#python 3 modules

[cosmogyros]

Thank you so much for this guide! I have one question for OP or anyone else who's done this successfully:

When it comes to installing the dependencies, e.g. the line: pip install tumblr-backup[video] ...my command line doesn't seem to like the square brackets. (At least, I'm assuming they're the problem here.)

When I try to enter that command, I get this error: zsh: no matches found: tumblr-backup[video]

Has anybody else had a similar experience? Am I doing something wrong? Are you not actually supposed to type the square brackets verbatim?

FWIW I'm doing this on macOS, not Linux, but all the commands look familiar so I think it ought to work if I can get over this one hurdle...

ETA: I know square brackets on the command line indicate something optional, but in that case, what do I actually type? Neither "pip install tumblr-backup video", with a space, nor "pip install tumblr-backupvideo", without a space, seem to work.

Quick Tumblr Backup Guide (Linux)

Go to www.tumblr.com/oauth/apps and click the "Register Application" button

Fill in the form. I used the following values for the required fields: Application Name - tumblr-arch Application Website - https://github.com/Cebtenzzre/tumblr-utils Application Description - tumblr archival instance based on tumblr-utils Adminstrative contact email - < my personal email > Default callback URL - https://github.com/Cebtenzzre/tumblr-utils OAuth2 redirect URLs - https://github.com/Cebtenzzre/tumblr-utils

Get the OAuth Consumer Key for your application. It should be listed right on the www.tumblr.com/oauth/apps page.

Do python things:

# check python version: python --version # I've got Python 3.9.9 # create a venv: python -m venv --prompt tumblr-bkp --upgrade-deps venv # activate the venv: source venv/bin/activate # install dependencies: pip install tumblr-backup pip install tumblr-backup[video] pip install tumblr-backup[jq] pip install tumblr-backup[bs4] # Check dependencies are all installed: pip freeze # set the api key: tumblr-backup --set-api-key <OAuth Consumer Key>

So far I have backed up two blogs using the following:

tumblr-backup --save-audio --save-video --tag-index --save-notes --incremental -j --no-post-clobber --media-list <blog name>

There have been two issues I had to deal with so far:

one of the blogs was getting a "Non-OK API repsonse: HTTP 401 Unauthorized". It further stated that "This is a dashboard-only blog, so you probably don't have the right cookies. Try --cookiefile." I resolved the issue by a) setting the "Hide from people without an account" to off and b) enabling a custom theme. I think only step a) was actually necessary though.

"Newly registered consumers are rate limited to 1,000 requests per hour, and 5,000 requests per day. If your application requires more requests for either of these periods, please use the 'Request rate limit removal' link on an app above." Depending on how big your blog is, you may need to break up the download. I suspect using the "-n COUNT" or "--count COUNT" to save only COUNT posts at a time, combined with the "--incremental" will allow you to space things out. You would have to perform multiple passes though. I will have to play with that, so I'll report back my findings.

[a-fox-studies]

March 5, 2025 • Wednesday

--- 30 days of productivity • COLLAB CHALLENGE WITH @studaxy • Day 26/30 ---

💛 Axy's productive time: 1h 32min

💙 Iris's study time: 2h

Today I did an activity because I was bored. My textbook said that implementing the "finding GCD of numbers by prime factorization method" into a program is hard, and I went "are you challenging me?"

So yeah I spent the day doing that and turns out it was pretty hard lol XD but! I ended up succeeding!

Also, I learned about the Counter module in python, which creates a dictionary of items — the keys being the elements of an iterable passed to it, and the values being the number of occurrences of the key in the iterable. So that was fun :3

[ixhika-jsx]

BLACK SWAN- ✧˖°BTS Challenge - 𐙚

Main concept: of this challenge is that I have to bring my passions back to life that died long ago

Bit inspired by @zzzzzestforlife 🍾🫶🏻

As in song's lyrics of 'black swan'

"If this can no longer resonate, no longer make my heart vibrate, then like this may be how I die my first death."

[ You can reblog this post and start this challenge by yourself after adding your own goals under the reblogged post of yours... :)) ]

[ Academics:- ᥫ᭡🎐

As to bring back my interest in studies there are some goals of mine and some tips (I am referring myself as 'you' as some external force for myself) 🎀

☆ By the mid of September you must be on track in academics - complete notes and zero backlogs , regular revision ! 📄❕️❕️

☆ 📌 Complete pw modules till December

☆ work on weak chapters🗯 - relation and functions , trigonometry , periodic classification and topic electronic configuration of chapter - 2 of chemistry 💨

☆ listen to podcasts like 'ACADEMIC VALIDATION'🗒and 'YOUR A+ LIFE'📈 while studying mathematics. (As I kinda not get maths yk )

☆ study along with study vloggers - 'STUDY WITH ME' 🩰 because it helps when you find a 'partner' in studying.

☆ Have a mindset that you are not a student but you are a employee working for a greater position in your job or for greater income....🏷 which means position- topper or sum and income - grades ⏳️

☆ while studying physics you should use whiteboard 📇cuz I know it gets boring at times so yea

☆ for chemistry I would say that read books and make pretty pretty notes 🪄 and if you still can't study it then just watch some study vlogs and restart 🎲 (it helps me sometimes)

☆ study computer science chapter of - 'PYTHON' 🖥 whenever you get time as of getting mind off STEM subjects

[ Workout :- ᥫ᭡ 🎳

☆ I know it's not easy getting off bed but just use 1-2-5 minute rule 🎗

-stand up for 1 minute and drink some water

- start off with some stretching next for 2 minutes

- do 4 plank sessions in 5 minutes or any other favourite exercise move of yours

(This is my concept btw) And this will help about 70 percent to actually get you up.🥊

☆ do pilates in case you don't feel like exercising⛳️

☆ do 'lazy' stretching either before sleeping ot after sleeping.🎯

☆ walk minimum 6k steps a day♠️

[ Hobbies/Extra curricular :- ᥫ᭡ 🎱

☆ subscribe/follow to multiple dance pages so you automatically get the urge to dance🪀

☆ watch your idol dancing...it helps🧩

☆ dance atleast twice a week no matter what , even if you have to force it. It will individually get better if you were some day passionate bout it once.👯🏻‍♀️

☆ start writing your incomplete book by visualizing the scenes of the book...may help sometimes🖇

☆ during breaks from studies play basketball even for 5 minutes... put your phone away and walk around with your basketball around you then you will automatically feel the urge.🏀

☆ take part in school activities as much as you can....I get it that there is lot of academic work but it shouldn't stop you from being an all rounder🏆🏅

[ Social :- ᥫ᭡🥂

☆ cut people off...yea exactly CUT THEM OFF !! Lot of people don't really deserve you. You know who those people are.🌬

☆ don't get too comfy with some people. I get it that its your nature but keep that aside rn because it can be pressuring your self respect.🛑

☆ cut off atleast 3 people this year (atleast)💬

☆ don't be too kind to endure every other 'tease' of thiers. No this degrades your self respect and standards✋🏻

☆ if they are constantly mean then cut them off or just give them what they deserve(be the karma).🗣

☆ be as much confident as you can.you know nothing is cringe.... your definition of cringe is limiting you from your potential.🧭

So this is it for this challenge. I will regularly add more goals if needed and keep on updating my process.

You all are free to join :))🍾💐

[megumi-fm]

👾 this fortnight in megumi.fm

---🎓 a c a d e m i c 🎓---

🔓 Achievement Unlocked: graduate soon?🏆 — the player has cleared most undergrad requirements → completed all classes for undergrad degree → completed three month requirement of internship ⭐ LEVEL UP >> bi in biotechnology — the player has gotten admission into their fav uni for masters 📍 new level completion requirements 🔄 offer letter acceptance tasks [1/3] ▸ accommodation related paperwork ▸ student visa

--- 💻 w o r k 💻---

🎯 bi-weekly challenge complete! ✅ run binding site alignment against template ✅ run binding site alignment against self ✅ threshold cutoff 📌next week's task: visualization on cytoscape [💬 view all challenges?] ⭐LEVEL UP >> snake charmer 🏆 — the player has achieved intermediate level mastery in python -> completed debugging of all code -> added modules for system arg-parsing -> upload to github with proper readme 3/6 months of remaining internship to unlock achievement —⚗️sorcerer's apprentice

--- 💊 u s e r - s t a t s 💊---

key: ◆ - completed / ◇ - not done 📅 tracking [◆◆◆◆◆◆◆◆◆◆◆◆◆◆] 🍶 2L+ water [◆◇◇◇◇◆◆◆◆◆◆◆◆◆] 👟 movement [◆◆◆◆◆◆◆◇◇◇◆◆◆◆] ⭐ LEVEL UP >> amateur compass — the player has learnt choreography of SVT's Left & Right

--- 🎲 recreation 🎲 ---

📺 watched Kung Fu Panda in theatres 🍰 birthday celebrations 📖 read Tomorrow and Tomorrow and Tomorrow by Gabrielle Zevin

——— [1st - 14th Apr; week 15+16/52 || I had the time of my life making this post xD the last couple weeks have been pretty fun, and I'm nearing the end of my degree, I'm anxious and excited for what's to come xD. also this post is very much inspired by the achievement unlocked concept in @zzzzzestforlife's lil animal crossing tag game post they just always have the best post formats and concepts I'm in love ]

[sak-shi]

Python Libraries to Learn Before Tackling Data Analysis

To tackle data analysis effectively in Python, it's crucial to become familiar with several libraries that streamline the process of data manipulation, exploration, and visualization. Here's a breakdown of the essential libraries:

 1. NumPy

   - Purpose: Numerical computing.

   - Why Learn It: NumPy provides support for large multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays efficiently.

   - Key Features:

     - Fast array processing.

     - Mathematical operations on arrays (e.g., sum, mean, standard deviation).

     - Linear algebra operations.

 2. Pandas

   - Purpose: Data manipulation and analysis.

   - Why Learn It: Pandas offers data structures like DataFrames, making it easier to handle and analyze structured data.

   - Key Features:

     - Reading/writing data from CSV, Excel, SQL databases, and more.

     - Handling missing data.

     - Powerful group-by operations.

     - Data filtering and transformation.

 3. Matplotlib

   - Purpose: Data visualization.

   - Why Learn It: Matplotlib is one of the most widely used plotting libraries in Python, allowing for a wide range of static, animated, and interactive plots.

   - Key Features:

     - Line plots, bar charts, histograms, scatter plots.

     - Customizable charts (labels, colors, legends).

     - Integration with Pandas for quick plotting.

 4. Seaborn

   - Purpose: Statistical data visualization.

   - Why Learn It: Built on top of Matplotlib, Seaborn simplifies the creation of attractive and informative statistical graphics.

   - Key Features:

     - High-level interface for drawing attractive statistical graphics.

     - Easier to use for complex visualizations like heatmaps, pair plots, etc.

     - Visualizations based on categorical data.

 5. SciPy

   - Purpose: Scientific and technical computing.

   - Why Learn It: SciPy builds on NumPy and provides additional functionality for complex mathematical operations and scientific computing.

   - Key Features:

     - Optimized algorithms for numerical integration, optimization, and more.

     - Statistics, signal processing, and linear algebra modules.

 6. Scikit-learn

   - Purpose: Machine learning and statistical modeling.

   - Why Learn It: Scikit-learn provides simple and efficient tools for data mining, analysis, and machine learning.

   - Key Features:

     - Classification, regression, and clustering algorithms.

     - Dimensionality reduction, model selection, and preprocessing utilities.

 7. Statsmodels

   - Purpose: Statistical analysis.

   - Why Learn It: Statsmodels allows users to explore data, estimate statistical models, and perform tests.

   - Key Features:

     - Linear regression, logistic regression, time series analysis.

     - Statistical tests and models for descriptive statistics.

 8. Plotly

   - Purpose: Interactive data visualization.

   - Why Learn It: Plotly allows for the creation of interactive and web-based visualizations, making it ideal for dashboards and presentations.

   - Key Features:

     - Interactive plots like scatter, line, bar, and 3D plots.

     - Easy integration with web frameworks.

     - Dashboards and web applications with Dash.

 9. TensorFlow/PyTorch (Optional)

   - Purpose: Machine learning and deep learning.

   - Why Learn It: If your data analysis involves machine learning, these libraries will help in building, training, and deploying deep learning models.

   - Key Features:

     - Tensor processing and automatic differentiation.

     - Building neural networks.

 10. Dask (Optional)

   - Purpose: Parallel computing for data analysis.

   - Why Learn It: Dask enables scalable data manipulation by parallelizing Pandas operations, making it ideal for big datasets.

   - Key Features:

     - Works with NumPy, Pandas, and Scikit-learn.

     - Handles large data and parallel computations easily.

Focusing on NumPy, Pandas, Matplotlib, and Seaborn will set a strong foundation for basic data analysis.

[zooplekochi]

Automate Simple Tasks Using Python: A Beginner’s Guide

In today's fast paced digital world, time is money. Whether you're a student, a professional, or a small business owner, repetitive tasks can eat up a large portion of your day. The good news? Many of these routine jobs can be automated, saving you time, effort, and even reducing the chance of human error.

Enter Python a powerful, beginner-friendly programming language that's perfect for task automation. With its clean syntax and massive ecosystem of libraries, Python empowers users to automate just about anything from renaming files and sending emails to scraping websites and organizing data.

If you're new to programming or looking for ways to boost your productivity, this guide will walk you through how to automate simple tasks using Python.

🌟 Why Choose Python for Automation?

Before we dive into practical applications, let’s understand why Python is such a popular choice for automation:

Easy to learn: Python has simple, readable syntax, making it ideal for beginners.

Wide range of libraries: Python has a rich ecosystem of libraries tailored for different tasks like file handling, web scraping, emailing, and more.

Platform-independent: Python works across Windows, Mac, and Linux.

Strong community support: From Stack Overflow to GitHub, you’ll never be short on help.

Now, let’s explore real-world examples of how you can use Python to automate everyday tasks.

🗂 1. Automating File and Folder Management

Organizing files manually can be tiresome, especially when dealing with large amounts of data. Python’s built-in os and shutil modules allow you to automate file operations like:

Renaming files in bulk

Moving files based on type or date

Deleting unwanted files

Example: Rename multiple files in a folder

import os folder_path = 'C:/Users/YourName/Documents/Reports' for count, filename in enumerate(os.listdir(folder_path)): dst = f"report_{str(count)}.pdf" src = os.path.join(folder_path, filename) dst = os.path.join(folder_path, dst) os.rename(src, dst)

This script renames every file in the folder with a sequential number.

📧 2. Sending Emails Automatically

Python can be used to send emails with the smtplib and email libraries. Whether it’s sending reminders, reports, or newsletters, automating this process can save you significant time.

Example: Sending a basic email

import smtplib from email.message import EmailMessage msg = EmailMessage() msg.set_content("Hello, this is an automated email from Python!") msg['Subject'] = 'Automation Test' msg['From'] = 'you@example.com' msg['To'] = 'recipient@example.com' with smtplib.SMTP_SSL('smtp.gmail.com', 465) as smtp: smtp.login('you@example.com', 'yourpassword') smtp.send_message(msg)

⚠️ Note: Always secure your credentials when writing scripts consider using environment variables or secret managers.

🌐 3. Web Scraping for Data Collection

Want to extract information from websites without copying and pasting manually? Python’s requests and BeautifulSoup libraries let you scrape content from web pages with ease.

Example: Scraping news headlines

import requests from bs4 import BeautifulSoup url = 'https://www.bbc.com/news' response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') for headline in soup.find_all('h3'): print(headline.text)

This basic script extracts and prints the headlines from BBC News.

📅 4. Automating Excel Tasks

If you work with Excel sheets, you’ll love openpyxl and pandas two powerful libraries that allow you to automate:

Creating spreadsheets

Sorting data

Applying formulas

Generating reports

Example: Reading and filtering Excel data

import pandas as pd df = pd.read_excel('sales_data.xlsx') high_sales = df[df['Revenue'] > 10000] print(high_sales)

This script filters sales records with revenue above 10,000.

💻 5. Scheduling Tasks

You can schedule scripts to run at specific times using Python’s schedule or APScheduler libraries. This is great for automating daily reports, reminders, or file backups.

Example: Run a function every day at 9 AM

import schedule import time def job(): print("Running scheduled task...") schedule.every().day.at("09:00").do(job) while True: schedule.run_pending() time.sleep(1)

This loop checks every second if it’s time to run the task.

🧹 6. Cleaning and Formatting Data

Cleaning data manually in Excel or Google Sheets is time-consuming. Python’s pandas makes it easy to:

Remove duplicates

Fix formatting

Convert data types

Handle missing values

Example: Clean a dataset

df = pd.read_csv('data.csv') df.drop_duplicates(inplace=True) df['Name'] = df['Name'].str.title() df.fillna(0, inplace=True) df.to_csv('cleaned_data.csv', index=False)

💬 7. Automating WhatsApp Messages (for fun or alerts)

Yes, you can even send WhatsApp messages using Python! Libraries like pywhatkit make this possible.

Example: Send a WhatsApp message

import pywhatkit pywhatkit.sendwhatmsg("+911234567890", "Hello from Python!", 15, 0)

This sends a message at 3:00 PM. It’s great for sending alerts or reminders.

🛒 8. Automating E-Commerce Price Tracking

You can use web scraping and conditionals to track price changes of products on sites like Amazon or Flipkart.

Example: Track a product’s price

url = "https://www.amazon.in/dp/B09XYZ123" headers = {"User-Agent": "Mozilla/5.0"} page = requests.get(url, headers=headers) soup = BeautifulSoup(page.content, 'html.parser') price = soup.find('span', {'class': 'a-price-whole'}).text print(f"The current price is ₹{price}")

With a few tweaks, you can send yourself alerts when prices drop.

📚 Final Thoughts

Automation is no longer a luxury it’s a necessity. With Python, you don’t need to be a coding expert to start simplifying your life. From managing files and scraping websites to sending e-mails and scheduling tasks, the possibilities are vast.

As a beginner, start small. Pick one repetitive task and try automating it. With every script you write, your confidence and productivity will grow.

Conclusion

If you're serious about mastering automation with Python, Zoople Technologies offers comprehensive, beginner-friendly Python course in Kerala. Our hands-on training approach ensures you learn by doing with real-world projects that prepare you for today’s tech-driven careers.

[digitaldetoxworld]

Python Programming Language: A Comprehensive Guide

 Python is one of the maximum widely used and hastily growing programming languages within the world. Known for its simplicity, versatility, and great ecosystem, Python has become the cross-to desire for beginners, professionals, and organizations across industries.

What is Python used for

🐍 What is Python?

Python is a excessive-stage, interpreted, fashionable-purpose programming language.  The language emphasizes clarity, concise syntax, and code simplicity, making it an excellent device for the whole lot from web development to synthetic intelligence.

Its syntax is designed to be readable and easy, regularly described as being near the English language. This ease of information has led Python to be adopted no longer simplest through programmers but also by way of scientists, mathematicians, and analysts who may not have a formal heritage in software engineering.

📜 Brief History of Python

Late Nineteen Eighties: Guido van Rossum starts work on Python as a hobby task.

1991: Python zero.9.0 is released, presenting classes, functions, and exception managing.

2000: Python 2.Zero is launched, introducing capabilities like list comprehensions and rubbish collection.

2008: Python 3.Zero is launched with considerable upgrades but breaks backward compatibility.

2024: Python three.12 is the modern day strong model, enhancing performance and typing support.

⭐ Key Features of Python

Easy to Learn and Use:

Python's syntax is simple and similar to English, making it a high-quality first programming language.

Interpreted Language:

Python isn't always compiled into device code; it's far done line by using line the usage of an interpreter, which makes debugging less complicated.

Cross-Platform:

Python code runs on Windows, macOS, Linux, and even cell devices and embedded structures.

Dynamic Typing:

Variables don’t require explicit type declarations; types are decided at runtime.

Object-Oriented and Functional:

Python helps each item-orientated programming (OOP) and practical programming paradigms.

Extensive Standard Library:

Python includes a rich set of built-in modules for string operations, report I/O, databases, networking, and more.

Huge Ecosystem of Libraries:

From data technological know-how to net development, Python's atmosphere consists of thousands of programs like NumPy, pandas, TensorFlow, Flask, Django, and many greater.

📌 Basic Python Syntax

Here's an instance of a easy Python program:

python

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Edit

def greet(call):

    print(f"Hello, call!")

greet("Alice")

Output:

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Edit

Hello, Alice!

Key Syntax Elements:

Indentation is used to define blocks (no curly braces  like in different languages).

Variables are declared via task: x = 5

Comments use #:

# This is a remark

Print Function:

print("Hello")

📊 Python Data Types

Python has several built-in data kinds:

Numeric: int, go with the flow, complicated

Text: str

Boolean: bool (True, False)

Sequence: listing, tuple, range

Mapping: dict

Set Types: set, frozenset

Example:

python

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age = 25             # int

name = "John"        # str

top = 5.Nine         # drift

is_student = True    # bool

colors = ["red", "green", "blue"]  # listing

🔁 Control Structures

Conditional Statements:

python

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if age > 18:

    print("Adult")

elif age == 18:

    print("Just became an person")

else:

    print("Minor")

Loops:

python

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for color in hues:

    print(coloration)

while age < 30:

    age += 1

🔧 Functions and Modules

Defining a Function:

python

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def upload(a, b):

    return a + b

Importing a Module:

python

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import math

print(math.Sqrt(sixteen))  # Output: four.0

🗂️ Object-Oriented Programming (OOP)

Python supports OOP functions such as lessons, inheritance, and encapsulation.

Python

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elegance Animal:

    def __init__(self, call):

        self.Call = name

def communicate(self):

        print(f"self.Call makes a valid")

dog = Animal("Dog")

dog.Speak()  # Output: Dog makes a legitimate

🧠 Applications of Python

Python is used in nearly each area of era:

1. Web Development

Frameworks like Django, Flask, and FastAPI make Python fantastic for building scalable web programs.

2. Data Science & Analytics

Libraries like pandas, NumPy, and Matplotlib permit for data manipulation, evaluation, and visualization.

Three. Machine Learning & AI

Python is the dominant language for AI, way to TensorFlow, PyTorch, scikit-research, and Keras.

4. Automation & Scripting

Python is extensively used for automating tasks like file managing, device tracking, and data scraping.

Five. Game Development

Frameworks like Pygame allow builders to build simple 2D games.

6. Desktop Applications

With libraries like Tkinter and PyQt, Python may be used to create cross-platform computing device apps.

7. Cybersecurity

Python is often used to write security equipment, penetration trying out scripts, and make the most development.

📚 Popular Python Libraries

NumPy: Numerical computing

pandas: Data analysis

Matplotlib / Seaborn: Visualization

scikit-study: Machine mastering

BeautifulSoup / Scrapy: Web scraping

Flask / Django: Web frameworks

OpenCV: Image processing

PyTorch / TensorFlow: Deep mastering

SQLAlchemy: Database ORM

💻 Python Tools and IDEs

Popular environments and tools for writing Python code encompass:

PyCharm: Full-featured Python IDE.

VS Code: Lightweight and extensible editor.

Jupyter Notebook: Interactive environment for statistics technological know-how and studies.

IDLE: Python’s default editor.

🔐 Strengths of Python

Easy to study and write

Large community and wealthy documentation

Extensive 0.33-birthday celebration libraries

Strong support for clinical computing and AI

Cross-platform compatibility

⚠️ Limitations of Python

Slower than compiled languages like C/C++

Not perfect for mobile app improvement

High memory usage in massive-scale packages

GIL (Global Interpreter Lock) restricts genuine multithreading in CPython

🧭 Learning Path for Python Beginners

Learn variables, facts types, and control glide.

Practice features and loops.

Understand modules and report coping with.

Explore OOP concepts.

Work on small initiatives (e.G., calculator, to-do app).

Dive into unique areas like statistics technological know-how, automation, or web development.

[sindhu14]

What is Python, How to Learn Python?

What is Python?

Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used in various fields like: ✅ Web Development (Django, Flask) ✅ Data Science & Machine Learning (Pandas, NumPy, TensorFlow) ✅ Automation & Scripting (Web scraping, File automation) ✅ Game Development (Pygame) ✅ Cybersecurity & Ethical Hacking ✅ Embedded Systems & IoT (MicroPython)

Python is beginner-friendly because of its easy-to-read syntax, large community, and vast library support.

How Long Does It Take to Learn Python?

The time required to learn Python depends on your goals and background. Here’s a general breakdown:

1. Basics of Python (1-2 months)

If you spend 1-2 hours daily, you can master:

Variables, Data Types, Operators

Loops & Conditionals

Functions & Modules

Lists, Tuples, Dictionaries

File Handling

Basic Object-Oriented Programming (OOP)

2. Intermediate Level (2-4 months)

Once comfortable with basics, focus on:

Advanced OOP concepts

Exception Handling

Working with APIs & Web Scraping

Database handling (SQL, SQLite)

Python Libraries (Requests, Pandas, NumPy)

Small real-world projects

3. Advanced Python & Specialization (6+ months)

If you want to go pro, specialize in:

Data Science & Machine Learning (Matplotlib, Scikit-Learn, TensorFlow)

Web Development (Django, Flask)

Automation & Scripting

Cybersecurity & Ethical Hacking

Learning Plan Based on Your Goal

📌 Casual Learning – 3-6 months (for automation, scripting, or general knowledge) 📌 Professional Development – 6-12 months (for jobs in software, data science, etc.) 📌 Deep Mastery – 1-2 years (for AI, ML, complex projects, research)

Scope @ NareshIT:

At NareshIT’s Python application Development program you will be able to get the extensive hands-on training in front-end, middleware, and back-end technology.

It skilled you along with phase-end and capstone projects based on real business scenarios.

Here you learn the concepts from leading industry experts with content structured to ensure industrial relevance.

An end-to-end application with exciting features

Earn an industry-recognized course completion certificate.

For more details:

[xpc-web-dev]

Studying code calmly and avoiding a burnout. Day 1

If you saw a list of tasks that I said I would do until 23:59 on Sunday, you realized that was a lot for 3 days.

And guess what, he almost had a burnout of his own doing? Myself IEEJIJEIJIE

Yesterday, learning with my elders and colleagues, I understood that I wanted to do a lot of things and almost had my third burnout just to show the recruiter what I can do if I pass the process I want.

BUT it won't do me any good to have a github full of repositories, if I have a burnout and I don't want to touch the code and it gets worse if I'm in a work process because then I'm going to miss a hell of a chance because in the past I've done more than that I could.

SO today Monday I set myself small goals.

[ ] Finish the 1 module Javascript course

[ ] Take the Introduction to computer science with python (1 and 2)

[ ] Object orientation with python

[ ] Project 1 final with Html, css and bootstrap + a bootstrap course individual

I changed plans and that lightened the load. Now I think I can handle it and not freak out.

I will try to make daily updates. I want to be proud of myself in the future when I look at all this bullshit bounout, frustration, etc. And I also share it here for the sake of ego/vanity and wanting to be heard/seen. Which is fine, as long as it's not hurting anyone.

(I don't need any advice comments about ego and vanity. I already have someone to teach me about and I deal very well with my shadows, thank you.)

I wish you a great week, drink water, sunbathe if possible and don't give up.

[education43]

What Are the Qualifications for a Data Scientist?

In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.

The Key Qualifications for a Data Scientist

To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:

1. Educational Background

A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.

2. Proficiency in Programming Languages

Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.

3. Understanding of Machine Learning

Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.

4. Data Wrangling Skills

Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.

5. Statistical Knowledge

Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.

6. Communication and Data Visualization Skills

Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.

7. Domain Knowledge

Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.

Why Choose DataCouncil for a Data Science Course in Pune?

If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:

Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.

Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.

Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.

100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.

Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.

Conclusion

Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.

Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!

[acorgiirl]

Project Euler #2

Welcome back to my series on Project Euler problems. HackerRank Lets get into it.

Links:

Project Euler: https://projecteuler.net/problem=2 HackerRank: https://www.hackerrank.com/contests/projecteuler/challenges/euler002

Each new term in the Fibonacci sequence is generated by adding the previous two terms. By starting with 1 and 2, the first 10 terms will be: 1,2,3,5,8,13,21,34,55,89,… By considering the terms in the Fibonacci sequence whose values do not exceed N, find the sum of the even-valued terms.

So first thing to note is just how odds and evens work. This starts with 1 and 2 so Odd + Even = Odd, then the next term would just be Even + Odd = Odd. It isn't until the 3rd addition that we get Odd + Odd = Even. After that this cycle will repeat.

So really what this is asking for is, starting at index 2, what is the sum of every 3rd term less than N.

F(2) + F(5) + ... + F(3k + 2)

(Where F(N) is the Nth Fibonacci number)

Now, computing Fibonacci numbers notoriously sucks to do, with the naive way of doing it causing you to compute from just F(20) would require computing F(3) like hundreds if not thousands of times over. So the best way to do it is to create either a hash or a cache to store it. I'm going to be utilizing something built into Python, "lru_cache" from the "functools" module. It'll just store the answers for me so I don't have to recompute what F(10) is thousands of times.

Here's my HackerRank code:

import sys from functools import lru_cache @lru_cache def fibonacci(N: int) -> int: if N < 0: return 0 if N <= 1: return 1 return fibonacci(N-1) + fibonacci(N-2) t = int(input().strip()) for a0 in range(t): n = int(input().strip()) x = 2 f = fibonacci(x) total = 0 while f <= n: total += f x += 3 f = fibonacci(x) print(total)

So as you can see, I just start at 2 and keep incrementing by fibonacci number by 3 each time. Then the loop will stop when my fibonacci number exceeds N.

And that's all tests passed! Onto the next one!

[zabeelinstitutes-blog]

The Ultimate Guide to Mastering Power BI: A Comprehensive Course by Zabeel Institute

In today's data-driven world, businesses are constantly seeking ways to leverage data for better decision-making. One of the most powerful tools to achieve this is Microsoft Power BI, a business analytics solution that empowers organizations to visualize their data, share insights, and make data-driven decisions in real time. If you're looking to gain expertise in this powerful tool, Zabeel Institute's Power BI course in Dubai is the perfect starting point.

What is Power BI?

Power BI is a suite of business analytics tools that allows users to analyze data and share insights. With its user-friendly interface and robust capabilities, Power BI enables both beginners and seasoned professionals to create interactive dashboards and reports. Whether you're dealing with simple data sets or complex analytics, Power BI makes data visualization intuitive and accessible.

Why Learn Power BI?

Learning Power BI opens up a world of opportunities. As businesses increasingly rely on data to drive their decisions, professionals skilled in Power BI are in high demand. Here are some compelling reasons why you should consider enrolling in a Power BI course:

High Demand for Power BI Skills: With the rise of data-driven decision-making, there is a growing demand for professionals who can interpret and visualize data effectively.

Career Advancement: Mastering Power BI can significantly enhance your career prospects, especially in fields such as data analysis, business intelligence, and management.

Versatility: Power BI is versatile and can be applied across various industries, including finance, healthcare, marketing, and more.

Improved Decision-Making: By learning how to create detailed and interactive reports, you can help your organization make informed decisions based on real-time data.

Course Overview: Analyzing Data with Microsoft Power BI

At Zabeel Institute, the Analyzing Data with Microsoft Power BI course is designed to equip you with the skills needed to harness the full potential of Power BI. This comprehensive course covers everything from the basics to advanced data visualization techniques.

1. Introduction to Power BI

The course begins with an introduction to the Power BI environment. You'll learn about the Power BI service, Power BI Desktop, and how to navigate through these tools efficiently. Understanding the interface is crucial for leveraging the full capabilities of Power BI.

2. Connecting to Data Sources

Power BI allows you to connect to a wide range of data sources, including Excel, SQL Server, Azure, and many more. In this module, you'll learn how to import data from various sources and prepare it for analysis.

3. Data Transformation and Cleaning

Before you can visualize your data, it often needs to be cleaned and transformed. This section of the course will teach you how to use Power Query to shape and clean your data, ensuring it's ready for analysis.

4. Creating Data Models

Data modeling is a crucial step in the data analysis process. In this module, you'll learn how to create relationships between different data sets and build a robust data model that supports your analysis.

5. Building Interactive Dashboards

One of Power BI's strengths is its ability to create interactive dashboards. You'll learn how to design visually appealing dashboards that provide meaningful insights at a glance.

6. Advanced Data Visualizations

Once you're comfortable with the basics, the course delves into more advanced visualizations. You'll explore custom visuals, R and Python integration, and how to create sophisticated reports that stand out.

7. DAX (Data Analysis Expressions)

DAX is a powerful formula language in Power BI. This section covers the fundamentals of DAX, enabling you to perform complex calculations and create dynamic reports.

8. Power BI Service and Collaboration

Power BI is not just about creating reports—it's also about sharing and collaborating on those reports. You'll learn how to publish your reports to the Power BI service, set up security, and collaborate with your team.

9. Power BI Mobile App

In today's mobile world, being able to access your reports on the go is essential. The course will show you how to use the Power BI Mobile App to view and interact with your dashboards from anywhere.

10. Best Practices for Power BI

To ensure you're getting the most out of Power BI, the course concludes with a module on best practices. This includes tips on performance optimization, report design, and maintaining data security.

Why Choose Zabeel Institute?

When it comes to learning Power BI, choosing the right institute is crucial. Zabeel Institute stands out for several reasons:

Experienced Instructors: Zabeel Institute's instructors are industry experts with years of experience in data analysis and business intelligence.

Hands-On Training: The course is designed to be highly practical, with plenty of hands-on exercises to reinforce your learning.

Industry-Recognized Certification: Upon completion, you'll receive a certification that is recognized by employers globally, giving you an edge in the job market.

Flexible Learning Options: Whether you prefer in-person classes or online learning, Zabeel Institute offers flexible options to suit your schedule.

Real-World Applications of Power BI

Understanding Power BI is one thing, but knowing how to apply it in the real world is what truly matters. Here are some examples of how Power BI can be used across various industries:

Finance: Create detailed financial reports and dashboards that track key metrics such as revenue, expenses, and profitability.

Healthcare: Analyze patient data to improve healthcare delivery and outcomes.

Retail: Track sales data, customer trends, and inventory levels in real time.

Marketing: Measure the effectiveness of marketing campaigns by analyzing data from multiple channels.

Human Resources: Monitor employee performance, track recruitment metrics, and analyze workforce trends.

Success Stories: How Power BI Transformed Businesses

To illustrate the impact of Power BI, let's look at a few success stories:

Company A: This retail giant used Power BI to analyze customer purchasing behavior, resulting in a 15% increase in sales.

Company B: A financial services firm leveraged Power BI to streamline its reporting process, reducing the time spent on report generation by 50%.

Company C: A healthcare provider used Power BI to track patient outcomes, leading to improved patient care and reduced readmission rates.

Mastering Power BI is not just about learning a tool—it's about acquiring a skill that can transform the way you work with data. Whether you're looking to advance your career, enhance your business's decision-making capabilities, or simply stay ahead in today's data-driven world, Zabeel Institute's Power BI course is the perfect choice.

Don't miss out on the opportunity to learn from the best. Enroll in Zabeel Institute's Power BI course today and take the first step towards becoming a Power BI expert.

Ready to transform your career with Power BI? Enroll in Zabeel Institute's Power BI course now and start your journey towards mastering data analysis and visualization. Visit Zabeel Institut for more information.

[psychosomatica]

Natural Text to Speech (python)

Microsoft Edge has very good, natural-sounding Text to Speech voices used in its "Read Aloud" feature. You can utilize these voices using python and a module called edge-tts (edge text to speech) to generate audio files of whatever text you like, including subtitles (for free).

Install python if you haven't already

Use pip to install edge-tts in your favorite command line

Run the CLI commands or create a new .py file. I suggest starting with this basic audio generation example.

Replace the TEXT variable contents with your string of choice. I recommend creating separate .txt files then reading them with the program, which allows you to cleanly scale your program to generate multiple files at once. (Imagine crawling your Obsidian vault to generate audio versions of all of your files!)

Choose your voice. You can use the Read Aloud feature in Edge to try out the different available voices (their quality varies). Their programatic voice names are found here. Note that not all voices are available, depending on your region, and trying to use one out of your region will throw an error. Read the footnotes. I'm still early in testing the different voices, but if you want to start on the right foot, Ava, or "en-US-AvaMultilingualNeural" is very good.

If you run the above example, it will generate a file called test.mp3 in the directory of the .py file. It's definitely performant. I ran a ~10k word file and it took a couple of minutes to generate (~23 MB with a running length of 1 hour and 3 minutes).

Have fun!

Added voice samples for the two I like the most, Ava and Brian multilingual.

[crippl-hacker]

Python Day 2

Today I am starting off with exercise 13. Exercise 13 introduces the concepts of variables, modules, and argv.

[ID: Exercise 13 code. It imports the argv module from sys, then uses argv to create 4 variables, script, first, second, and third. Next print() is used to print out the different variables /ID]

When calling the program I was confused as to why I got the error of too many variables. Looking into this I found that the first variable of 'argv' is always going to be the script. I then fixed that and added in script as the first variable.

Next for the study drill I wrote a new variable and updated the code to print the retrieved information.

Alrighty then - onto exercise 14. Exercise 14 is about practicing prompts and variables.

In the study drills I updated the script with a new prompt and print statement.

Exercise 15 is a simple program that prints out the contents of a file. An important thing to note is to always close the file when doing things like this!

Exercise 16 practices making a copy of a file and then updating it with 3 lines from user input.

I ended up running into the issue where it was saying that it couldn't read the file. I ended up finding out that .read() starts from the cursor position - and if the cursor is at the end of the file from writing it you will not have your file printed.

Exercise 17 is practicing copying files over and was relatively simple.

[c-cracks]

Matrix Breakout: 2 Morpheus

Hello everyone, it's been a while. :)

Haven't been posting much recently as I haven't really done anything noteworthy- I've just been working on methodologies for different types of penetration tests, nothing interesting enough to write about!

However, I have my methodologies largely covered now and so I'll have the time to do things again. There are a few things I want to look into, particularly binary exploit development and OS level security vulnerabilities, but as a bit of a breather I decided to root Morpheus from VulnHub.

It is rated as medium to hard, however I don't feel there's any real difficulty to it at all.

Initial Foothold

Run the standard nmap scans and 3 open ports will be discovered:

Port 22: SSH

Port 80: HTTP

Port 31337: Elite

I began with the web server listening at port 80.

The landing page is the only page offered- directory enumeration isn't possible as requests to pages just time out. However, there is the hint to "Follow the White Rabbit", along with an image of a rabbit on the page. Inspecting the image of the rabbit led to a hint in the image name- p0rt_31337.png. Would never have rooted this machine if I'd known how unrealistic and CTF-like it was. *sigh*

The above is the landing page of the web server listening at port 31337, along with the page's source code. There's a commented out paragraph with a base64 encoded string inside.

The string as it is cannot be decoded, however the part beyond the plus sign can be- it decodes to 'Cypher.matrix'.

This is a file on the web server at port 31337 and visiting it triggers a download. Open the file in a text editor and see this voodoo:

Upon seeing the ciphertext, I was immediately reminded of JSFuck. However, it seemed to include additional characters. It took me a little while of looking around before I came across this cipher identifier.

I'd never heard of Brainfuck, but I was confident this was going to be the in-use encryption cipher due to the similarity in name to JSFuck. So, I brainfucked the cipher and voila, plaintext. :P

Here, we are given a username and a majority of the password for accessing SSH apart from the last two character that were 'forgotten'.

I used this as an excuse to use some Python- it's been a while and it was a simple script to create. I used the itertools and string modules.

The script generates a password file with the base password 'k1ll0r' along with every possible 2-character combination appended. I simply piped the output into a text file and then ran hydra.

The password is eventually revealed to be 'k1ll0r7n'. Surely enough this grants access to SSH; we are put into an rbash shell with no other shells immediately available. It didn't take me long to discover how to bypass this- I searched 'rbash escape' and came across this helpful cheatsheet from PSJoshi. Surely enough, the first suggested command worked:

The t flag is used to force tty allocation, needed for programs that require user input. The "bash --noprofile" argument will cause bash to be run; it will be in the exec channel rather than the shell channel, thus the need to force tty allocation.

Privilege Escalation

With access to Bash commands now, it is revealed that we have sudo access to everything, making privilege escalation trivial- the same rbash shell is created, but this time bash is directly available.

Thoughts

I did enjoy working on Morpheus- the CTF element of it was fun, and I've never came across rbash before so that was new.

However, it certainly did not live up to the given rating of medium to hard. I'm honestly not sure why it was given such a high rating as the decoding and decryption elements are trivial to overcome if you have a foundational knowledge of hacking and there is alot of information on bypassing rbash.

It also wasn't realistic in any way, really, and the skills required are not going to be quite as relevant in real-world penetration testing (except from the decoding element!)

[shemsuji432]

Tips for the Best Way to Learn Python from Scratch to Pro

Python, often regarded as one of the most beginner-friendly programming languages, offers an excellent entry point for those looking to embark on a coding journey. Whether you aspire to become a Python pro or simply want to add a valuable skill to your repertoire, the path to Python proficiency is well-paved. In this blog, we’ll outline a comprehensive strategy to learn Python from scratch to pro, and we’ll also touch upon how ACTE Institute can accelerate your journey with its job placement services.

1. Start with the basics:

Every journey begins with a single step. Familiarise yourself with Python’s fundamental concepts, including variables, data types, and basic operations. Online platforms like Codecademy, Coursera, and edX offer introductory Python courses for beginners.

2. Learn Control Structures:

Master Python’s control structures, such as loops and conditional statements. These are essential for writing functional code. Sites like HackerRank and LeetCode provide coding challenges to practice your skills.

3. Dive into Functions:

Understand the significance of functions in Python. Learn how to define your functions, pass arguments, and return values. Functions are the building blocks of Python programmes.

4. Explore Data Structures:

Delve into Python’s versatile data structures, including lists, dictionaries, tuples, and sets. Learn their usage and when to apply them in real-world scenarios.

5. Object-Oriented Programming (OOP):

Python is an object-oriented language. Learn OOP principles like classes and objects. Understand encapsulation, inheritance, and polymorphism.

6. Modules and Libraries:

Python’s strength lies in its extensive libraries and modules. Explore popular libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation.

7. Web Development with Django or Flask:

If web development interests you, pick up a web framework like Django or Flask. These frameworks simplify building web applications using Python.

8. Dive into Data Science:

Python is a dominant language in the field of data science. Learn how to use libraries like SciPy and Scikit-Learn for data analysis and machine learning.

9. Real-World Projects:

Apply your knowledge by working on real-world projects. Create a portfolio showcasing your Python skills. Platforms like GitHub allow you to share your projects with potential employers.

10. Continuous learning:

Python is a dynamic language, with new features and libraries regularly introduced. Stay updated with the latest developments by following Python communities, blogs, and podcasts.

The ACTE Institute offers a structured Python training programme that covers the entire spectrum of Python learning. Here’s how they can accelerate your journey:

Comprehensive Curriculum: ACTE’s Python course includes hands-on exercises, assignments, and real-world projects. You’ll gain practical experience and a deep understanding of Python’s applications.

Experienced Instructors: Learn from certified Python experts with years of industry experience. Their guidance ensures you receive industry-relevant insights.

Job Placement Services: One of ACTE’s standout features is its job placement assistance. They have a network of recruiting clients, making it easier for you to land a Python-related job.

Flexibility: ACTE offers both online and offline Python courses, allowing you to choose the mode that suits your schedule.

The journey from Python novice to pro involves continuous learning and practical application. ACTE Institute can be your trusted partner in this journey, providing not only comprehensive Python training but also valuable job placement services. Whether you aspire to be a Python developer, data scientist, or web developer, mastering Python opens doors to diverse career opportunities. So, take that first step, start your Python journey, and let ACTE Institute guide you towards Python proficiency and a rewarding career.

I hope I answered your question successfully. If not, feel free to mention it in the comments area. I believe I still have much to learn.

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Thank you for spending your valuable time and upvotes here. Have a great day.