Tag: python

python if string equals

A string in Python represents a sequence of characters and is a fundamental data type in the language. Strings are predominantly utilized for displaying and manipulating text.

Strings can be defined by enclosing text within quotes. Python supports various types of quotes, including single ('), double ("), and triple (''' or """).

Displaying and Receiving String Input

To display a string on the screen, you can use the print function. For instance:

s = "hello world"
print(s)

If you need to retrieve a string input from the user via the keyboard, the input function comes in handy:

name = input("Enter name: ")
print(name)

Note: If you are utilizing an older version of Python (2.x), the raw_input function is used instead of input:

name = raw_input("Enter name: ")
print(name)

To ascertain your Python version, you can execute the command:
python –version

Comparing Strings in Python

In Python, the equality operator (==) lets you check if two strings are identical. For example:

sentence = "The cat is brown"
q = "cat"

if q == sentence:
    print('strings are identical')

Conversely, to see if two strings are different, employ the inequality operator (!=):

sentence = "The cat is brown"
q = "cat"

if q != sentence:
    print('strings are not identical')

Enhance your Python skills further with exercises:
Download Python Exercises

For more tutorials, navigate:

Python functions are powerful tools in programming. They enable you to create reusable blocks of code, thereby enhancing the efficiency and readability of your programs.
Python is renowned for its simplicity and functions play a vital role in this. By leveraging functions, programmers can reduce repetition, increase code clarity, and simplify testing and modifications.

Understanding Python Functions

To comprehend the power and structure of functions in Python, it’s essential to first understand their syntax and formation.

In Python, the def keyword signals the beginning of a function. This is followed by the function name and any parameters the function might need. The body of the function contains the operations to be carried out, and the function may or may not return a value.

Here’s a basic structure:

def function_name(parameters):
    # Body of the function
    return value

A Simple Python Function in Action

To illustrate, let’s look at a function that calculates the square of a number.

#!/usr/bin/python

def square(x):
    return x * x
    
print(square(3))

This will produce the output:

The above example demonstrates a function with a single parameter, x. It’s worth noting that while functions can return a value (like our square function), not all functions are required to.

Delving Deeper: Multiple Parameters in Python Functions

Functions in Python can be more intricate. They can accept multiple parameters, making them incredibly versatile.

Consider this example:

#!/usr/bin/python

def multiply(x, y):
    print(f'You called multiply(x,y) with the values x = {x} and y = {y}')
    print(f'x * y = {x * y}')

multiply(3, 2)

The output will be:

You called multiply(x,y) with the values x = 3 and y = 2
x * y = 6

The key takeaway here is the versatility of functions in Python. Whether you’re working with a single parameter or multiple ones, Python functions are designed to streamline your programming efforts.

Dive deeper with Python exercises here

dbms in python

In this tutorial you will learn how to use the SQLite database management system with Python. You will learn how to use SQLite, SQL queries, RDBMS and more of this cool stuff!

Related course: Master SQL Databases with Python

Pyton Database

Python Database.
Data is retrieved from a database system using the SQL language. Data is everywhere and software applications use that. Data is either in memory, files or databases.

Python has bindings for many database systems including MySQL, Postregsql, Oracle, Microsoft SQL Server and Maria DB.

One of these database management systems (DBMS) is called SQLite. SQLite was created in the year 2000 and is one of the many management systems in the database zoo.

SQL is a special-purpose programming language designed for managing data held in a databases. The language has been around since 1986 and is worth learning. The is an old funny video about SQL

SQLite

SQLite, a relational database management system. SQLite is the most widely deployed SQL database engine in the world. The source code for SQLite is in the public domain.

It is a self-contained, serverless, zero-configuration, transactional SQL database engine. The SQLite project is sponsored by Bloomberg and Mozilla.

Install SQLite:

Use this command to install SQLite:

$ sudo apt-get install sqlite

Verify if it is correctly installed. Copy this program and save it as test1.py

#!/usr/bin/python
# -*- coding: utf-8 -*-

import sqlite3 as lite
import sys

con = None

try:
    con = lite.connect('test.db')
    cur = con.cursor()  
    cur.execute('SELECT SQLITE_VERSION()')
    data = cur.fetchone()
    print "SQLite version: %s" % data                
except lite.Error, e:   
    print "Error %s:" % e.args[0]
    sys.exit(1)
finally:    
    if con:
        con.close()

Execute with:

$ python test1.py

It should output:

SQLite version: 3.8.2

What did the script above do?
The script connected to a new database called test.db with this line:

con = lite.connect('test.db')

It then queries the database management system with the command

SELECT SQLITE_VERSION()

which in turn returned its version number. That line is known as an SQL query.

Related course: Master SQL Databases with Python

SQL Create and Insert

The script below will store data into a new database called user.db

#!/usr/bin/python
# -*- coding: utf-8 -*-

import sqlite3 as lite
import sys

con = lite.connect('user.db')

with con:
    
    cur = con.cursor()    
    cur.execute("CREATE TABLE Users(Id INT, Name TEXT)")
    cur.execute("INSERT INTO Users VALUES(1,'Michelle')")
    cur.execute("INSERT INTO Users VALUES(2,'Sonya')")
    cur.execute("INSERT INTO Users VALUES(3,'Greg')")

SQLite is a database management system that uses tables. These tables can have relations with other tables: it’s called relational database management system or RDBMS. The table defines the structure of the data and can hold the data. A database can hold many different tables. The table gets created using the command:

cur.execute("CREATE TABLE Users(Id INT, Name TEXT)")

We add records into the table with these commands:

cur.execute("INSERT INTO Users VALUES(2,'Sonya')")
cur.execute("INSERT INTO Users VALUES(3,'Greg')")

The first value is the ID. The second value is the name. Once we run the script the data gets inserted into the database table Users:

SQL Table

SQLite query data

We can explore the database using two methods: the command line and a graphical interface.

From console: To explore using the command line type these commands:

sqlite3 user.db
.tables
SELECT * FROM Users;

This will output the data in the table Users.

sqlite&gt; SELECT * FROM Users;
1|Michelle
2|Sonya
3|Greg

From GUI: If you want to use a GUI instead, there is a lot of choice. Personally I picked sqllite-man but there are many others. We install using:

sudo apt-get install sqliteman

We start the application sqliteman. A gui pops up.

sqliteman

Press File > Open > user.db. It appears like not much has changed, do not worry, this is just the user interface. On the left is a small tree view, press Tables > users. The full table including all records will be showing now.

sqliteman

This GUI can be used to modify the records (data) in the table and to add new tables.

Related course: Master SQL Databases with Python

The SQL database query language

SQL has many commands to interact with the database. You can try the commands below from the command line or from the GUI:

sqlite3 user.db 
SELECT * FROM Users;
SELECT count(*) FROM Users;
SELECT name FROM Users;
SELECT * FROM Users WHERE id = 2;
DELETE FROM Users WHERE id = 6;

We can use those queries in a Python program:

#!/usr/bin/python
# -*- coding: utf-8 -*-

import sqlite3 as lite
import sys


con = lite.connect('user.db')

with con:    
    
    cur = con.cursor()    
    cur.execute("SELECT * FROM Users")

    rows = cur.fetchall()

    for row in rows:
        print row

This will output all data in the Users table from the database:

$ python get.py 
(1, u'Michelle')
(2, u'Sonya')
(3, u'Greg')

Creating a user information database

We can structure our data across multiple tables. This keeps our data structured, fast and organized. If we would have a single table to store everything, we would quickly have a big chaotic mess. What we will do is create multiple tables and use them in a combination. We create two tables:

Users:

SQL Table

Jobs:

SQL Table

To create these tables, you can do that by hand in the GUI or use the script below:

# -*- coding: utf-8 -*-
 
import sqlite3 as lite
import sys
 
con = lite.connect('system.db')
 
with con:
    
    cur = con.cursor()    
    cur.execute("CREATE TABLE Users(Id INT, Name TEXT)")
    cur.execute("INSERT INTO Users VALUES(1,'Michelle')")
    cur.execute("INSERT INTO Users VALUES(2,'Howard')")
    cur.execute("INSERT INTO Users VALUES(3,'Greg')")

    cur.execute("CREATE TABLE Jobs(Id INT, Uid INT, Profession TEXT)")
    cur.execute("INSERT INTO Jobs VALUES(1,1,'Scientist')")
    cur.execute("INSERT INTO Jobs VALUES(2,2,'Marketeer')")
    cur.execute("INSERT INTO Jobs VALUES(3,3,'Developer')")

The jobs table has an extra parameter, Uid. We use that to connect the two tables in an SQL query:

SELECT users.name, jobs.profession FROM jobs INNER JOIN users ON users.ID = jobs.uid

You can incorporate that SQL query in a Python script:

#!/usr/bin/python
# -*- coding: utf-8 -*-

import sqlite3 as lite
import sys


con = lite.connect('system.db')

with con:    
    
    cur = con.cursor()    
    cur.execute("SELECT users.name, jobs.profession FROM jobs INNER JOIN users ON users.ID = jobs.uid")

    rows = cur.fetchall()

    for row in rows:
        print row

It should output:

$ python get2.py
(u'Michelle', u'Scientist')
(u'Howard', u'Marketeer')
(u'Greg', u'Developer')

You may like: Databases and data analysis

Matplotlib Bar chart

Matplotlib may be used to create bar charts. You might like the Matplotlib gallery.

Matplotlib is a python library for visualizing data. You can use it to create bar charts in python. Installation of matplot is on pypi, so just use pip: pip install matplotlib

The course below is all about data visualization:

Related course:
Data Visualization with Matplotlib and Python

Bar chart code

A bar chart shows values as vertical bars, where the position of each bar indicates the value it represents. matplot aims to make it as easy as possible to turn data into Bar Charts.

A bar chart in matplotlib made from python code. The code below creates a bar chart:

import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt

objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp')
y_pos = np.arange(len(objects))
performance = [10,8,6,4,2,1]

plt.bar(y_pos, performance, align='center', alpha=0.5)
plt.xticks(y_pos, objects)
plt.ylabel('Usage')
plt.title('Programming language usage')

plt.show()

Output:

Python Bar Chart

Matplotlib charts can be horizontal, to create a horizontal bar chart:

import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt

objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp')
y_pos = np.arange(len(objects))
performance = [10,8,6,4,2,1]

plt.barh(y_pos, performance, align='center', alpha=0.5)
plt.yticks(y_pos, objects)
plt.xlabel('Usage')
plt.title('Programming language usage')

plt.show()

Output:

Bar chart horizontal

Bar chart comparison

You can compare two data series using this Matplotlib code:

import numpy as np
import matplotlib.pyplot as plt

# data to plot
n_groups = 4
means_frank = (90, 55, 40, 65)
means_guido = (85, 62, 54, 20)

# create plot
fig, ax = plt.subplots()
index = np.arange(n_groups)
bar_width = 0.35
opacity = 0.8

rects1 = plt.bar(index, means_frank, bar_width,
alpha=opacity,
color='b',
label='Frank')

rects2 = plt.bar(index + bar_width, means_guido, bar_width,
alpha=opacity,
color='g',
label='Guido')

plt.xlabel('Person')
plt.ylabel('Scores')
plt.title('Scores by person')
plt.xticks(index + bar_width, ('A', 'B', 'C', 'D'))
plt.legend()

plt.tight_layout()
plt.show()

Output:

Python Bar Chart comparison

Stacked bar chart

The example below creates a stacked bar chart with Matplotlib. Stacked bar plots show diffrent groups together.

# load matplotlib
import matplotlib.pyplot as plt

# data set
x = ['A', 'B', 'C', 'D']
y1 = [100, 120, 110, 130]
y2 = [120, 125, 115, 125]

# plot stacked bar chart 
plt.bar(x, y1, color='g')
plt.bar(x, y2, bottom=y1, color='y')
plt.show()

Output:

stacked bar chart

Download All Matplotlib Examples

pie chart python

Matplotlib is a versatile library in Python that supports the creation of a wide variety of charts, including pie charts. Check out the Matplotlib gallery to explore more chart types.

Related course: Data Visualization with Matplotlib and Python

Crafting a Pie Chart with Matplotlib

To begin with, ensure you’ve imported the required module using: import matplotlib.pyplot as plt. Once done, the plt.pie() method is readily available for creating your pie chart.

Here’s a simple example that demonstrates how to generate a pie chart:

import matplotlib.pyplot as plt

# Defining data for the chart
labels = 'Python', 'C++', 'Ruby', 'Java'
sizes = [215, 130, 245, 210]
colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
explode = (0.1, 0, 0, 0)  # explode 1st slice

# Plotting the chart
plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True, startangle=140)
plt.axis('equal')
plt.show()

With the above code, the result is a visually pleasing pie chart.

pie chart python

Matplotlib allows for extensive customization. You can determine slice sizes, which segments should stand out from the center (explode), their respective labels, and even their colors.

plt.pie(sizes, explode=explode, labels=labels, colors=colors, ...)

Enhancing Your Pie Chart with a Legend

To make your pie chart even more informative, consider adding a legend using the plt.legend() function. This overlays a legend on your chart, providing clarity.

import matplotlib.pyplot as plt

labels = ['Cookies', 'Jellybean', 'Milkshake', 'Cheesecake']
sizes = [38.4, 40.6, 20.7, 10.3]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
patches, texts = plt.pie(sizes, colors=colors, shadow=True, startangle=90)
plt.legend(patches, labels, loc="best")
plt.axis('equal')
plt.tight_layout()
plt.show()

This code renders a pie chart that’s enriched with a legend.

python pie chart

Always remember, after setting up your plot, call the method .show() to ensure it gets displayed.

plt.show()

For more examples and downloadable code, click here.

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pyqt treeview

tkinter button

The Tkinter library in Python makes it easy to develop interactive desktop applications. One of its versatile features is the ability to display buttons, serving as an interactive interface component. Here, we will explore how to create and customize buttons using this powerful library.

⚙️ Installation Check
Before proceeding, ensure that you’re using the right version of Python. Check your version:

1	python -- version

📘 Related Course:

Mastering Desktop Apps with Tkinter

Crafting Simple Buttons

Let’s begin by creating a basic button that prints a message upon clicking:

from Tkinter import *

master = Tk()

def callback():
    print "Clicked!"

b = Button(master, text="Click Me", command=callback)
b.pack()

mainloop()

Tkinter Button

Crafting Image Buttons

Enhance your UI by using buttons with images. Here’s how:

from Tkinter import *

master = Tk()
master.minsize(300,100)
master.geometry("320x100")

def callback():
    print "Clicked!"

photo = PhotoImage(file="add.png")
b = Button(master, image=photo, command=callback, height=50, width=150)
b.pack()

mainloop()

Image Button

Adding Text Labels to Image Buttons

For a blend of imagery and text, adjust your button like this:

from Tkinter import *

master = Tk()
master.minsize(300,100)
master.geometry("320x100")

def callback():
    print "Clicked!"

photo = PhotoImage(file="add.png")
b = Button(master, image=photo, text="Click Me", command=callback, height=50, width=150, compound=LEFT)
b.pack()

mainloop()

Text and Image Button

Positioning Buttons on Your GUI

Take control of your button’s position using the place function:

from Tkinter import *

master = Tk()
master.minsize(300,100)
master.geometry("320x100")

def callback():
    print "Clicked!"

photo = PhotoImage(file="add.png")
b = Button(master, image=photo, text="Click Me", command=callback, height=50, width=150, compound=LEFT)
b.place(x=20, y=20)

mainloop()

Button Placement

Want More Insights?
Dive deeper with our downloadable Tkinter examples.

qt message box

PyQT4 offers message box functionality using several functions.
Messageboxes included in PyQT4 are: question, warning, error, information, criticial and about box.

Related course: Create GUI Apps with Python PyQt5

PyQt4 mesagebox

The code below will display a message box with two buttons:

#! /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()

# Show a message box
result = QMessageBox.question(w, 'Message', "Do you like Python?", QMessageBox.Yes | QMessageBox.No, QMessageBox.No)

if result == QMessageBox.Yes:
    print('Yes.')
else:
    print('No.')

# Show window
w.show()

sys.exit(a.exec_())

Result:

qtMessagebox question

There are different types of messageboxes that PyQT4 provides.

PyQT4 Warning Box

You can display a warning box using this line of code:

QMessageBox.warning(w, "Message", "Are you sure you want to continue?")

PyQT4 Information box

We can display an information box using QMessageBox.information()

QMessageBox.information(w, "Message", "An information messagebox @ pythonspot.com ")

Result:

QMessageBox Info

PyQT4 Critical Box

If something goes wrong in your application you may want to display an error message.

QMessageBox.critical(w, "Message", "No disk space left on device.")

Result:

QMessagebox

PyQT4 About box

We have shown the question box above.

QMessageBox.about(w, "About", "An example messagebox @ pythonspot.com ")

Result:

qt Messagebox

Download PyQT Code (Bulk Collection)

python tuple

python dictionary

A dictionary can be thought of as an unordered set of key: value pairs.

A pair of braces creates an empty dictionary: {}. Each element can maps to a certain value. An integer or string can be used for the index. Dictonaries do not have an order.

Dictionary example

Let us make a simple dictionary:

#!/usr/bin/python

words = {}
words["Hello"] = "Bonjour"
words["Yes"] = "Oui"
words["No"] = "Non"
words["Bye"] = "Au Revoir"

print(words["Hello"])
print(words["No"])

Output:


Bonjour
Non

We are by no means limited to single word defintions in the value part. A demonstration:

#!/usr/bin/python

dict = {}
dict['Ford'] = "Car"
dict['Python'] = "The Python Programming Language"
dict[2] = "This sentence is stored here."

print(dict['Ford'])
print(dict['Python'])
print(dict[2])

Output:


Car
The Python Programming Language
This sentence is stored here.

Manipulating the dictionary

We can manipulate the data stored in a dictionairy after declaration. This is shown in the example below:

#!/usr/bin/python

words = {}
words["Hello"] = "Bonjour"
words["Yes"] = "Oui"
words["No"] = "Non"
words["Bye"] = "Au Revoir"

print(words)           # print key-pairs.
del words["Yes"]       # delete a key-pair.
print(words)           # print key-pairs.
words["Yes"] = "Oui!"  # add new key-pair.
print(words)           # print key-pairs.

Output:


{'Yes': 'Oui', 'Bye': 'Au Revoir', 'Hello': 'Bonjour', 'No': 'Non'}
{'Bye': 'Au Revoir', 'Hello': 'Bonjour', 'No': 'Non'}
{'Yes': 'Oui!', 'Bye': 'Au Revoir', 'Hello': 'Bonjour', 'No': 'Non'}

If you are new to Python programming, I highly recommend this book.

Download Python Exercises

How to Read a File in Python

encapsulation in python

python class inheritance

Polymorphism

python factory

recursion in python

Recursion is a widely-discussed concept not just in programming, but also in day-to-day language. An example from the English language that beautifully captures recursion is “To understand recursion, you must first understand recursion”. Similarly, the saying “A human is someone whose mother is human” offers another simple explanation.

Now, pivoting to programming, you may ask: How is this relevant?

In the realm of problem-solving, often there’s a need to break down a large, intricate problem into smaller, manageable parts. While you might be accustomed to using loops or iterations for such purposes, sometimes, recursion provides a more elegant and intuitive solution.

So, what exactly is recursion in Python? A function is termed as recursive when it makes a call to itself, but it’s imperative that this function has a stopping point or a termination condition. This ensures that the function doesn’t end up calling itself endlessly.

Recursion in Practice

List-Based Recursion Example

Consider a simple task of summing all numbers in a given list. A non-recursive approach to achieve this would be:

#!/usr/bin/env python

def sum(list):
    sum = 0

    # Iteratively add each number in the list.
    for i in range(0, len(list)):
        sum = sum + list[i]
    
    # Return the computed sum.
    return sum

print(sum([5,7,3,8,10]))

The above approach is straightforward: we iterate through each element and accumulate the sum. But how can we approach this using recursion?

#!/usr/bin/env python

def sum(list):
    if len(list) == 1:
        return list[0]
    else:
        return list[0] + sum(list[1:])

print(sum([5,7,3,8,10]))

Here, if the list contains just one element, that element is returned (acting as the termination condition). Otherwise, the function adds the first element to the sum of the rest of the list (achieved through a recursive call).

Factorial Using Recursion

Factorials are often calculated using recursion in programming. The mathematical definition states: n! = n * (n-1)!, given n > 1 and f(1) = 1. For instance, 3! = 3 x 2 x 1 = 6. Here’s how you can compute factorials recursively in Python:

#!/usr/bin/env python

def factorial(n):
    if n == 1:
        return 1
    else:
        return n * factorial(n-1)

print(factorial(3))

In the above code, as long as the input is greater than 1, the function keeps calling itself, thus calculating the factorial in a recursive manner.

Constraints of Using Recursion

It’s essential to understand the limitations of recursion. Each time a function calls itself, it uses some memory to store return values. Because of this, a recursive function can sometimes use a lot more memory compared to its iterative counterpart. In Python, recursion is limited to a depth of 1000 calls. If you try to surpass this, as demonstrated below:

#!/usr/bin/env python

def factorial(n):
    if n == 1:
        return 1
    else:
        return n * factorial(n-1)

print(factorial(3000))

You’ll be met with the error:

RuntimeError: maximum recursion depth exceeded

Some languages might crash your program under such conditions. While you can tweak the maximum recursion depth in Python, as shown:

#!/usr/bin/env python
import sys

sys.setrecursionlimit(5000)

def factorial(n):
    if n == 1:
        return 1
    else:
        return n * factorial(n-1)

print(factorial(3000))

Remember that this isn’t a foolproof solution. There will always be a threshold, and for problems like calculating large factorials, a recursive function might not be the most efficient choice. However, for tasks like directory traversal, recursion can be quite handy.

python logging

Python logging

We can track events in a software application, this is known as logging. Let’s start with a simple example, we will log a warning message.

As opposed to just printing the errors, logging can be configured to disable output or save to a file. This is a big advantage to simple printing the errors.

Logging example

import logging

# print a log message to the console.
logging.warning('This is a warning!')

This will output:

WARNING:root:This is a warning!

We can easily output to a file:

import logging

logging.basicConfig(filename='program.log',level=logging.DEBUG)
logging.warning('An example message.')
logging.warning('Another message')

The importance of a log message depends on the severity.

Level of severity

The logger module has several levels of severity. We set the level of severity using this line of code:

logging.basicConfig(level=logging.DEBUG)

These are the levels of severity:

The default logging level is warning, which implies that other messages are ignored. If you want to print debug or info log messages you have to change the logging level like so:

Type	Description
DEBUG	Information only for problem diagnostics
INFO	The program is running as expected
WARNING	Indicate something went wrong
ERROR	The software will no longer be able to function
CRITICAL	Very serious error

import logging

logging.basicConfig(level=logging.DEBUG)
logging.debug('Debug message')

Time in log

You can enable time for logging using this line of code:

logging.basicConfig(format='%(asctime)s %(message)s')

An example below:

import logging

logging.basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG)
logging.info('Logging app started')
logging.warning('An example logging message.')
logging.warning('Another log message')

Output:

2015-06-25 23:24:01,153 Logging app started
2015-06-25 23:24:01,153 An example message.
2015-06-25 23:24:01,153 Another message

python subprocess

python threading

python create set

Sets in Python

A set in Python is a collection of objects. Sets are available in Python 2.4 and newer versions. They are different from lists or tuples in that they are modeled after sets in mathematics.

Set example
To create a set, we use the set() function.

#!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram"])
print(x)

If we add the same item element multiple times, they are removed. A set may not contain the same element multiple times.

#!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram", "Postcard"])
print(x)

Simple notation

If you use Python version 2.6 or a later version, you can use a simplified notation:

#!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram"])
print(x)

y = {"Postcard","Radio","Telegram"}
print(y)

Set Methods

Clear elements from set
To remove all elements from sets:

#!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram"])
x.clear()
print(x)

Add elements to a set
To add elements to a set:

#!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram"])
x.add("Telephone")
print(x)

Remove elements to a set
To remove elements to a set:

!/usr/bin/env python

x = set(["Postcard", "Radio", "Telegram"])
x.remove("Radio")
print(x)

Difference between two sets
To find the difference between two sets use:

#!/usr/bin/env python
x = set(["Postcard", "Radio", "Telegram"])
y = set(["Radio","Television"])
print( x.difference(y) )
print( y.difference(x) )

Be aware that x.difference(y) is different from y.difference(x).

Subset
To test if a set is a subset use:

#!/usr/bin/env python

x = set(["a","b","c","d"])
y = set(["c","d"])
print( x.issubset(y) )<b>
</b>

Super-set
To test if a set is a super-set:

#!/usr/bin/env python

x = set(["a","b","c","d"])
y = set(["c","d"])
print( x.issuperset(y) )

Intersection
To test for intersection, use:

#!/usr/bin/env python

x = set(["a","b","c","d"])
y = set(["c","d"])
print( x.intersection(y) )

qpython

python web development

django getting started

python state machine

python binary number

flask hello world

In this tutorial you’ll learn how to build a web app with Python.

We’ll use a micro-framework called Flask. It has a small core but is extensible with many plugins such as SQLAlchemy, Babel, CouchDB, MongoDB etc.

Some Flask example apps are:

flaskr — a microblog
minitwit — a twitter clone
flask website — static pages + mailinglist archives

Related course
Python Flask: Make Web Apps with Python

easy to use.
built in development server and debugger
integrated unit testing support
RESTful request dispatching
uses Jinja2 templating
support for secure cookies (client side sessions)
100% WSGI 1.0 compliant
Unicode based
extensively documented

Download Flask Examples

Installing Flask

Install Flask using the command below:

pip install Flask

Flask hello world app

Create a file called hello.py


from flask import Flask
app = Flask(__name__)

@app.route("/")
    def hello():
        return "Hello World!"

if __name__ == "__main__":
    app.run()

Finally run the web app using this command:

$ python hello.py
* Running on http://localhost:5000/

Open http://localhost:5000/ in your webbrowser, and “Hello World!” should appear.

Download Flask Examples

jinja2 tutorial

chart flask

flask

python mysql

python download file from url

wx.filedialog

python dialog box input

python text game

In this article we will demonstrate how to create a simple guessing game.
The goal of the game is to guess the right number.

Example
An example run below:

Simple text game with Python

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Simple games with Python

Random number

The user will be asked to guess the random number. We first pick the random number:

from random import randint

x = randint(1,9)

The randint() function will pick a pseudo random number between 1 and 10. Then we have to continue until the correct number is found:

guess = -1

print("Guess the number below 10:")
while guess != x:
    guess = int(raw_input("Guess: "))

    if guess != x:
        print("Wrong guess")
    else:
        print("Guessed correctly")

Python Guessing Game

The code below starts the game:

from random import randint

x = randint(1,9)
guess = -1

print "Guess the number below 10:"
while guess != x:
    guess = int(raw_input("Guess: "))

    if guess != x:
        print("Wrong guess")
    else:
        print("Guessed correctly")

An example run:

Guess the number below 10:
Guess: 3
Wrong guess
Guess: 6
Wrong guess
..

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Simple games with Python

python socket

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pyqt menu

pyqt widgets

QT4 Table

We can show a table using the QTableWidget, part of the PyQt module. We set the title, row count, column count and add the data.

Related course:

Create GUI Apps with PyQt5

Qt4 Table example

An example below:

from PyQt4.QtGui import *
from PyQt4.QtCore import *
import sys

def main():
    app 	= QApplication(sys.argv)
    table 	= QTableWidget()
    tableItem 	= QTableWidgetItem()
    
    # initiate table
    table.setWindowTitle("QTableWidget Example @pythonspot.com")
    table.resize(400, 250)
    table.setRowCount(4)
    table.setColumnCount(2)
    
    # set data
    table.setItem(0,0, QTableWidgetItem("Item (1,1)"))
    table.setItem(0,1, QTableWidgetItem("Item (1,2)"))
    table.setItem(1,0, QTableWidgetItem("Item (2,1)"))
    table.setItem(1,1, QTableWidgetItem("Item (2,2)"))
    table.setItem(2,0, QTableWidgetItem("Item (3,1)"))
    table.setItem(2,1, QTableWidgetItem("Item (3,2)"))
    table.setItem(3,0, QTableWidgetItem("Item (4,1)"))
    table.setItem(3,1, QTableWidgetItem("Item (4,2)"))
    
    # show table
    table.show()
    return app.exec_()

if __name__ == '__main__':
    main()

Result:

PyQt Table

QTableWidget labels

You can set the header using the setHorizontalHeaderLabels() function. The same applies for vertical labels. A qt4 demonstration below:

from PyQt4.QtGui import *
from PyQt4.QtCore import *
import sys

def main():
    app 	= QApplication(sys.argv)
    table 	= QTableWidget()
    tableItem 	= QTableWidgetItem()
    
    # initiate table
    table.setWindowTitle("QTableWidget Example @pythonspot.com")
    table.resize(400, 250)
    table.setRowCount(4)
    table.setColumnCount(2)
    
    # set label
    table.setHorizontalHeaderLabels(QString("H1;H2;").split(";"))
    table.setVerticalHeaderLabels(QString("V1;V2;V3;V4").split(";"))
    
    # set data
    table.setItem(0,0, QTableWidgetItem("Item (1,1)"))
    table.setItem(0,1, QTableWidgetItem("Item (1,2)"))
    table.setItem(1,0, QTableWidgetItem("Item (2,1)"))
    table.setItem(1,1, QTableWidgetItem("Item (2,2)"))
    table.setItem(2,0, QTableWidgetItem("Item (3,1)"))
    table.setItem(2,1, QTableWidgetItem("Item (3,2)"))
    table.setItem(3,0, QTableWidgetItem("Item (4,1)"))
    table.setItem(3,1, QTableWidgetItem("Item (4,2)"))
    
    # show table
    table.show()
    return app.exec_()

if __name__ == '__main__':
    main()

Result:

PyQT Table

Note: These days you can use pyqt5 to create a pyqt table.

QTableWidget click events

We can detect cell clicks using this procedure, first add a function:

# on click function
table.cellClicked.connect(cellClick)

Then define the function:

def cellClick(row,col):
print "Click on " + str(row) + " " + str(col)

The Python programming language starts counting with 0, so when you press on (1,1) you will see (0,0). Full code to detect table clicks:

from PyQt4.QtGui import *
from PyQt4.QtCore import *
import sys

def cellClick(row,col):
    print "Click on " + str(row) + " " + str(col)

def main():
    app 	= QApplication(sys.argv)
    table 	= QTableWidget()
    tableItem 	= QTableWidgetItem()

    # initiate table
    table.setWindowTitle("QTableWidget Example @pythonspot.com")
    table.resize(400, 250)
    table.setRowCount(4)
    table.setColumnCount(2)
    
    # set label
    table.setHorizontalHeaderLabels(QString("H1;H2;").split(";"))
    table.setVerticalHeaderLabels(QString("V1;V2;V3;V4").split(";"))
    
    # set data
    table.setItem(0,0, QTableWidgetItem("Item (1,1)"))
    table.setItem(0,1, QTableWidgetItem("Item (1,2)"))
    table.setItem(1,0, QTableWidgetItem("Item (2,1)"))
    table.setItem(1,1, QTableWidgetItem("Item (2,2)"))
    table.setItem(2,0, QTableWidgetItem("Item (3,1)"))
    table.setItem(2,1, QTableWidgetItem("Item (3,2)"))
    table.setItem(3,0, QTableWidgetItem("Item (4,1)"))
    table.setItem(3,1, QTableWidgetItem("Item (4,2)"))
    
    # on click function
    table.cellClicked.connect(cellClick)
    
    # show table
    table.show()
    return app.exec_()

if __name__ == '__main__':
    main()

If you want to show the cell/row numbers in a non-programmer way use this instead:

def cellClick(row,col):
print "Click on " + str(row+1) + " " + str(col+1)

Tooltip text

We can set tooltip (mouse over) text using the method. If you set tooltips on non-existing columns you will get an error.

from PyQt4.QtGui import *
from PyQt4.QtCore import *
import sys

def main():
    app 	= QApplication(sys.argv)
    table 	= QTableWidget()
    tableItem 	= QTableWidgetItem()
    
    # initiate table
    table.setWindowTitle("QTableWidget Example @pythonspot.com")
    table.resize(400, 250)
    table.setRowCount(4)
    table.setColumnCount(2)
    
    # set label
    table.setHorizontalHeaderLabels(QString("H1;H2;").split(";"))
    table.setVerticalHeaderLabels(QString("V1;V2;V3;V4").split(";"))
    
    # set data
    table.setItem(0,0, QTableWidgetItem("Item (1,1)"))
    table.setItem(0,1, QTableWidgetItem("Item (1,2)"))
    table.setItem(1,0, QTableWidgetItem("Item (2,1)"))
    table.setItem(1,1, QTableWidgetItem("Item (2,2)"))
    table.setItem(2,0, QTableWidgetItem("Item (3,1)"))
    table.setItem(2,1, QTableWidgetItem("Item (3,2)"))
    table.setItem(3,0, QTableWidgetItem("Item (4,1)"))
    table.setItem(3,1, QTableWidgetItem("Item (4,2)"))
    
    # tooltip text
    table.horizontalHeaderItem(0).setToolTip("Column 1 ")
    table.horizontalHeaderItem(1).setToolTip("Column 2 ")
    
    # show table
    table.show()
    return app.exec_()

if __name__ == '__main__':
    main()

Result:

PyQT Table tooltips

Download PyQT Code (Bulk Collection)