Python MultiTrack- beginners and professionals- zero to hero

Navigate the alpha release of multi-track training dot com to access Python notes, learn list slicing, explore functions and decorators, and view banking data from the transaction file.

Install Xcode command line tools to set up the macOS development environment for Python, enabling git and Homebrew to install Python 2 and Pip.

Install homebrew as the second step to set up the development environment, run the provided terminal command, and verify installation with brew help and brew list.

Install python 3 on MAKO OS using a single brew install python 3 command, then use pip 3 to install packages. The process downloads dependencies and completes setup.

Finalize the MAKO X development environment by installing PyCharm Community Edition with brew cask, downloading the latest version from JetBrains, then prepare to test installations in the next video.

Learn to create a hello world project with Python 3 on command line, perform arithmetic with a and b, print the result, edit hello world.py with vi, and run.

Set up a hello world project in PyCharm Community Edition, configure a Python 3 virtual environment, and run a script that adds 14 and 23 and prints 'Hello world'.

Set up a Python multi-track project environment with four areas: fast track, detail track, examples, and play, using a dedicated virtual environment and a hello world test.

Install python 3.8.2 on windows from python.org, verify with hello world and a+b, then install PyCharm community edition and run a hello world project in a virtual environment.

Set up a Python multi-track project with a virtual environment, create folders for detail track, fast track, examples, and play, and test by running a hello world script.

Build a banking gui in Python that reads JSON transaction files, converts hexadecimal to decimal, applies transactions to accounts, and generates opening and closing balances.

Set up the banking project by creating a data folder with accounts and a multi-format transactions file, and illustrate hexadecimal to decimal conversions for client records and debits/credits.

Learn how to assign data to variables in Python, name values, and print component strings such as file header records, file date, and client transaction details for data processing.

Learn how to work with Python variable types by converting strings to int and float, printing types, and parsing transaction data to distinguish string, int, and float values.

Learn how to explicitly cast data in Python by converting strings to numeric types, using fixed-width records from banking transactions to cast amounts to float and accounts to int.

Extract data from transaction records by slicing Python strings to retrieve the file header, file date, and client records, using zero-based indexing.

Explicitly cast extracted data to the proper types (int, float, date) after slicing header records, ensuring account numbers, transaction amounts, and record counts are typed correctly.

Learn how to convert hex account numbers to decimal in Python by casting hex strings to integers with base 16 and printing the results.

Convert a days string to a proper Python date using the datetime module, extracting year, month, day, hour, and minute (and seconds) by slicing and casting to int.

Transform procedural code into reusable Python functions by defining parse file header, parse client header, and parse file footer, then pass records and invoke in the correct order.

Learn to refactor code to collect file records as tuples by returning values from parsing functions (header, client header, transactions) and printing via a dedicated detail printer.

Identify record types using control flow to parse records with a main function. Iterate over records with a for loop, parse file header, client header, client transaction, and file photo.

Learn to iterate a collection of records and print every field of each tuple by iterating the detail tuple, naming fields, and separating outputs.

Convert tuples to dictionaries to print meaningful field names during iteration, using Python dictionaries with curly braces and quotes to display record types, file dates, and client transactions clearly.

Create a Python transaction object by defining a transaction class with __init__ and __str__ to store and print date, type, amount, and third party account, from parsed records.

Learn how to design an account object by reusing the transaction object, parsing client header and transaction data, and building an account from code and transaction count.

Create account and transaction objects, add transactions to each account, and print accounts with their transactions.

Learn to structure a Python project with the model–view–controller pattern by creating model and controller packages, modules like account and transaction, and proper imports via __init__.py.

Learn how to read and parse data files, identify client header and client transaction records, and build accounts with their transactions from a transaction file.

Parse a JSON accounts file in Python to load opening balances and account codes, create account objects, and integrate with the transaction parser workflow.

Modify the account model to update existing accounts with transactions, track transaction counts, and compute closing balances from opening balances using credits and debits.

Learn to compute closing balances by parsing accounts and transactions, using a class-level accounts dictionary keyed by account code, and integrate parsing with robust tests.

Output combined account and transaction records as json, create an output directory, and implement a custom json encoder to serialize accounts, transactions, and date times in ISO format, with tests.

learn to build a main app module and an app controller, organize tests, and parse accounts and transaction data to produce a structured json output.

Build a banking GUI in Python to upload accounts and transactions, process and display JSON output, and visualize analyzed results with a pie chart.

Create a gui frame by building a Python app with model, view, and controller, wire banking view to a Tkinter window, set its title and geometry, and run main loop.

Add a top menu to a tkinter GUI by creating a menu, attaching it to the window, adding a File cascade with a close command via lambda.

Layout a multi-frame user interface by defining left and right bar button frames, input and output frames, and a bottom frame, using five init functions, relative positioning, and anchor points.

Add upload accounts and upload transactions buttons to the top left and right frames, wire click events, and adjust frames to fit and mirror process and analyze transactions.

Layout the input and output frames with a tab bar, add accounts and transactions tabs, and remove the blue border for a clean layout.

Learn to add button controllers in a gui, create write methods for accounts, transactions, and output details, and wire button handlers to update text fields and load and process data.

Learn to read and parse data files in a Python MultiTrack app by opening a file dialog to select account or transaction files and update accounts and transactions tabs.

Implement the final solution by parsing transaction data from files, processing the data, and generating output, using a 24 banking GUI and added parsing code.

Learn to parse account and transaction data by loading file names, reading contents, and parsing records into a json output, with modular get file name and get file content steps.

Tidy up the user interface in this final exercise by showing a popup when accounts or transactions files are missing, remove error messages, and adjust colors and launch screen size.

Tidy up the multi-track app by adjusting window geometry, improving visuals with borders and color, and adding validation with pop-up errors for missing accounts or transactions files.

Launch graphs for banking projects to analyze data by uploading accounts and transactions files, processing transactions, and generating a pie chart that shows credits versus debits as percentages.

Learn to create straight-line and multi-graph plots with matplotlib by plotting x and y points, labeling axes, enabling grids, and adding legends.

Create a scatter graph of planets from Mercury to Neptune, plotting distance from the sun versus radius in kilometers, with colored, size-scaled dots and a planet legend.

Create a simple bar chart of days in each month using Python, label bars with three-letter month names, and annotate each bar with its day count.

Create a simple pie chart of planet radii using plot lib, assign colors, add a legend, and adjust start angle, shadow, and explode effects for a polished visualization.

This lecture guides you to add a pie-chart based transaction analysis to a banking GUI, plotting credits against debits with matplotlib and a new graphs package.

Learn to compute total credits and debits from banking transactions, using a create credits and debits method, process accounts and transactions, and visualize results with a pie chart.

Set up the detail track project in a Python environment, creating a structured directory layout from variables to unit testing. Test with a simple hello world to verify the setup.

Learn basic python syntax by executing code in the terminal, writing and saving scripts with vi, and using comments and indentation to structure control flow.

Explore how Python stores data with variables, using naming conventions that start with a letter or underscore. Practice assignment, reassignment, and multi‑assignment of strings, integers, and floats, with type checks.

Explore building a hospital booking system in Python by defining variables for patients, treatments, and doctors, then print theater allocations with dates and times as design hints.

Build a hospital booking system in python: define patient records, assign designated and allocated doctors, manage theatres and time slots, and print patient schedules.

Explore core data types in Python, including int, float, and string. Demonstrate integers as whole numbers, positive or negative, with no decimals, and use the type function to verify.

Learn how to work with floats in Python, exploring floating point numbers, declaring decimal values like pi, assigning x, y, z, and printing both values and their float type.

Explore Python strings, including single and double quotes, variable assignment, and printing; learn to create multi-line strings with triple quotes and print them.

Master printing and formatting strings in Python by concatenating values with type conversion to strings, using separators, and printing collections via unpacking lists and tuples.

Demonstrate base conversion in Python by converting decimal to binary, octal, and hexadecimal and displaying results with formatted strings.

Learn how to work with scientific notation in Python using e notation and f-strings, print formatting, and how floats represent powers of ten, infinity, and min/max ranges.

Master Python string manipulation using indexing and slicing to extract substrings, access characters, and apply start, end, and step parameters, including negative indices.

Master how to use special characters in Python strings, including embedded quotes, escaping with backslashes, and formatting with braces while handling newlines, tabs, and backspaces.

Explore Python string manipulation with methods such as capitalize, upper, lower, casefold, find, startswith, endswith, count, split, and replace. Apply slicing and splitting to extract dates, addresses, and transaction details.

Explore how Python evaluates boolean values through comparisons and conditions, showing true and false results and the truthiness of nonzero numbers and nonempty collections.

Learn to create and examine Python complex numbers such as 2+5j and 3+4j, access their real and imaginary parts, and build them with the complex(real, imag) constructor.

Update the hospital booking system to use correct data types, rename variables, and implement a simple solution showing patient and doctor theater assignments with dates and hours.