Don't Confuse to learn Python.
Learn This Concept to be proficient in Python.
๐๐ฎ๐๐ถ๐ฐ๐ ๐ผ๐ณ ๐ฃ๐๐๐ต๐ผ๐ป:
- Python Syntax
- Data Types
- Variables
- Operators
- Control Structures:
if-elif-else
Loops
Break and Continue
try-except block
- Functions
- Modules and Packages
๐ข๐ฏ๐ท๐ฒ๐ฐ๐-๐ข๐ฟ๐ถ๐ฒ๐ป๐๐ฒ๐ฑ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ด ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Classes and Objects
- Inheritance
- Polymorphism
- Encapsulation
- Abstraction
๐ฃ๐๐๐ต๐ผ๐ป ๐๐ถ๐ฏ๐ฟ๐ฎ๐ฟ๐ถ๐ฒ๐:
- Pandas
- Numpy
๐ฃ๐ฎ๐ป๐ฑ๐ฎ๐:
- What is Pandas?
- Installing Pandas
- Importing Pandas
- Pandas Data Structures (Series, DataFrame, Index)
๐ช๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐๐ฎ๐๐ฎ๐๐ฟ๐ฎ๐บ๐ฒ๐:
- Creating DataFrames
- Accessing Data in DataFrames
- Filtering and Selecting Data
- Adding and Removing Columns
- Merging and Joining DataFrames
- Grouping and Aggregating Data
- Pivot Tables
๐๐ฎ๐๐ฎ ๐๐น๐ฒ๐ฎ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Handling Missing Values
- Handling Duplicates
- Data Formatting
- Data Transformation
- Data Normalization
๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ ๐ง๐ผ๐ฝ๐ถ๐ฐ๐:
- Handling Large Datasets with Dask
- Handling Categorical Data with Pandas
- Handling Text Data with Pandas
- Using Pandas with Scikit-learn
- Performance Optimization with Pandas
๐๐ฎ๐๐ฎ ๐ฆ๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ๐ ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Lists
- Tuples
- Dictionaries
- Sets
๐๐ถ๐น๐ฒ ๐๐ฎ๐ป๐ฑ๐น๐ถ๐ป๐ด ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Reading and Writing Text Files
- Reading and Writing Binary Files
- Working with CSV Files
- Working with JSON Files
๐ก๐๐บ๐ฝ๐:
- What is NumPy?
- Installing NumPy
- Importing NumPy
- NumPy Arrays
๐ก๐๐บ๐ฃ๐ ๐๐ฟ๐ฟ๐ฎ๐ ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐:
- Creating Arrays
- Accessing Array Elements
- Slicing and Indexing
- Reshaping Arrays
- Combining Arrays
- Splitting Arrays
- Arithmetic Operations
- Broadcasting
๐ช๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐๐ฎ๐๐ฎ ๐ถ๐ป ๐ก๐๐บ๐ฃ๐:
- Reading and Writing Data with NumPy
- Filtering and Sorting Data
- Data Manipulation with NumPy
- Interpolation
- Fourier Transforms
- Window Functions
๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐ข๐ฝ๐๐ถ๐บ๐ถ๐๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐ต ๐ก๐๐บ๐ฃ๐:
- Vectorization
- Memory Management
- Multithreading and Multiprocessing
- Parallel Computing
Like this post if you need more resources like this ๐โค๏ธ
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Learn This Concept to be proficient in Python.
๐๐ฎ๐๐ถ๐ฐ๐ ๐ผ๐ณ ๐ฃ๐๐๐ต๐ผ๐ป:
- Python Syntax
- Data Types
- Variables
- Operators
- Control Structures:
if-elif-else
Loops
Break and Continue
try-except block
- Functions
- Modules and Packages
๐ข๐ฏ๐ท๐ฒ๐ฐ๐-๐ข๐ฟ๐ถ๐ฒ๐ป๐๐ฒ๐ฑ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ด ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Classes and Objects
- Inheritance
- Polymorphism
- Encapsulation
- Abstraction
๐ฃ๐๐๐ต๐ผ๐ป ๐๐ถ๐ฏ๐ฟ๐ฎ๐ฟ๐ถ๐ฒ๐:
- Pandas
- Numpy
๐ฃ๐ฎ๐ป๐ฑ๐ฎ๐:
- What is Pandas?
- Installing Pandas
- Importing Pandas
- Pandas Data Structures (Series, DataFrame, Index)
๐ช๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐๐ฎ๐๐ฎ๐๐ฟ๐ฎ๐บ๐ฒ๐:
- Creating DataFrames
- Accessing Data in DataFrames
- Filtering and Selecting Data
- Adding and Removing Columns
- Merging and Joining DataFrames
- Grouping and Aggregating Data
- Pivot Tables
๐๐ฎ๐๐ฎ ๐๐น๐ฒ๐ฎ๐ป๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป:
- Handling Missing Values
- Handling Duplicates
- Data Formatting
- Data Transformation
- Data Normalization
๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ ๐ง๐ผ๐ฝ๐ถ๐ฐ๐:
- Handling Large Datasets with Dask
- Handling Categorical Data with Pandas
- Handling Text Data with Pandas
- Using Pandas with Scikit-learn
- Performance Optimization with Pandas
๐๐ฎ๐๐ฎ ๐ฆ๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ๐ ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Lists
- Tuples
- Dictionaries
- Sets
๐๐ถ๐น๐ฒ ๐๐ฎ๐ป๐ฑ๐น๐ถ๐ป๐ด ๐ถ๐ป ๐ฃ๐๐๐ต๐ผ๐ป:
- Reading and Writing Text Files
- Reading and Writing Binary Files
- Working with CSV Files
- Working with JSON Files
๐ก๐๐บ๐ฝ๐:
- What is NumPy?
- Installing NumPy
- Importing NumPy
- NumPy Arrays
๐ก๐๐บ๐ฃ๐ ๐๐ฟ๐ฟ๐ฎ๐ ๐ข๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐:
- Creating Arrays
- Accessing Array Elements
- Slicing and Indexing
- Reshaping Arrays
- Combining Arrays
- Splitting Arrays
- Arithmetic Operations
- Broadcasting
๐ช๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐๐ฎ๐๐ฎ ๐ถ๐ป ๐ก๐๐บ๐ฃ๐:
- Reading and Writing Data with NumPy
- Filtering and Sorting Data
- Data Manipulation with NumPy
- Interpolation
- Fourier Transforms
- Window Functions
๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐ข๐ฝ๐๐ถ๐บ๐ถ๐๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐ต ๐ก๐๐บ๐ฃ๐:
- Vectorization
- Memory Management
- Multithreading and Multiprocessing
- Parallel Computing
Like this post if you need more resources like this ๐โค๏ธ
#Python
@CodingCoursePro
Shared with Love
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Create a telegram bot to scan IP/host/websites (enter the IP and get the fastest open port report)
Create Telegram bot Scan.py:
โก๏ธ First, install the necessary libraries:
โก๏ธ Create a file Filename.py
โก๏ธ Go to BotFather and create a new Telegram Bot
โก๏ธ Save the script as Filename.py Source
โก๏ธ Execute the 'Scan.py' script, and visit your Telegram bot, type '/start' to receive the welcome message.
โก๏ธ Pass the IP/host and get open ports, service and versions.
#nmap @NxSMind #python_Telegram_Bot
@CodingCoursePro
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NOTE: This post serves as a demonstration for creating a Python application. I do not endorse spamming or violating the terms or services of any individuals.
Create Telegram bot Scan.py:
โก๏ธ First, install the necessary libraries:
$ pip install python-telegram-bot==13.7
$ pip install python-nmap
โก๏ธ Create a file Filename.py
โก๏ธ Go to BotFather and create a new Telegram Bot
โก๏ธ Save the script as Filename.py Source
import telegram
from telegram.ext import Updater, CommandHandler, MessageHandler, Filters
import nmap
bot = telegram.Bot(token='8371237947:Aeo3bq8qEJP2kipYIPC_JhwFOIGk5bU')
updater = Updater('8371237947:Aeo3bq8qEJP2kipYIPC_JhwFOIGk5bU', use_context=True)
dispatcher = updater.dispatcher
nm = nmap.PortScanner()
def start(update, context):
context.bot.send_message(chat_id=update.effective_chat.id, text="Welcome there ! Please pass the IP or Host.")
def scan(update, context):
try:
target = update.message.text
nm.scan(hosts=target, arguments='-T4 -F')
scan_result = ''
for host in nm.all_hosts():
scan_result += f"Host: {host}\n"
for proto in nm[host].all_protocols():
ports = nm[host][proto].keys()
for port in ports:
port_info = nm[host][proto][port]
scan_result += f"Port: {port} State: {port_info['state']} Service: {port_info['name']}"
if 'product' in port_info:
scan_result += f", Version: {port_info['product']}"
scan_result += "\n"
context.bot.send_message(chat_id=update.effective_chat.id, text=scan_result)
except Exception as e:
context.bot.send_message(chat_id=update.effective_chat.id, text=f"Error: {str(e)}")
start_handler = CommandHandler('start', start)
dispatcher.add_handler(start_handler)
message_handler = MessageHandler(Filters.text & ~Filters.command, scan)
dispatcher.add_handler(message_handler)
updater.start_polling()
updater.idle()
โก๏ธ Execute the 'Scan.py' script, and visit your Telegram bot, type '/start' to receive the welcome message.
โก๏ธ Pass the IP/host and get open ports, service and versions.
#nmap @NxSMind #python_Telegram_Bot
@CodingCoursePro
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