Learn From Scratch Visual C Net With Mysql
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The Quick Tutorial to Learn Database Programming Using Python GUI with MariaDB and PostgreSQL
In this book, you will create two MariaDB and PostgreSQL driven projects using PyQt. The step-by-step guide in this book is expected to help the reader's confidence to become a programmer who can solve database programming problems. A progressive project is provided to demonstrate how to apply the concepts of MariaDB and PostgreSQL using Python. In second chapter, you will learn PyQt that consists of a number of Python bindings for cross-platform applications that combine all the strengths of Qt and Python. By using PyQt, you can include all Qt libraries in Python code, so you can write GUI applications in Python. In other words, you can use PyQt to access all the features provided by Qt through Python code. Because PyQt depends on the Qt libraries at run time, you need to install PyQt. In third chapter, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In fourth chapter, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In this chapter, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter five, you will create dan configure PotgreSQL database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter six, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have a VARCHAR data type (200). You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In chapter eight, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.
The Fast Tutorial to Learn Database Programming Using Python GUI with Access and SQL Server
This book covers microsoft acces and SQL Server based GUI programming using pyqt. Intentionally designed for various levels of interest and ability of learners, this book is suitable for students, engineers, and even researchers in a variety of disciplines. No advanced programming experience is needed, and only a few school-level programming skill are needed. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In third chapter, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In fourth chapter, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will create dan configure database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have VARBINARY(MAX) data type. You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In the last chapter, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.
DIGITAL SIGNATURE ALGORITHM: LEARN BY EXAMPLES WITH PYTHON AND TKINTER
Project 1 demonstrates generating a DSA (Digital Signature Algorithm) key pair using the cryptography library, where a 2048-bit private key is created and a corresponding public key is derived. The private key is essential for securely signing digital messages, and the public key allows others to verify these signatures. Both keys are serialized into PEM format, making them suitable for storage or transmission. The private key is serialized without encryption (though encryption is optional), while the public key is also serialized for easy sharing and use in cryptographic operations. Project 2 is a DSA (Digital Signature Algorithm) Key Generator application built with Python's tkinter for the GUI and the cryptography library for key generation. It provides an intuitive interface to generate, view, and save 2048-bit DSA key pairs, essential for secure digital signatures. The GUI features two tabs: "Generate Keys" for creating and serializing keys into PEM format, and "View Keys" for displaying them. Users can save the keys as .pem files with ease, supported by robust error handling and success notifications, making the application accessible and practical for secure communication needs. Project 3 demonstrates the process of signing and verifying a message using the Digital Signature Algorithm (DSA) in Python, while ensuring the signature is UTF-8 safe by encoding it in Base64. It begins by generating a DSA private and public key pair with a key size of 2048 bits. A message (in bytes) is then created, which is the data to be signed. The private key is used to generate a digital signature for the message using the SHA-256 hashing algorithm, ensuring the integrity and authenticity of the message. The generated signature, which is binary data, is encoded into Base64 format to make it text-safe and suitable for UTF-8 encoding. To verify the signature, the Base64-encoded signature is first decoded back into its original binary form. The public key is then used to verify the authenticity of the signature by comparing it to the message. If the verification is successful, the message "Signature is valid." is printed; otherwise, an InvalidSignature exception is raised, and the message "Signature is invalid." is displayed. This approach ensures that the digital signature can be safely transmitted or stored as text without data corruption, while still preserving its security properties. Project 4 is a Tkinter-based GUI application for Digital Signature Algorithm (DSA) operations, offering an intuitive interface for generating DSA keys, signing messages, and verifying signatures. It has two main tabs: one for generating and displaying DSA key pairs in PEM format, and another for signing and verifying messages. Users can input a message, sign it with the private key, and view the Base64-encoded signature, or verify a signature against the original message using the public key. The application handles errors gracefully, providing feedback on operations, making it a practical tool for cryptographic tasks. Project 5 and 6 provides a complete implementation for generating, signing, and verifying files using the Digital Signature Algorithm (DSA). It includes functions for creating DSA key pairs, signing file contents, and verifying signatures. The generate_and_save_keys() function generates a private and public key, serializes them to PEM format, and saves them to files. The sign_file() function uses the private key to sign the SHA-256 hash of a file's content, saving the signature in Base64 format. The verify_file_signature() function then verifies this signature using the public key, ensuring the file's authenticity and integrity. The project is designed as a user-friendly Tkinter-based GUI application, with three main functionalities: key generation, file signing, and signature verification. Users can generate DSA key pairs in the "Generate Keys" tab, sign files in the "Sign File" tab, and verify signatures in the "Verify Signature" tab. By providing an intuitive interface, this application enables users to efficiently manage cryptographic operations, ensuring data security and authenticity without needing to understand low-level cryptographic details. Project 7 and 8 focuses on creating and securing synthetic financial datasets to ensure data integrity. It combines data generation, digital signing, and signature verification to authenticate and protect financial records. The primary goals are to generate realistic financial data, secure it with digital signatures, and verify these signatures to detect tampering or corruption. The project involves generating a synthetic dataset with multiple columns such as transaction IDs, account numbers, amounts, currencies, timestamps, and transaction types. DSA keys are then generated for signing and verification, with the private key used for signing each entry in the dataset. These signatures are saved separately, allowing verification using the public key. This process ensures that any unauthorized changes to the data are detected, demonstrating a secure approach to data handling in financial applications. Project 9 and 10 combines the Digital Signature Algorithm (DSA) with Least Significant Bit (LSB) steganography to securely hide a signed message within an image. First, DSA keys are generated and used to sign a message, ensuring its authenticity and integrity. The signed message is then embedded into an image using LSB steganography, where the least significant bits of the image pixels' red channel are altered to include the binary representation of the message and its signature. To extract and verify the hidden data, the code retrieves the embedded bits from the image and reconstructs the original message. It then uses the public DSA key to verify the signature, confirming the message's authenticity. This integration of cryptographic signing with steganography provides a secure method to conceal and authenticate sensitive information within an image file. Project 11 and 12 provides a workflow for encrypting and hiding data using RSA and DSA cryptographic algorithms, along with steganography. It begins with generating RSA and DSA keys, then encrypts a message using RSA and signs it with a DSA private key, ensuring confidentiality and authenticity. The encrypted and signed data is embedded into an image using Least Significant Bit (LSB) steganography, altering the pixel values to include the hidden information. The process continues by extracting the hidden data from the image, verifying its integrity using the DSA signature, and decrypting the message with the RSA private key. This approach demonstrates a secure method of combining encryption, digital signatures, and steganography to protect and authenticate sensitive data, making it a robust solution for secure data transmission.