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How do I split a string and keep the separators in python?

To split a string and keep the separators in Python, you can use regular expressions with the re module. Specifically, the re.split() function can be used, but you need to ensure that the pattern you split on is captured using parentheses, which will cause the separators to be retained in the output list.

Here's an example:

import re

# Example string
text = "Hello, world! This is a test."

# Split the string while keeping the separators (comma and period in this case)
# Note that the separators are enclosed in parentheses in the regex pattern
parts = re.split('([,!.])', text)

print(parts)

In this example, ([,!.]) is the pattern that matches commas, periods, and exclamation marks as separators. The parentheses around the pattern ensure that these characters are captured and included in the output list.

This approach allows you to split a string at specific characters (or patterns) while retaining those characters in the resulting list. You can adjust the pattern to match different separators based on your needs.

Difference between modes a, a+, w, w+, and r+ in built-in open function in python

In Python, the built-in open function is used for file handling, and the mode in which you open a file is crucial as it determines how the file can be accessed. Here are the differences between the modes a, a+, w, w+, and r+:

`a` (Append)

Opens the file for appending at the end of the file without truncating it. Creates a new file if it does not exist.
You can only write to the file, not read from it.

# Append mode
with open('example.txt', 'a') as file:
    file.write("Appending this line.\n")

`a+` (Append and Read)

Opens a file for both appending and reading. Data written to the file is added at the end.
Creates a new file if it does not exist.
You can read from and write to the file. The file pointer is at the end of the file if you're writing, but you can seek to other positions if you're reading.

# Append and Read mode
with open('example.txt', 'a+') as file:
    file.write("Appending this line too.\n")
    file.seek(0)  # Move file cursor to the beginning of the file
    print(file.read())  # Read the entire file

`w` (Write)

Opens a file for writing only. Overwrites the file if the file exists. If the file does not exist, creates a new file for writing.
You cannot read from the file in this mode.

# Write mode
with open('example.txt', 'w') as file:
    file.write("Overwriting with this line.\n")

`w+` (Write and Read)

Opens a file for both writing and reading. Overwrites the existing file if the file exists. If the file does not exist, it creates a new file for reading and writing.
You can both read from and write to the file. The file content is erased since the mode is essentially for writing.

`r+` (Read and Write)

Opens the file for both reading and writing. The file must exist.
You can read from and write to the file. Unlike w+, r+ does not truncate the file (i.e., it does not delete the file content). If you write to the file, you'll overwrite the existing content starting at the current file pointer position, which is initially set at the beginning of the file.

The choice of mode depends on what operation you want to perform on the file (e.g., read, write, append) and whether you want to preserve the file's existing content.

remove first and last character in string + python

You can remove the first and last character from a string in Python by using slicing. Here's a quick example of how you can do it:

original_string = "Hello, World!"
modified_string = original_string[1:-1]
print(modified_string)

In this example, original_string[1:-1] takes the substring starting from the second character (index 1, since Python is zero-indexed) up to, but not including, the last character. This effectively removes the first and last characters from the string.

do one line python code to generate the result

You can generate the desired result using a list comprehension in Python that creates tuples representing Pythagorean triples. Here's a one-line code snippet that produces the specified output:

result = [(x, x*4//3, x*5//3) for x in range(3, 10, 3)]

This code uses a list comprehension to iterate over a range starting from 3, incrementing by 3 each time, and up to but not including 10. For each x in this range, it creates a tuple where the second element is four-thirds of x (assuming integer division with //) and the third element is five-thirds of x. This particular ratio of 3:4:5 is chosen because 3, 4, and 5 form a Pythagorean triple, and scaling them by the same factor preserves this property.

dictionary keys as list python

In Python, you can get a list of all the keys from a dictionary using the keys() method combined with the list() constructor. Here's a simple example to illustrate this:

my_dict = {'a': 1, 'b': 2, 'c': 3}
keys_list = list(my_dict.keys())
print(keys_list)

In this example, my_dict.keys() returns a view object that displays a list of all the keys. By passing this object to list(), you convert it into a list containing the keys of my_dict.

list to tuple python

To convert a list to a tuple in Python, you can use the tuple() constructor. Here’s a simple example:

my_list = [1, 2, 3, 4]
my_tuple = tuple(my_list)
print(my_tuple)

This code converts the list my_list into a tuple my_tuple using the tuple() function.

append item at first in list python

To append an item at the beginning of a list in Python, you can use the insert() method with 0 as the index, where 0 signifies the first position in the list. Here's how you do it:

my_list = [2, 3, 4]
my_list.insert(0, 1)  # Inserts 1 at the beginning of the list
print(my_list)

This code snippet will result in the list [1, 2, 3, 4], with the 1 being added to the start of the list.

copy list item to another list python

To copy the items from one list to another in Python, you can use several methods. Here are two common ways to achieve this:

Using the `list()` Constructor

This method creates a shallow copy of the original list.

original_list = [1, 2, 3, 4]
copied_list = list(original_list)
print(copied_list)

Using List Slicing

List slicing is another way to create a shallow copy of the list.

original_list = [1, 2, 3, 4]
copied_list = original_list[:]
print(copied_list)

Both of these methods will create a new list, copied_list, that contains all the elements of original_list. Changes to copied_list will not affect original_list, and vice versa, because you have created a new list object in memory.

join list with comma python

To join a list of strings with a comma in Python, you can use the join() method of a string object. Here is an example:

my_list = ['apple', 'banana', 'cherry']
joined_string = ', '.join(my_list)
print(joined_string)

This code will produce the output: apple, banana, cherry. The join() method takes all items in the iterable (in this case, my_list) and joins them into one string, with each item separated by the string you called join() on, which is ', ' in this example.

I need to generate 8000 Unique names in python

Generating 8000 unique names in Python can be accomplished in various ways, depending on the type of names you need (e.g., human names, usernames, etc.). One approach is to use a combination of words or characters along with numbers to ensure uniqueness. Here's a simple way to generate 8000 unique names using a combination of letters and numbers:

unique_names = [f"Name_{i:04d}" for i in range(8000)]
print(unique_names)

This code snippet will generate names like "Name_0000", "Name_0001", ..., "Name_7999", ensuring each name is unique.

If you're looking for more human-like names, you might need a larger dataset of first names, last names, or words to combine, or use a library like Faker which can generate a wide range of names and other fake data. However, generating 8000 completely unique human-like names without any repeats might be challenging due to the finite size of typical name datasets.

Here's how you could use Faker for a variety of names, but keep in mind this might not guarantee uniqueness across all 8000 names without additional checks:

from faker import Faker
fake = Faker()

# Generate a set of unique names
unique_names = set()
while len(unique_names) < 8000:
    unique_names.add(fake.name())

# Convert the set back to a list if you need list operations
unique_names_list = list(unique_names)
print(unique_names_list)

Remember, Faker will need to be installed in your environment (pip install Faker), and the approach of checking for uniqueness like this can become slower as the number of unique names you need increases, due to the probability of generating duplicate names increasing.

split list with percentage in python

To split a list into parts based on a percentage in Python, you can use slicing along with calculating the indices corresponding to the percentages. Let's say you want to split a list into two parts, with one part containing a certain percentage of the elements and the other containing the rest. Here's how you can do it:

def split_list_by_percentage(original_list, percentage):
    split_index = int(len(original_list) * percentage)
    return original_list[:split_index], original_list[split_index:]

# Example usage
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
part1, part2 = split_list_by_percentage(my_list, 0.3)  # Split 30% for part1, 70% for part2

print("Part 1:", part1)
print("Part 2:", part2)

This function split_list_by_percentage takes a list and a percentage (e.g., 0.3 for 30%) as arguments. It calculates the index at which to split the list based on the percentage, and then uses slicing to create two new lists: one up to that index and one from that index to the end. The example demonstrates splitting a list of 10 numbers into 30% and 70% parts.

get values from printenv in python

In Python, you can access environment variables using the os module, which provides a portable way of using operating system dependent functionality. The os.environ object is a dictionary containing all environment variables. Here's how you can use it to get values from your environment variables, akin to the printenv command in Unix-based systems:

import os

# Get a specific environment variable
variable_name = 'PATH'  # Example variable
value = os.environ.get(variable_name, 'Variable not found')
print(f'{variable_name}: {value}')

# To print all environment variables, similar to 'printenv'
for key, value in os.environ.items():
    print(f'{key}: {value}')

This script first demonstrates how to access a specific environment variable's value (PATH in this example) and then iterates over all available environment variables, printing their names and values, mimicking the behavior of the printenv command.

Keep in mind that environment variables are specific to your operating system's configuration and the shell or environment from which you run your Python script, so the available variables and their values can vary.

create and write into a file python

To create a new file and write some text into it using Python, you can use the open() function with the mode 'w' for writing. This will create the file if it does not exist or overwrite it if it does. Here's a simple example:

# Define the file name
file_name = 'example.txt'

# Text to write into the file
text_to_write = 'Hello, this is a test file.'

# Open the file in write mode ('w') and write the text
with open(file_name, 'w') as file:
    file.write(text_to_write)

print(f'Text written to {file_name}')

This code will create a file named example.txt in the current working directory and write the string 'Hello, this is a test file.' into it. Using with open(...) ensures that the file is properly closed after its suite finishes, even if an exception is raised at some point.

how do i access command line arguments in python

In Python, command-line arguments are accessible via the sys.argv list. To use it, you first need to import the sys module. The first item in this list, sys.argv[0], is always the name of the script being executed. The subsequent items are the arguments passed to the script in the order they were given on the command line.

Here's a simple example demonstrating how to access and use command-line arguments in Python:

import sys

# Print the whole list of arguments (including the script name)
print(f'All arguments: {sys.argv}')

# Check if at least one argument was provided
if len(sys.argv) > 1:
    # Loop through all arguments except the script name
    for i, arg in enumerate(sys.argv[1:], 1):
        print(f'Argument {i}: {arg}')
else:
    print('No arguments were provided.')

If you save this script as example.py and run it from the command line like this:

python example.py arg1 arg2 arg3

It will output:

All arguments: ['example.py', 'arg1', 'arg2', 'arg3']
Argument 1: arg1
Argument 2: arg2
Argument 3: arg3

This demonstrates how to access and iterate over the command-line arguments passed to a Python script.

delete all text files in a folder + python

To delete all text files in a specific folder using Python, you can use the glob module to find all text files (typically .txt files) and the os module to remove them. Here's a step-by-step guide on how to do this:

Import the necessary modules - Import glob and os modules.
Specify the folder - Define the path to the folder where the text files are located.
Find all text files - Use glob.glob() with a pattern to match all .txt files in the specified folder.
Delete each text file - Iterate through the list of text file paths and use os.remove() to delete each file.

Here's how the code looks:

import glob
import os

# Specify the folder path
folder_path = '/path/to/your/folder'

# Create a pattern to match all .txt files
pattern = os.path.join(folder_path, '*.txt')

# Find all text files in the folder
text_files = glob.glob(pattern)

# Delete each text file
for file_path in text_files:
    try:
        os.remove(file_path)
        print(f'Deleted {file_path}')
    except OSError as e:
        print(f'Error: {e.strerror} - {file_path}')

Replace '/path/to/your/folder' with the actual path to your folder. This script will delete all .txt files in the specified folder and print a message for each file it deletes. If there's an error (e.g., a file doesn't exist, or you don't have permission to delete a file), it will print an error message.

check GPU in my machine in python

To check for GPUs in your machine using Python, you can utilize libraries that interface with your system's hardware, like torch, tensorflow, or GPUtil. Here’s how you can do it with each of these libraries:

Using PyTorch

If you have PyTorch installed, you can check for GPU availability and details as follows:

import torch

if torch.cuda.is_available():
    print(f"GPU is available.")
    print(f"GPU Name: {torch.cuda.get_device_name(0)}")
    print(f"Total Number of GPUs: {torch.cuda.device_count()}")
else:
    print("GPU is not available.")

Using TensorFlow

With TensorFlow, the method is similar:

import tensorflow as tf

gpus = tf.config.list_physical_devices('GPU')
if gpus:
    for gpu in gpus:
        print(f"GPU is available.")
        print(f"GPU Details: {gpu}")
else:
    print("GPU is not available.")

Using GPUtil

GPUtil is a lightweight Python library for getting the status of your GPUs. First, you need to install GPUtil (pip install GPUtil), then you can use it as follows:

import GPUtil

gpus = GPUtil.getGPUs()
if gpus:
    for gpu in gpus:
        print(f"GPU is available.")
        print(f"GPU ID: {gpu.id}, Name: {gpu.name}")
else:
    print("GPU is not available.")

Each of these methods requires the respective library to be installed in your environment. Choose the one that best fits your installed packages or your project's dependencies.

get uuid of 8 characters in python

Generating a UUID of exactly 8 characters in Python using the standard uuid library doesn't directly fit the UUID standard formats, as UUIDs are typically 32 characters long (excluding hyphens). However, if you need a unique identifier that's only 8 characters long, you can generate a UUID and then take a substring of it, or use other methods to generate a unique string. Keep in mind, shortening the UUID increases the risk of collisions (non-unique values).

Here's how you could generate an 8-character unique identifier by taking the first 8 characters of a UUID:

import uuid

# Generate a UUID and convert to a string
full_uuid = str(uuid.uuid4())

# Take the first 8 characters
short_uuid = full_uuid[:8]

print(short_uuid)

Another approach is to use a hash function and encode the result, but even then, uniqueness isn't guaranteed over a large number of IDs:

import hashlib

# Use a unique value, like a timestamp, as input for the hash function
unique_value = str(uuid.uuid4()).encode('utf-8')

# Generate a hash and take the first 8 characters
short_hash = hashlib.sha256(unique_value).hexdigest()[:8]

print(short_hash)

Remember, the shorter the identifier, the higher the risk of a collision. For truly unique and cryptographically secure identifiers, it's recommended to use the full UUID or another system designed for generating short unique IDs, like nanoid, which you would need to install and use in your Python environment.

shortest possible generated unique id in python

Creating the shortest possible unique ID in Python that guarantees uniqueness within a certain context requires balancing between length and the risk of collision. For most practical purposes, especially if you're looking to minimize the ID length, a commonly used approach is to generate a sufficiently random or hashed value and encode it in a way that uses a high-density character set, such as Base64 or a custom alphabet.

A popular library for generating concise, unique IDs is shortuuid, which provides shorter, URL-friendly UUIDs. It's a wrapper around Python's built-in uuid module but uses a larger alphabet to shorten the length of the ID. This library does not come with Python's standard library, so you would need to install it using pip (pip install shortuuid).

Here's a simple example using shortuuid:

import shortuuid

# Generate a short uuid
short_id = shortuuid.ShortUUID().random(length=8)  # You can specify the desired length

print(short_id)

This will generate a unique ID of the specified length using a safe alphabet. Keep in mind that the shorter the ID, the higher the risk of eventually producing duplicate IDs, especially as the number of generated IDs grows.

For something built-in, you could use a combination of the current time, process ID, and a random component, encoded in a compact form like Base64. However, achieving both uniqueness and shortness without an external library becomes a more complex and less reliable endeavor, especially as the requirements for the ID length become more stringent.

enumerate dictionary python

In Python, you can use the enumerate() function to get both the index and the value when iterating over items like lists. However, dictionaries don't have a fixed order until Python 3.7, where dictionaries were made to maintain insertion order. Even so, enumerate() can still be used with dictionaries for scenarios where you might need the enumeration index along with the key-value pairs.

To enumerate a dictionary, you typically work with its items (key-value pairs), keys, or values. Here's how to use enumerate() with a dictionary's items:

my_dict = {'a': 1, 'b': 2, 'c': 3}

# Enumerating items (key-value pairs)
for index, (key, value) in enumerate(my_dict.items()):
    print(f"Index: {index}, Key: {key}, Value: {value}")

This will output something like:

Index: 0, Key: a, Value: 1
Index: 1, Key: b, Value: 2
Index: 2, Key: c, Value: 3

The enumerate() function wraps around my_dict.items(), which returns an iterator of tuple pairs (each tuple containing a key and its corresponding value). As enumerate() iterates over this, it provides the index (starting from 0 by default) along with each tuple from the dictionary.

You can similarly enumerate over just the keys or the values by using my_dict.keys() or my_dict.values() in place of my_dict.items().

tell me about class static variables and methods

In object-oriented programming, specifically in Python, class static variables and methods are elements that belong to the class itself, rather than to any specific instance of the class. This means they can be accessed without creating an instance of the class. Let's delve into each of them:

Class Static Variables

Static variables (also known as class variables) are shared across all instances of a class. They are defined within a class but outside any of the class’s methods. Since these variables are shared, changing the value of a static variable using one instance changes it for all other instances as well.

class MyClass:
    static_variable = "I am static!"

    def __init__(self, instance_variable):
        self.instance_variable = instance_variable

# Accessing a static variable
print(MyClass.static_variable)  # Directly via class

instance_a = MyClass("Instance A")
instance_b = MyClass("Instance B")

print(instance_a.static_variable)  # Via an instance
MyClass.static_variable = "Changed!"
print(instance_b.static_variable)  # Changed for all instances

Class Static Methods

Static methods in Python are defined using the @staticmethod decorator. A static method does not receive an implicit first argument (self for instance methods or cls for class methods). Consequently, it can't modify object instance state or class state. Static methods are utility functions that perform a task in isolation, not affecting or depending on the class or instance state.

class MyClass:
    @staticmethod
    def my_static_method():
        return "I am static method!"

# Accessing a static method
print(MyClass.my_static_method())  # Directly via class, no need to instantiate

Static methods are used when some functionality is related to the class but does not require the class or its instances to perform its task. This makes them somewhat similar to regular functions, with the key difference being that static methods are grouped with a class because they are logically connected to the class they're defined in.

In summary, class static variables are used for data shared across all instances, and static methods are used for functionality that does not require access to instance or class-specific data.

list files in a folder + python

To list files in a folder using Python, you can use the os module, which provides a portable way of using operating system dependent functionality. Here's a simple example that lists all files in a specified directory:

import os

# Specify the directory you want to list
directory = '/path/to/directory'

# List all files and directories in the specified directory
for filename in os.listdir(directory):
    filepath = os.path.join(directory, filename)
    if os.path.isfile(filepath):
        print(filename)

This script will print the names of all files in the specified directory. If you also want to include directories in the list, you can remove the if os.path.isfile(filepath): condition.

Remember to replace '/path/to/directory' with the actual path of the directory you're interested in.

rename folder's files with index like 1, 2, 3.jpeg

To rename files in a folder with an index, such as "1.jpeg", "2.jpeg", "3.jpeg", etc., you can use Python's os module for interacting with the file system. The following steps outline how to achieve this:

List all files in the folder.
Sort the files if needed to ensure they are renamed in the desired order.
Rename each file using os.rename() with the new name format based on an incrementing index.

Here's how you could implement this:

import os

def rename_files_in_folder(folder_path):
    # Ensure the folder path ends with a '/'
    if not folder_path.endswith('/'):
        folder_path += '/'

    # List all files in the directory and sort them (optional)
    files = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
    files.sort()  # Optional: Sort the files alphabetically. Remove this line if sorting is not required.

    # Rename files
    for index, filename in enumerate(files, start=1):
        # Define the new file name
        new_filename = f"{index}.jpeg"
        # Define the full old and new file paths
        old_file_path = os.path.join(folder_path, filename)
        new_file_path = os.path.join(folder_path, new_filename)
        
        # Rename the file
        os.rename(old_file_path, new_file_path)
        print(f"Renamed '{filename}' to '{new_filename}'")

# Example usage
folder_path = '/path/to/your/folder'
rename_files_in_folder(folder_path)

Before running this script, replace '/path/to/your/folder' with the actual path to your folder. This script will sequentially rename all files in the specified folder to "1.jpeg", "2.jpeg", "3.jpeg", etc., in alphabetical order.

Note: This operation is not reversible through the script, so make sure to backup your files or test in a safe directory if you're unsure about the result. Also, be careful with file extensions; this script assumes all files should end with ".jpeg". Adjust the new_filename format if your files have different extensions or you need to preserve the original extension.

pick random elements as a sublist in python

To pick random elements from a list and create a sublist in Python, you can use the random.sample() function from the random module. This function allows you to specify the number of elements you want to pick from the original list. Here's an example:

import random

# Original list
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# Number of elements you want in the sublist
num_elements = 5

# Generate a random sublist
random_sublist = random.sample(my_list, num_elements)

print(random_sublist)

In this example, random.sample(my_list, num_elements) picks num_elements random, unique elements from my_list and creates a new list containing these elements. This ensures that the picked elements are unique within the returned sublist, but their order is random. If you try to sample more elements than are available in the list (i.e., if num_elements > len(my_list)), random.sample() will raise a ValueError.

append to file python

To append text to an existing file in Python, you can open the file in append mode by using the open() function with the mode 'a'. If the file does not exist, it will be created. Here's a simple example:

# Define the file name
file_name = 'example.txt'

# Text to append to the file
text_to_append = '\nNew line of text.'

# Open the file in append mode and write the text
with open(file_name, 'a') as file:
    file.write(text_to_append)

print(f'Text appended to {file_name}')

This code opens example.txt in append mode ('a') and adds a new line of text to it. The with statement is used to ensure that the file is properly closed after appending the text, even if an error occurs during the operation.

list a method of a module + python

To list all the methods of a module in Python, you can use the dir() function, which returns a list of the attributes and methods of any object (modules, functions, strings, lists, dictionaries, etc.). To filter out methods from a module, you might also want to use the callable() function to check if each attribute is callable (which methods are), and possibly the inspect module to differentiate between functions and other callable objects if necessary.

Here's a basic example using the math module, which is part of Python's standard library:

import math

# List all attributes and methods of the math module
all_attributes = dir(math)

# Filter out only the methods (callable attributes)
methods = [attr for attr in all_attributes if callable(getattr(math, attr))]

print(methods)

This script lists all callable attributes of the math module, which includes functions (methods in the context of modules are essentially functions defined within the module).

For more refined control, especially to distinguish between different types of callables, you can use the inspect module:

import math
import inspect

# Filter for methods, excluding any built-in functions or methods
methods = [attr for attr in dir(math) if inspect.isfunction(getattr(math, attr))]

print(methods)

This approach specifically filters for functions defined in the module, ignoring built-in functions or callable objects that aren't functions. This can be more accurate depending on what you're looking for when you say "methods".

NextPy Notes 2

Last updated 1 year ago

a (Append)

a+ (Append and Read)

w (Write)

w+ (Write and Read)

r+ (Read and Write)

Using the list() Constructor