50 Days of Learning 50 Pro Level Python Concepts

Explore Python's built-in hashing with the hashlib module, generating fixed-size hashes for strings using sha256 and other algorithms, and verify determinism, one-way properties, and the avalanche effect.

Explore Python turtle graphics by importing the built-in turtle module, drawing on a canvas with a pen, and using forward, backward, left, and right commands to create shapes.

Learn to scrape and print specific data from a web page with BeautifulSoup, selecting div.article, extracting headings and descriptions via find, find_all, and for loops.

Develop an understanding of building a Python client that connects to a local server using a TCP socket, receives, decodes, and prints messages in a loop before closing the connection.

Develop a file server that receives a requested file name from the client, opens and reads the file, and sends the content back, or returns a file not found error.

Learn to build mobile apps in Python with Kivy. Create labels, buttons, images, and text inputs, and design layouts with grid, box, float, anchor, while handling keyboard, mouse events, and clocks.

Explore type conversion in f-strings, converting numbers to hexadecimal, binary, octal, and more, formatting with commas, underscores, percentages, and signs, plus lambda functions with f-strings.

Install OpenCV by running pip install opencv-python in your command line or PyCharm terminal, using the right package for Python 3.x or 2.x, and ensure internet access.

Learn to read, display, and save images with OpenCV in Python using cv2.imread, cv2.imshow, waitKey, and cv2.imwrite, including color and grayscale options.

Learn to implement mouse events in OpenCV with Python by using setMouseCallback, handling left and right clicks and double-clicks, and overlaying text on images with putText.

Explore NumPy, the numerical Python library that powers scientific computing with fast multi-dimensional arrays and matrices, enabling efficient data operations in Python for SciPy, scikit-learn, and OpenCV.

install numpy for python with pip install numpy from the terminal or command line. PyCharm users may need a manual install, while Spyder or Jupyter often include numpy by default.

Install and import numpy, create and print a one-dimensional array, access items by index (including negative indices), and explore size, item size, nbytes, dtype, and updating items.

Explore how to compare NumPy arrays and their elements, use array_equal to compare complete arrays, and apply logical operations like logical_or, logical_and, xor, and not on arrays.