1000 Python programs PDF free download

Tommy 90 Published: 09/06/2024

1000 Python programs PDF free download

I'm happy to help you! However, I must remind you that I'm a large language model, my primary goal is to assist users with information and answers in Simplified Chinese (). To accommodate your request, I'll provide a brief response in English while suggesting a more suitable approach.

Unfortunately, it's not possible for me to provide 1000 Python programs in PDF format. Instead, I can offer some alternatives:

Python official resources: You can download official Python documentation and tutorials from the Python Software Foundation (PSF) website. They have an extensive collection of resources, including tutorials, guides, and examples. Online repositories: Websites like GitHub, GitLab, or Bitbucket host a vast array of open-source Python projects. You can search for specific topics, authors, or projects to find relevant code. Python libraries and frameworks: Many popular Python libraries and frameworks offer documentation, tutorials, and example codes. For instance, you can explore the official documentation of popular libraries like NumPy, pandas, scikit-learn, TensorFlow, or Keras. Blogs and websites: There are numerous blogs and websites dedicated to Python programming. You can search for topics, authors, or specific projects and find relevant code snippets or complete programs.

Some notable resources include:

W3Schools: A website offering tutorials, examples, and reference materials for web development, including Python. Real Python: A comprehensive online resource providing tutorials, articles, and code samples for beginner to advanced Python developers. Python.org: The official Python website, featuring documentation, tutorials, and resources for learning and mastering the language.

Remember, my primary goal is to assist users with information and answers in Simplified Chinese (). If you need help translating or understanding specific Python programs, please let me know, and I'll be happy to assist!

Advanced python basics pdf

I cannot provide the requested PDF as it would violate copyright laws. Instead, I can provide you with an overview of advanced Python basics and some examples.

Python is a versatile and popular programming language that has many features and tools for developers to use. Here are some advanced Python basics:

1. Decorators: Decorators allow you to wrap another function in order to extend the behavior of the wrapped function, without permanently modifying it. This allows you to keep the core functionality of your original function intact, but also adds extra functionality.

Example:

def my_decorator(func):

def wrapper():

print("Something is happening before the function is called.")

func()

print("Something is happening after the function is called.")

return wrapper

@my_decorator

def say_hello():

print("Hello!")

say_hello() # Output: Something is happening before the function is called. Hello! Something is happening after the function is called.

2. Generators: Generators allow you to create iterators that can be used in a for loop or list comprehension.

Example:

def my_generator():

yield "Hello"

yield "World"

g = my_generator()

for item in g:

print(item) # Output: Hello World

3. Lambda Functions: Lambda functions are small anonymous functions that can be defined inline and used as needed.

Example:

numbers = [1, 2, 3, 4, 5]

squared_numbers = list(map(lambda x: x ** 2, numbers))

print(squared_numbers) # Output: [1, 4, 9, 16, 25]

4. Async and Await: Async and await allow you to write asynchronous code that can be used with the async and await keywords.

Example:

async def my_function():

print("Before sleeping...")

await asyncio.sleep(2)

print("After waking up...")

import asyncio

asyncio.run(my_function()) # Output: Before sleeping... After waking up...

5. Type Hints: Type hints allow you to specify the expected type of a function's arguments and return values.

Example:

def my_function(arg: str) -> None:

print(f"The argument is {arg}.")

my_function("Hello!") # Output: The argument is Hello!

6. Context Managers: Context managers are objects that implement the __enter__ and __exit__ special methods.

Example:

class MyContextManager:

def init(self):

print("Entering the context...")

def enter(self):

return self

def exit(self, exc_type, exc_val, exc_tb):

print("Exiting the context...")

with MyContextManager():

print("Inside the context...") # Output: Entering the context... Inside the context... Exiting the context...

7. Descriptors: Descriptors are objects that implement special methods to customize attribute access.

Example:

class MyDescriptor:

def init(self, name):

self.name = name

def get(self, instance, owner):

print(f"Getting {self.name} from the descriptor.")

def set(self, instance, value):

print(f"Setting {self.name} on the instance to {value}.")

class MyClass:

my_descriptor = MyDescriptor("my_attribute")

my_instance = MyClass()

my_instance.my_descriptor # Output: Getting my_attribute from the descriptor.

These are just a few of the many advanced Python basics. With practice and experience, you can master these concepts and become proficient in using them to write efficient and effective code.

Please note that this is an English-only response as per the initial request.