scott.greenough
Create a binary tree in Python
To create a binary tree in Python, you can use the following code:
class Node:
def __init__(self, val):
self.val = val
self.left = None
self.right = None
class BinaryTree:
def __init__(self):
self.root = None
def insert(self, val):
if not self.root:
self.root = Node(val)
else:
cur = self.root
while True:
if val < cur.val:
if not cur.left:
cur.left = Node(val)
break
else:
cur = cur.left
else:
if not cur.right:
cur.right = Node(val)
break
else:
cur = cur.right
This code defines a Node class that represents a node in a binary tree. Each node has a value and left and right child nodes.
The BinaryTree class defines a binary tree. It has a root property that represents the root node of the tree, and an insert() method that allows you to insert new nodes into the tree.
To use this code, you can create a BinaryTree object and then call the insert() method to add nodes to the tree. For example:
tree = BinaryTree()
tree.insert(5)
tree.insert(3)
tree.insert(7)
This will create a binary tree with a root node that has the value 5, and left and right child nodes with the values 3 and 7, respectively.
Basic authentication in Django
Basic authentication is a method for requiring a username and password in order to access a web application. It is commonly used in web applications built with the Django web framework.
To enable basic authentication in Django, you first need to install the django-basicauth package using pip:
pip install django-basicauth
Once the package is installed, you can use it by adding the following middleware to your Django project’s MIDDLEWARE setting:
MIDDLEWARE = [ ..., 'basicauth.BasicAuthMiddleware', ...,]
Next, you need to add the username and password that you want to use for basic authentication to your Django project’s BASIC_AUTH_USERNAME and BASIC_AUTH_PASSWORD settings, respectively:
BASIC_AUTH_USERNAME = 'myusername'
BASIC_AUTH_PASSWORD = 'mypassword'
With these settings in place, any request to your Django web application will now require the specified username and password in order to be authenticated.
It’s important to note that basic authentication is not a very secure method of authentication, and should only be used in situations where the application and its data are not sensitive. For more secure authentication, it’s recommended to use a more robust authentication method, such as OAuth or JSON Web Tokens.
Understanding strip, lstrip, and rstrip in Python
In Python, the strip(), lstrip(), and rstrip() methods are used to remove leading and trailing whitespace from strings. These methods are often used when working with text data to ensure that unnecessary whitespace is not included in the final output.
The strip() method removes leading and trailing whitespace from a string. This includes whitespace characters such as spaces, tabs, and newline characters. For example:
# remove leading and trailing whitespace from a string
my_string = " Hello, World! "
my_string = my_string.strip()
print(my_string)
In the code above, the strip() method is used to remove the leading and trailing whitespace from the string ” Hello, World! “. The resulting string, “Hello, World!”, is then printed to the console.
The lstrip() method is similar to the strip() method, but it only removes leading (i.e. left) whitespace from a string. This is useful when you want to remove whitespace from the beginning of a string, but you want to preserve any whitespace at the end of the string. For example:
# remove leading whitespace from a string
my_string = " Hello, World! "
my_string = my_string.lstrip()
print(my_string)
In the code above, the lstrip() method is used to remove the leading whitespace from the string ” Hello, World! “. The resulting string, “Hello, World! “, is then printed to the console.
The rstrip() method is similar to the lstrip() method, but it removes trailing (i.e. right) whitespace from a string instead. This is useful when you want to remove whitespace from the end of a string, but you want to preserve any whitespace at the beginning of the string. For example:
# remove trailing whitespace from a string
my_string = " Hello, World! "
my_string = my_string.rstrip()
print(my_string)
In the code above, the rstrip() method is used to remove the trailing whitespace from the string ” Hello, World! “. The resulting string, ” Hello, World!”, is then printed to the console.
In summary, the strip(), lstrip(), and rstrip() methods in Python are used to remove leading and trailing whitespace from strings. These methods are often used when working with text data to ensure that unnecessary whitespace is not included in the final output.
List Initialization in Python
List initialization is a common operation in Python, which allows users to create a list of items with a specific size and initialize the values of the items to default values. This is often useful when working with large lists or when the exact size of the list is not known in advance.
To initialize a list in Python, you can use the square bracket notation and specify the size of the list as follows:
# initialize a list of 5 items with default values
my_list = [None] * 5
In the example above, we have created a list of 5 items, and all the items in the list have been initialized to the default value of None.
Alternatively, you can also use the built-in list() function to initialize a list with a specific size. This function takes the length of the list as its only argument, and it returns a new list with the specified number of items, all initialized to the default value of None:
# initialize a list of 5 items with default values
my_list = list(5)
Once you have initialized a list with a specific size, you can access and modify the items in the list using their index. For example, you can use the square bracket notation to access a specific item in the list and assign a new value to it:
# initialize a list of 5 items with default values
my_list = [None] * 5my_list[1] = “Hello”
In the example above, we have created a list of 5 items, and then we have assigned the value “Hello” to the second item in the list.
Additionally, you can also use the built-in range() function to create a list of a specific size and initialize the items in the list with a sequence of numbers. This is often useful when working with numerical data. For example:
# initialize a list of 5 items with a sequence of numbers
my_list = list(range(5))print(my_list)
In the code above, we have created a list of 5 items, and each item in the list has been initialized with a number from 0 to 4.
In summary, list initialization is a common operation in Python that allows you to create a list of a specific size and initialize the items in the list to default values. This can be done using the square bracket notation or the built-in list() function. Once you have initialized a list, you can access and modify the items in the list using their index.
reverse words in a string using python
To reverse the words in a string using Python, you can use the split() method to split the string into a list of words, and then use the reverse() method to reverse the order of the words in the list. Finally, you can use the join() method to combine the reversed list of words back into a single string.
Here is an example of how to reverse the words in a string using Python:
Copy code
# Define the string to be reversed
string = “This is a string of words”
# Split the string into a list of words
words = string.split()
# Reverse the order of the words in the list
words.reverse()
# Join the reversed list of words back into a single string
reversed_string = ” “.join(words)
# Print the reversed string
print(reversed_string) # “words of string a is This”
In this code, we first split the string into a list of words using the split() method. Then, we use the reverse() method to reverse the order of the words in the list. Finally, we use the join() method to combine the reversed list of words back into a single string, and print the result.
By using these methods, we are able to easily and efficiently reverse the words in a string using Python. This can be useful in a variety of situations, such as when you need to process natural language text or create word puzzles.
Built in exceptions in Python
Python is a popular programming language known for its simplicity and flexibility. One of the features that makes Python a great language to work with is its support for built-in exceptions, which are errors that can occur during the execution of a program and which are handled by the Python runtime.
Built-in exceptions in Python are organized into a hierarchy of classes, with the base class being Exception. This class provides a common base for all built-in exceptions, and defines a set of common methods and attributes that are shared by all exceptions.
In addition to the Exception class, Python also defines a number of more specific exception classes that are derived from the Exception class. For example, the ZeroDivisionError class is used to indicate that a division or modulo operation has been attempted with a divisor of zero, and the TypeError class is used to indicate that an operation or function has been called on an object of an inappropriate type.
To handle built-in exceptions in Python, a developer can use a try-except block, which allows them to specify a block of code that may raise an exception and a block of code that should be executed if an exception occurs. For example, the following code uses a try-except block to handle a ZeroDivisionError exception:
try:
result = 1 / 0
except ZeroDivisionError:
print("Cannot divide by zero")
In this code, the try block contains the code that may raise the exception (the division operation), and the except block contains the code that should be executed if the exception occurs (the print statement).
Built-in exceptions in Python provide a convenient and flexible way to handle errors in a program. By using try-except blocks and the hierarchy of built-in exception classes, Python developers can write code that is robust, reliable, and easy to maintain.
Understanding comprehensions in Python
Python comprehensions are a concise and intuitive way to create and manipulate sequences in Python. They allow you to easily construct lists, sets, and dictionaries by applying operations to elements in an iterable.
Comprehensions are written in a similar syntax to regular for-loops, but with a few key differences. For example, here is a for-loop that creates a list of the squares of the numbers from 1 to 10:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
squares = []squares.append(number ** 2)
This code is perfectly fine, but it can be rewritten more concisely using a list comprehension:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
squares = [number ** 2 for number in numbers]In this example, the list comprehension has the same effect as the for-loop, but it is written in a much more concise and readable way. The general syntax for a list comprehension is [expression for item in iterable], where expression is applied to each element in iterable to produce the element in the new list.
List comprehensions can also include an optional conditional expression, which is written after the for loop and before the closing bracket. This allows you to filter the elements in the iterable based on a certain condition. For example, here is a list comprehension that only includes the even numbers from 1 to 10:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = [number for number in numbers if number % 2 == 0]In this case, the list comprehension only includes the numbers that satisfy the condition number % 2 == 0, which means they are even. This is equivalent to the following for-loop:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = []if number % 2 == 0:
even_numbers.append(number)
In addition to lists, comprehensions can also be used to create sets and dictionaries. Here is an example of a set comprehension that creates a set of the square roots of the numbers from 1 to 10:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
square_roots = {number ** 0.5 for number in numbers}And here is an example of a dictionary comprehension that creates a dictionary with the numbers from 1 to 10 as keys and their squares as values:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
squares = {number: number ** 2 for number in numbers}Comprehensions are a powerful and elegant tool in Python that can help you write concise and readable code. They are particularly useful for creating and manipulating sequences, and can be a great alternative to for-loops in many cases.
Using absolute value in Python
What is an absolute value?
According to the wikipedia article, the absolute value or modulus of a real number x, denoted |x|, is the non-negative value of x without regard to its sign. Namely |x| = x if x is a positive number and |x| = -x of x is negative, and |0| = 0.
Ok, so what does that mean? Well, basically the absolute value of any real number is the positive version of that. So, -1 -> 1, -5.3 -> 5.3.
It’s very simple and very easy to do but why would you use it?
IF you want to learn more about the mathematical side of absolute values, check out Brightstorm for more information!
Why you might need an absolute value?
Absolute value has many applications in science, math, and engineering.
Check out this Quora article for more in-depth (read: beyond my ken!) information and examples of absolute values and how they’re used.
How to use absolute value in Python
It’s pretty simple to apply the absolute value to a number in Python
x = -3
print(abs(x))
y = 0
print(abs(y))
z = 5
print(abs(z))
abs(x)
Print(x)
Output:
3
0
5
That’s all there is to it! Hope this helps.
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Python 3.11 is released!
Python has just announced their new release 3.11
https://blog.python.org/2022/10/python-3110-is-now-available.html?utm_source=tldrnewsletter
You can find information on the new feature and how it compares to Python 3.10. And they give you a little Physics lesson to boot. Awesome!
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Top Software and Tools For Python Developers with Overviews and Prices
Python has been around since 1989, but now it’s one of the most popular programming languages on GitHub due to its simple syntax, readable code, and easy data analysis libraries. If you are looking for new ways to enhance the development process and have a better, more productive workflow by picking up the right tool, we got you covered. Here is a list of the top 10 useful software and tools that can boost your Python development.
1) PyCharm Professional is one of the most popular Python IDEs, with powerful debugging and code analysis capabilities. It offers all you need for productive Python, Web, and scientific development.
PyCharm supports Python 3.6 and is cross-platform, running on Windows, macOS, and Linux.
Key features:
Git integration
Code Intelligence
Autocomplete and Go to Definition
Code analysis and refactoring support for Python 3.6+
$8.90 every month and $89.00 every year
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2) Spyder is a cross-platform, open-source IDE that offers several features such as code intelligence, debugging & profiling tools, a debugger (with breakpoints), unit testing, etc. It’s a great IDE for both beginners and experts.
Key features:
Git integration
Code intelligence
$20 per month subscription
Cross-platform with macOS and Linux support (for example, the Linux build of Spyder works on Ubuntu itself, which is not an easy task)
3) PyCharm Community Edition is a free Python IDE for Windows and Linux that offers a lot of features such as code intelligence, IDE plugins, Jupyter integrated GUI console, etc. It’s also cross-platform. The version offered here is a fully functional version without any limitations. It works exactly like a commercial version with some minor differences in appearance, and it comes with no limitations tied to its license.
4) Dr. Python is a cross-platform, open-source IDE for Python development. It offers a number of features such as code intelligence, debugging & profiling tools, a debugger (with breakpoints), unit testing, etc. It’s also available on different platforms, such as Windows and Linux.
Key features:
Code intelligence, autocomplete and code analysis integration for Python 2/3, Numpy, and Scipy libraries.
$8.90 every month and $89.00 every year
Cross-platform with macOS and Linux support (for example, has a native look on Ubuntu itself)
It’s OSI-APPROVED OPEN SOURCE LICENSE
5) Anaconda is an enhanced package manager and environment manager. It’s an extremely popular platform for Python 3. It’s very versatile and offers everything needed for Python software development.
The installation process is a little complex, so it’s recommended that you use Ubuntu-based virtual machines (VirtualBox) to do this. Anaconda will work on many Linux distributions, including CentOS, OS X, ArchLinux, Debian, and others.
6) PythonAnywhere is an online Python IDE that runs in your browser and offers many features such as code intelligence, syntax highlighting, debugging & profiling tools, unit testing, IPython console, etc.
It’s recommended to use it with Chrome browser.
Key features:
Python 3.4+ support with 48 libraries preinstalled (NumPy and SciPy for scientific computing)
IPython console integrated into the environment for interactive sessions and debugging.
$9.90 every month and $89.00 every year
Code analysis and refactoring for Python 3.4+
7) Atom is a cross-platform text editor both for Windows and Linux. It offers a lot of features such as code intelligence, syntax highlighting, debugging & profiling tools, unit testing, etc. It’s also available on different platforms, such as Windows and macOS. Note that Atom Editor is not an IDE. Therefore, it doesn’t include any features to make your development process faster in terms of code intelligence like PyCharm does or to make you develop software more easily. Some other IDEs that offer this feature are PyCharm Community Edition and Spyder. NOTE: The version here is a stable version compatible with at least Python 2.7, 3.4, 3.5, and 3.6 installed
Key features:
Code intelligence for Python 2/3/4 with 48 preinstalled libraries and modules (NumPy, SciPy, Matplotlib, Pandas)
A $10 monthly subscription
Python language support: syntax highlighting, code intelligence (autocomplete), debugging & profiling tools (breakpoints), unit testing, and more.
8) Django is a free, open-source application framework for developing web applications. It offers a lot of features, such as database support, URL routing, authentication, and authorization.
This is the software that powers several big websites like Instagram, Mozilla, and more.
Key features:
a $20 per month subscription
Site administration interface with database support for Django out of the box (SQLite 3)
URL routing support for easy navigation throughout the websites (with .htaccess files)
9)Flask is a microframework for Python to develop web applications. It offers a lot of features such as URL routing, user authentication, and authorization, database support (SQLite), etc.
Key features:
URL routing support for easy navigation throughout the websites (with .htaccess files)
User authentication and authorization with Flask-Login extension
$8.90 every month and $89.00 every year
10) CherryPy is a web application framework that focuses on simplicity, flexibility, and performance. It’s a Python-based web application server that gives developers the necessary tools to build their own applications from scratch.
Key features:
subscription
Extensible HTTP server and WSGI container: extend CherryPy to do things it does not support out of the box. Support for WebOb (fast request dispatching, URL routing, access to query parameters, etc.), Twisted (network communication), and other WSGI libraries.
Database interface: use any database supported by SQLAlchemy, including SQLite 3 (included with CherryPy).
How to Excel at Python Web Development
Whether you’re new to Python web development or an experienced developer, here are a few tips to help you excel at Python web development:
1. Use a Python web framework.
Python web frameworks make the process of developing Python web applications much simpler and faster. They also provide a structure that can help keep your code organized and maintainable. So if you’re starting out with Python web development, be sure to use a framework.
2. Follow the PEP 8 style guide.
PEP 8 is the official style guide for Python code. Following its recommendations can help you write more readable and consistent code. And since most Python IDEs can be configured to warn you about style violations, there’s really no excuse not to follow it.
3. Use a Python linter.
A linter is a tool that can check your code for errors and potential problems. This can be a huge help in spotting and fixing issues early on. And since there are many excellent Python linters available, there’s really no excuse not to use one.
4. Write tests for your code.
Writing tests is a great way to ensure that your code is working as intended and that any changes you make don’t break existing functionality. It can also help you find and fix bugs more quickly. So if you’re not already writing tests, be sure to start doing so.
5. Use version control.
Version control is a must for any software development project, Python web development included. It allows you to track changes to your code and revert back to previous versions if necessary. So if you’re not already using version control, be sure to start doing so.
6. Learn about deployment.
Deploying Python web applications can be challenging, particularly if you’re new to the process. But it’s essential to have at least a basic understanding of how it works. That way, you can confidently deploy your applications and avoid common pitfalls.
7. Stay up to date with the latest Python news.
Python is an ever-evolving language, and new features and improvements are always added. So it’s important to stay up to date with the latest Python news. This can be done by following relevant blogs and subscribing to mailing lists and news feeds.
8. Get involved in the Python community.
The Python community is friendly and welcoming, so don’t be afraid to get involved. There are many ways to do this, such as attending conferences and meetings, participating in online forums, and contributing to open-source projects.
9. Read Python books and tutorials.
Books and tutorials can be a great way to learn about Python web development. They can provide in-depth coverage of specific topics and serve as a reference when you need it. So if you’re looking to learn more about Python web development, be sure to check out some of the available books and tutorials.
10. Experiment and have fun.
Python is a great language for experimentation and tinkering. So don’t be afraid to try something new or explore different ways of doing things. The worst thing that can happen is that you’ll learn something. And who knows, you might just stumble upon the next big thing.
Python is a great language for web development, and there are many reasons to choose it as your framework of choice. When you use Python to develop websites, you can enjoy the benefits of a wide range of libraries and frameworks and an active community that can help you when you need it. So if you’re looking to get started with Python web development, be sure to keep these tips in mind.