowWidth = 800
    windowHeight = 600
    player = 0
    apple = 0

    def __init__(self):
        self._running = True
        self._display_surf = None
        self._image_surf = None
        self._apple_surf = None
        self.game = Game()
        self.player = Player(5) 
        self.apple = Apple(8,5)
        self.computer = Computer(5)

    def on_init(self):
        pygame.init()
        self._display_surf = pygame.display.set_mode((self.windowWidth,self.windowHeight), pygame.HWSURFACE)
        
        pygame.display.set_caption('Pygame pythonspot.com example')
        self._running = True
        self._image_surf = pygame.image.load("pygame.png").convert()
        self._apple_surf = pygame.image.load("apple.png").convert()

    def on_event(self, event):
        if event.type == QUIT:
            self._running = False

    def on_loop(self):
        self.computer.target(self.apple.x, self.apple.y)
        self.player.update()
        self.computer.update()
        
        # does snake eat apple?
        for i in range(0,self.player.length):
            if self.game.isCollision(self.apple.x,self.apple.y,self.player.x[i], self.player.y[i],44):
                self.apple.x = randint(2,9) * 44
                self.apple.y = randint(2,9) * 44
                self.player.length = self.player.length + 1

        # does computer eat apple?
        for i in range(0,self.player.length):
            if self.game.isCollision(self.apple.x,self.apple.y,self.computer.x[i], self.computer.y[i],44):
                self.apple.x = randint(2,9) * 44
                self.apple.y = randint(2,9) * 44
                #self.computer.length = self.computer.length + 1


        # does snake collide with itself?
        for i in range(2,self.player.length):
            if self.game.isCollision(self.player.x[0],self.player.y[0],self.player.x[i], self.player.y[i],40):
                print "You lose! Collision: "
                print "x[0] (" + str(self.player.x[0]) + "," + str(self.player.y[0]) + ")"  
                print "x[" + str(i) + "] (" + str(self.player.x[i]) + "," + str(self.player.y[i]) + ")"  
                exit(0)
       
        pass
    
    def on_render(self):
        self._display_surf.fill((0,0,0))
        self.player.draw(self._display_surf, self._image_surf)
        self.apple.draw(self._display_surf, self._apple_surf)
        self.computer.draw(self._display_surf, self._image_surf)
        pygame.display.flip()
 
    def on_cleanup(self):
        pygame.quit()
 
    def on_execute(self):
        if self.on_init() == False:
            self._running = False
 
        while( self._running ):
            pygame.event.pump()
            keys = pygame.key.get_pressed() 
            
            if (keys[K_RIGHT]):
                self.player.moveRight()

            if (keys[K_LEFT]):
                self.player.moveLeft()

            if (keys[K_UP]):
                self.player.moveUp()

            if (keys[K_DOWN]):
                self.player.moveDown()

            if (keys[K_ESCAPE]):
                self._running = False

            self.on_loop()
            self.on_render()

            time.sleep (50.0 / 1000.0);
        self.on_cleanup()
 
if __name__ == "__main__" :
    theApp = App()
    theApp.on_execute()

python snake python snake

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Conclusion
You learned how to create a basic computer player using an very simple AI algorithm.

Next: Learn basic sidescroller logic

python ftp client

python snake game

pygame

python chrome extension

face detection python

In this tutorial you will learn how to apply face detection with Python. As input video we will use a Google Hangouts video. There are tons of Google Hangouts videos around the web and in these videos the face is usually large enough for the software to detect the faces.

Detection of faces is achieved using the OpenCV (Open Computer Vision) library. The most common face detection method is to extract cascades. This technique is known to work well with face detection. You need to have the cascade files (included in OpenCV) in the same directory as your program.

Related course
Master Computer Vision with OpenCV and Python

Video with Python OpenCV

To analyse the input video we extract each frame.  Each frame is shown for a brief period of time. Start with this basic program:

#! /usr/bin/python

import cv2

vc = cv2.VideoCapture('video.mp4')
c=1
fps = 24

if vc.isOpened():
    rval , frame = vc.read()
else:
    rval = False

while rval:
    rval, frame = vc.read()
    cv2.imshow("Result",frame)
    cv2.waitKey(1000 / fps);
    vc.release()

Upon execution you will see the video played without sound. (OpenCV does not support sound). Inside the while loop we have every video frame inside the variable frame. 

Face detection with OpenCV


We will display a rectangle on top of the face. To avoid flickering of the rectangle, we will show it at it latest known position if the face is not detected.

#! /usr/bin/python

import cv2

face_cascade = cv2.CascadeClassifier('lbpcascade_frontalface.xml')
vc = cv2.VideoCapture('video.mp4')

if vc.isOpened():
    rval , frame = vc.read()
else:
    rval = False

roi = [0,0,0,0]

while rval:
    rval, frame = vc.read()

    # resize frame for speed.
    frame = cv2.resize(frame, (300,200))
    
    # face detection.
    faces = face_cascade.detectMultiScale(frame, 1.8, 2)
    nfaces = 0
    for (x,y,w,h) in faces:
    cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),2)
    nfaces = nfaces + 1
    roi = [x,y,w,h]

    # undetected face, show old on position.
    if nfaces == 0:
        cv2.rectangle(frame,(roi[0],roi[1]),(roi[0]+roi[2],roi[1]+roi[3]),(0,0,255),2)

    # show result
    cv2.imshow("Result",frame)
    cv2.waitKey(1);
    vc.release()

In this program we simply assumed there is one face in the video screen. We reduced the size of the screen to speed up the processing time. This is fine in most cases because detection will work fine in lower resolutions.  If you want to execute the face detection in “real time”, keeping the computational cycle short is mandatory. An alternative to this implementation is to process first and display later.

A limitation of this technique is that it does not always detect faces and faces that are very small or occluded may not be detected. It may show false positives such as a bag detected as face.  This technique works quite well on certain type of input videos.

Download Computer Vision Examples and Course

Car tracking with cascades

Car Tracking with OpenCV Car Tracking with OpenCV

In this tutorial we will look at vehicle tracking using haar features. We have a haar cascade file trained on cars.

The program will detect regions of interest, classify them as cars and show rectangles around them.

Related course:
Master Computer Vision with OpenCV

Detecting with cascades

Lets start with the basic cascade detection program:

#! /usr/bin/python

import cv2

face_cascade = cv2.CascadeClassifier('cars.xml')
vc = cv2.VideoCapture('road.avi')

if vc.isOpened():
    rval , frame = vc.read()
else:
    rval = False

while rval:
    rval, frame = vc.read()
    
    # car detection.
    cars = face_cascade.detectMultiScale(frame, 1.1, 2)
    
    ncars = 0
    for (x,y,w,h) in cars:
        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),2)
        ncars = ncars + 1

    # show result
    cv2.imshow("Result",frame)
    cv2.waitKey(1);
    vc.release()

This will detect cars in the screen but also noise and the screen will be jittering sometimes. To avoid all of these, we have to improve our car tracking algorithm.  We decided to come up with a simple solution.

Related course:
Master Computer Vision with OpenCV

Car tracking algorithm


For every frame:
  • Detect potential regions of interest
  • Filter detected regions based on vertical,horizontal similarity
  • If its a new region, add to the collection
  • Clear collection every 30 frames

Removing false positives
The mean square error function is used to remove false positives. We compare vertical and horizontal sides of the images. If the difference is to large or to small it cannot be a car.

ROI detection
A car may not be detected in every frame. If a new car is detected, its added to the collection.
We keep this collection for 30 frames, then clear it.

#!/usr/bin/python

import cv2
import numpy as np

def diffUpDown(img):
    # compare top and bottom size of the image
    # 1. cut image in two
    # 2. flip the top side
    # 3. resize to same size
    # 4. compare difference
    height, width, depth = img.shape
    half = height/2
    top = img[0:half, 0:width]
    bottom = img[half:half+half, 0:width]
    top = cv2.flip(top,1)
    bottom = cv2.resize(bottom, (32, 64))
    top = cv2.resize(top, (32, 64))
    return ( mse(top,bottom) )

def diffLeftRight(img):
    # compare left and right size of the image
    # 1. cut image in two
    # 2. flip the right side
    # 3. resize to same size
    # 4. compare difference
    height, width, depth = img.shape
    half = width/2
    left = img[0:height, 0:half]
    right = img[0:height, half:half + half-1]
    right = cv2.flip(right,1)
    left = cv2.resize(left, (32, 64))
    right = cv2.resize(right, (32, 64))
    return ( mse(left,right) )

def mse(imageA, imageB):
    err = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2)
    err /= float(imageA.shape[0] * imageA.shape[1])
    return err

def isNewRoi(rx,ry,rw,rh,rectangles):
    for r in rectangles:
        if abs(r[0] - rx) < 40 and abs(r[1] - ry) < 40:
            return False
        return True

def detectRegionsOfInterest(frame, cascade):
    scaleDown = 2
    frameHeight, frameWidth, fdepth = frame.shape
    # Resize
    frame = cv2.resize(frame, (frameWidth/scaleDown, frameHeight/scaleDown))
    frameHeight, frameWidth, fdepth = frame.shape

    # haar detection.
    cars = cascade.detectMultiScale(frame, 1.2, 1)

    newRegions = []
    minY = int(frameHeight*0.3)
        
    # iterate regions of interest
    for (x,y,w,h) in cars:
        roi = [x,y,w,h]
        roiImage = frame[y:y+h, x:x+w]
    
        carWidth = roiImage.shape[0]
        if y > minY:
            diffX = diffLeftRight(roiImage)
            diffY = round(diffUpDown(roiImage))
        if diffX > 1600 and diffX < 3000 and diffY > 12000:
            rx,ry,rw,rh = roi
            newRegions.append( [rx*scaleDown,ry*scaleDown,rw*scaleDown,rh*scaleDown] )

    return newRegions
    
def detectCars(filename):
    rectangles = []
    cascade = cv2.CascadeClassifier('cars.xml')
    vc = cv2.VideoCapture(filename)
    
    if vc.isOpened():
        rval , frame = vc.read()
    else:
        rval = False

    roi = [0,0,0,0]
    frameCount = 0

    while rval:
    rval, frame = vc.read()
    frameHeight, frameWidth, fdepth = frame.shape
    
    newRegions = detectRegionsOfInterest(frame, cascade)
    for region in newRegions:
    if isNewRoi(region[0],region[1],region[2],region[3],rectangles):
        rectangles.append(region)
    
    for r in rectangles:
        cv2.rectangle(frame,(r[0],r[1]),(r[0]+r[2],r[1]+r[3]),(0,0,255),3)
    
    frameCount = frameCount + 1
    if frameCount > 30:
        frameCount = 0
        rectangles = []
    
    # show result
    cv2.imshow("Result",frame)
    cv2.waitKey(1);
    vc.release()

detectCars('road.avi')

Final notes
The cascades are not  rotation invariant, scale and translation invariant. In addition, Detecting vehicles with haar cascades may work reasonably well, but there is gain with other algorithms (salient points).

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Download Computer Vision Examples + Course

create csv file python

python regex

Regular expressions are essentially a highly specialized programming language embedded inside Python that empowers you to specify the rules for the set of possible strings that you want to match.

In Python you need the re module for regular expressions usage. The grammar overview is on the bottom of this page.

Related course:
Python Programming Bootcamp: Go from zero to hero

The Match function


The match function is defined as:

re.match(pattern, string)

The parameters are:

If you want to match a string to a numberic sequence of exactly five, you can use this code:

Parameters Description
pattern a regular expression
string the input string 
#!/usr/bin/python
import re

input = raw_input("Enter an input string:")
m = re.match('\d{5}\Z',input)

if m:
    print("True")
else:
    print("False")

Example outputs:

Email validation regex


We can use the same function to validate email address. The grammar rules are seen in re.compile and in the grammar table.

String Match
12345 True
12358 True
55555 True
123 False
123K5 False
5555555 False 
#!/usr/bin/python
import re

input = raw_input("Enter an input string:")
m = re.match('[^@]+@[^@]+\.[^@]+',input)

if m:
    print("True")
else:
    print("False")

The Search Function


The search function is defined as:

re.search(pattern, string)

The parameters are:

To search if an e-mail address is in a string:

Parameter Description
pattern a regular expression, defines the string to be searched
string the search space 
#!/usr/bin/python
import re

input = "Contact me by [email protected] or at the office."

m = re.search('[^@]+@[^@]+\.[^@]+',input)

if m:
    print("String found.")
else:
    print("Nothing found.")

Regular Expression Examples


A few examples of regular expressions:

Regular Expression Grammar


Overview of the regex grammar:
Example Regex
IP address (([2][5][0-5]\.)|([2][0-4][0-9]\.)|([0-1]?[0-9]?[0-9]\.)){3}(([2][5][0-5])|([2][0-4][0-9])|([0-1]?[0-9]?[0-9]))
Email [^@]+@[^@]+\.[^@]+
Date MM/DD/YY (\d+/\d+/\d+)
Integer (positive) (?<![-.])\b[0-9]+\b(?!\.[0-9])
Integer [+-]?(?<!\.)\b[0-9]+\b(?!\.[0-9])
Float (?<=>)\d+.\d+|\d+
Hexadecimal \s–([0-9a-fA-F]+)(?:–)?\s

sqlalchemy orm

An object relational mapper maps a relational database system to objects. If you are unfamiliar with object orientated programming, read this tutorial first. The ORM is independent of which relational database system is used. From within Python, you can talk to objects and the ORM will map it to the database. In this article you will learn to use the SqlAlchemy ORM.

What an ORM does is shown in an illustration below:


Related course:

Creating a class to feed the ORM
We create the file tabledef.py. In this file we will define a class Student. An abstract visualization of the class below:

Observe we do not define any methods, only variables of the class. This is because we will map this class to the database and thus won’t need any methods.

This is the contents of tabledef.py:

Regex Description
\d Matches any decimal digit; this is equivalent to the class [0-9]
\D Matches any non-digit character; this is equivalent to the class [^0-9].
\s Matches any whitespace character; this is equivalent to the class [ \t\n\r\f\v].
\S Matches any non-whitespace character; this is equivalent to the class [^ \t\n\r\f\v].
\w Matches any alphanumeric character; this is equivalent to the class [a-zA-Z0-9_].
\W Matches any non-alphanumeric character; this is equivalent to the class [^a-zA-Z0-9_].
\Z Matches only at end of string
[..] Match single character in brackets
[^..] Match any single character not in brackets
. Match any character except newline
$ Match the end of the string
* Match 0 or more repetitions
+ 1 or more repetitions
{m} Exactly m copies of the previous RE should be matched.
| Match A or B. A|B
? 0 or 1 repetitions of the preceding RE
[a-z] Any lowercase character
[A-Z] Any uppercase character
[a-zA-Z] Any character
[0-9] Any digit
ORM Object Relational Mapping ORM Object Relational Mapping. We communicate with the database using the ORM and only use Python objects and classes. class Class definition 
from sqlalchemy import *
from sqlalchemy import create_engine, ForeignKey
from sqlalchemy import Column, Date, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship, backref

engine = create_engine('sqlite:///student.db', echo=True)
Base = declarative_base()
 
########################################################################
class Student(Base):
    """"""
    __tablename__ = "student"
 
    id = Column(Integer, primary_key=True)
    username = Column(String)
    firstname = Column(String)
    lastname = Column(String)
    university = Column(String)

    #----------------------------------------------------------------------
    def __init__(self, username, firstname, lastname, university):
        """"""
        self.username = username
        self.firstname = firstname
        self.lastname = lastname
        self.university = university

# create tables
Base.metadata.create_all(engine)

Execute with:

python tabledef.py

The ORM created the database file tabledef.py. It will output the SQL query to the screen, in our case it showed:

CREATE TABLE student (
	id INTEGER NOT NULL, 
	username VARCHAR, 
	firstname VARCHAR, 
	lastname VARCHAR, 
	university VARCHAR, 
	PRIMARY KEY (id)
)

Thus, while we defined a class, the ORM created the database table for us. This table is still empty.

Inserting data into the database
The database table is still empty. We can insert data into the database using Python objects. Because we use the SqlAlchemy ORM we do not have to write a single SQL query. We now simply create Python objects that we feed to the ORM. Save the code below as dummy.py

import datetime
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from tabledef import *

engine = create_engine('sqlite:///student.db', echo=True)

# create a Session
Session = sessionmaker(bind=engine)
session = Session()

# Create objects  
user = Student("james","James","Boogie","MIT")
session.add(user)

user = Student("lara","Lara","Miami","UU")
session.add(user)

user = Student("eric","Eric","York","Stanford")
session.add(user)

# commit the record the database
session.commit()

Execute with:

python dummy.py

The ORM will map the Python objects to a relational database. This means you do not have any direct interaction from your application, you simply interact with objects. If you open the database with SQLiteman or an SQLite database application you’ll find the table has been created:

Data in database table. Data in database table.

Query the data
We can query all items of the table using the code below. Note that Python will see every record as a unique object as defined by the Students class. Save the code as demo.py

import datetime
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from tabledef import *

engine = create_engine('sqlite:///student.db', echo=True)

# create a Session
Session = sessionmaker(bind=engine)
session = Session()

# Create objects  
for student in session.query(Student).order_by(Student.id):
    print student.firstname, student.lastname

On execution you will see:

James Boogie
Lara Miami
Eric York

To select a single object use the filter() method. A demonstration below:

import datetime
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from tabledef import *

engine = create_engine('sqlite:///student.db', echo=True)

# create a Session
Session = sessionmaker(bind=engine)
session = Session()

# Select objects  
for student in session.query(Student).filter(Student.firstname == 'Eric'):
    print student.firstname, student.lastname

Output:

Eric York

Finally, if you do not want the ORM the output any of the SQL queries change the create_engine statement to:

engine = create_engine('sqlite:///student.db', echo=False)

pyqt qml

wxpython

wxPython GUI wxPython GUI The wxPython module can be used to create a graphical application (GUI) that looks like a native application on any operating system including Windows, Mac OS X and Linux.

The official wxPython site has several screenshots and downloads for these platforms. wxPython is based on wxWidgets.

Related course: Creating GUI Applications with wxPython

Install wxPython

First download and install WxPython, the Python bindings for wxWidgets.

sudo apt-get install python-wxgtk2.8 python-wxtools wx2.8-doc wx2.8-examples wx2.8-headers wx2.8-i18n


Then install a GUI creator called wxglade:

sudo apt-get install wxglade


Using a GUI builder such as wxGlade will save you a lot of time, regardless of the GUI library you use. You can easily make complex graphical interfaces because you can simply drag and drop.

Creating our first GUI with Python and wxWidgets:



Start wxglade. You will see its user interface:

wxglade wxglade

Press on tiny window on the top left, below the file icon.

wxglade wxglade

Press OK. An empty window will now appear. Press on the tiny [OK] button in the wxGlade panel and press on the frame. The button will now appear. Press on Application in the tree window.

wxglade wxglade

Set the output file in the wxproperties window.

wxglade wxglade

If you look at the window note you can select multiple programming languages and two versions of wxWidgets. Select Python and wxWidgets 2.8. Finally press Generate code. (Do NOT name the file wx.py because the import needs wx, save it as window.py or something else).

Running wxglade code:


Run:

python window.py

And a window with a button will appear. Pressing the button will not do anything. To start a function when pressing the button, we need to define a so called Callback. This can be as simple as:

def OnButton(self, Event, button_label):
    print "In OnButton:", button_label

Finally we bind the button to the callback function using:

self.button_1.Bind(wx.EVT_BUTTON, self.OnButton )

Pressing the button will now write a message to the command line. Instead of the boring command line message, we want to show a message box. This can be done using this command:

wx.MessageBox( "This is a message.", "Button pressed.");

wxPython example code


The full code below:

#!/usr/bin/env python
# -*- coding: UTF-8 -*-
#
# generated by wxGlade 0.6.8 on Fri Jan 23 22:59:56 2015
#

import wx

# begin wxGlade: dependencies
import gettext
# end wxGlade

# begin wxGlade: extracode
# end wxGlade


class MyFrame(wx.Frame):
    def __init__(self, *args, **kwds):
        # begin wxGlade: MyFrame.__init__
        kwds["style"] = wx.DEFAULT_FRAME_STYLE
        wx.Frame.__init__(self, *args, **kwds)
        self.button_1 = wx.Button(self, wx.ID_ANY, _("Hello World!"))
        self.button_1.Bind(wx.EVT_BUTTON, self.OnButton )

        self.__set_properties()
        self.__do_layout()
        # end wxGlade

    def __set_properties(self):
        # begin wxGlade: MyFrame.__set_properties
        self.SetTitle(_("wxWidgets button example. pythonspot.com "))
        # end wxGlade

    def __do_layout(self):
        # begin wxGlade: MyFrame.__do_layout
        sizer_1 = wx.BoxSizer(wx.VERTICAL)
        sizer_1.Add(self.button_1, 0, 0, 0)
        self.SetSizer(sizer_1)
        sizer_1.Fit(self)
        self.Layout()
        # end wxGlade

    def OnButton(event, button_label):
        wx.MessageBox( "This is a message.", "Button pressed.");
  

# end of class MyFrame
if __name__ == "__main__":
    gettext.install("app") # replace with the appropriate catalog name

    app = wx.PySimpleApp(0)
    wx.InitAllImageHandlers()
    frame_1 = MyFrame(None, wx.ID_ANY, "")
    app.SetTopWindow(frame_1)
    frame_1.Show()
    app.MainLoop()

Related course: Creating GUI Applications with wxPython

 

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