Pavlo 2021-07-31

Logging in Python

I completed two tutorials on Logging in Python. o The first tutorial is “Python Tutorial: Logging Basics - Logging to Files, Setting Levels, and Formatting and Python Tutorial: Logging Advanced - Loggers, Handlers, and Formatters” instructed by Corey Schafer, he is a full-time content creator publishing regular Python tutorials on YouTube. The length of the tutorial is 0.30 total video hours. o The second tutorial is “Logging in Python” offered by Real Python and instructed by Abhinav Ajitaria. You can find these tutorials at · https://www.youtube.com/watch?v=-ARI4Czawo&ab_channel=CoreySchafer · https://www.youtube.com/watch?v=jxmzY9soFXg&ab_channel=CoreySchafer · https://realpython.com/python-logging/

Pavlo 2021-07-27

Bitwise Operators in Python

I completed the “Bitwise Operators in Python” intermediate-level tutorial offered by Real Python. The instructor of the tutorial is Bartosz Zaczyński. In this tutorial I learned how to: • Use Python bitwise operators to manipulate individual bits • Read and write binary data in a platform-agnostic way • Use 6 techniques of bitmasks to pack information on a single byte • Overload Python bitwise operators in custom data types • Bitwise with Numpy, Pandas, SQLAlchemy modules • Big-Endian vs Little-Endian • How computers use the binary system to represent different kinds of digital information • Different ways to interpret bits and how to mitigate the lack of unsigned data types in Python • Python’s unique way of storing integer numbers in memory You can find this tutorial at · https://realpython.com/python-bitwise-operators/ One of my favorites are: • Check if a value is odd or even by using & 1 operator: ('even', 'odd')[n & 1] • Check if a number is a power of two: (n != 0) and (n & (n-1) == 0) In the future, I can experiment using bitwise operators to implement algorithms such as compression, encryption, and error detection or elsewhere.

Pavlo 2021-07-05

Deep Computer Vision Library: OpenCV. Two Capstone Projects – Face Detection and Classify the Characters: The Simpsons

I completed two courses on Deep Computer Vision to enhance my understanding of the subject. o The first course is the “OpenCV Python for Beginners course”. The course is offered by the ProgrammingKnowledge YouTube channel. The length of the course is 10.0 total video hours. o The second course is the “OpenCV Course - Full Tutorial with Python“, intermediary level. The course is offered by FreeCodeCamp.org. The length of the course is 4.0 total video hours. • Capstone Projects from the second course: 1) Face Detection with Haar Cascades and Face Recognition use a built-in face recognizer. 2) I built a Deep Computer Vision model to classify the characters in the popular TV series "The Simpsons". Used https://www.kaggle.com/notebooks dataset. I learned from these courses: • How to Read, Write, and Show Images • Resizing and Rescaling Frames • Draw geometric shapes on images & Putting Tekst • Handle Mouse Events • cv.split, cv.merge, cv.resize, cv.add, cv.addWeighted, ROI • Bitwise Operations (bitwise AND, OR, NOT and XOR) • How to Bind Trackbar • Object Detection and Object Tracking Using HSV Color Space • Simple Image, Adaptive Thresholding • matplotlib • Created multiple trackbars where I could calibrate most of the values of various operations to find the right values for my arguments. In the future learn cvui Module in order to improve the visualization of trackbar. • Morphological Transformations • Color Spaces, Color Channels • Smoothing Images | Blurring Images | Canny Edge Detection • Image Gradients and Edge Detection, Image Pyramids with Python, image blending using Pyramids • Find and Draw Contours, Motion Detection, and Tracking Using Contours • Detect Simple Geometric Shapes • Understanding image Histograms • Template matching using • Hough Line Transform Theory • Probabilistic Hough Transform using HoughLines • Road Lane Line Detection • Circle Detection using OpenCV Hough Circle Transform • Face Detection using Haar Cascade Classifiers • Eye Detection Haar feature-based Cascade Classifiers • Detect Corners with Harris Corner Detector, Detect Corners with Shi Tomasi Corner Detector • How to Use Background Subtraction Methods • Mean Shift Object Tracking, Object Tracking Camshift Method You can find these courses at ·https://www.youtube.com/watchv=N81PCpADwKQ&ab_channel=ProgrammingKnowledge ·https://www.youtube.com/watchv=oXlwWbU8l2o&ab_channel=freeCodeCamp.org • Used the following book for the projects: Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, and augmented reality to deep learning with OpenCV 4 and Python 3.7 by Alberto Fernández Villán.

Pavlo 2021-06-09

Descriptors in Python

To learn about descriptors I started with the best out there Raymond Hittinger’s “Descriptors HowTo Guide”. There, I completed “Complete Practical Example” about using a validator as a descriptor and how to use an “abstract base class” with it. In his tutorial I learned how to: • Descriptor as validator and how to use “abstract base class” with it • Manage attribute and logging module • Descriptor protocol (__get__(), __set__(), __delete()) • Descriptor invocation from instance, class, super • Properties, bound methods, classes methods and __slots__ based on descriptor protocol You can find this tutorial at · https://docs.python.org/3/howto/descriptor.html#id1 Then, I read the book “Python Descriptors: Understanding and Using the Descriptor Protocol” written by Jacob Zimmerman. He is a certified Java programmer and a Python and Kotlin enthusiast. Additionally, to what Raymond Hittinger’s “Descriptors HowTo Guide” explains, this book goes into more examples of how descriptors are used. In his book I learned how to: • Use of descriptors for data encapsulation • Use of descriptors for reuse of read/write patterns • Use of descriptors for lazily instantiating an attribute • Use of descriptors for validation • Use of descriptors for triggering actions • Use of descriptors for lazily instantiating an attribute • Pros and Cons of descriptors • Data descriptor versus non-data descriptors • How to do Read-Only Descriptors and Writing _delete() • Attribute access and Descriptors • How to store attributes • Fetching the Name (__set_name__()) • Instance-Level Descriptors • Use a pip install-able library called descriptor_tools

Pavlo 2021-06-08

Completed Flask Tutorial: Full-Featured Web App

I completed Python Flask Tutorial about how to make a full-featured web application. In this tutorial, I learned how to get started using the Flask framework. The tutorial's instructor is Corey Schafer, he is a full-time content creator publishing regular Python tutorials on YouTube. The length of the tutorial is 9.0 total video hours. I learned from this tutorial: • How to get started with Flask • Use templates • Forms and User inputs • Create a database with Flask-SQLAlchemy • Package Structure • User Authentication • User Account and Profile Picture • Create, Update, and Delete Posts • Pagination • Email and Password Reset • Blueprints and Configuration • Custom Error Pages • Deploy to Linux Server • How to use a Custom Domain Name for our Application • How to enable HTTPS with a free SSL/TLS Certificate using Let’s Encrypt You can find his tutorial at · https://www.youtube.com/watch?v=MwZwr5Tvyxo&list=PL-osiE80TeTs4UjLw5MM6OjgkjFeUxCYH&ab_channel=CoreySchafer My thanks and appreciation goes to Corey Schafer whose brilliant YouTube Flask Tutorial helped me to create this blog from scratch.

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