I wrote a Python code or I created a Python script, and it executed successfully- So what does it Mean?

by | Jun 29, 2024 | Python | 0 comments

I wrote a Python code or I created a Python script, and it executed successfully So what does it Mean? This will be the most basic question a Early Python Learner can ask ! So Consider this scenario- where i executed a script in python which saves a many csv in Local disk and also wrote hundread of rows of tabular data to a table in mysql server. Let us explain what all has happended – when i execute this script, especially computer’s internal hardware & software standpoint.

Here’s a breakdown of what happens when you execute a Python script that saves multiple CSVs and writes to a MySQL server:

Hardware:

  1. CPU (Central Processing Unit): This is the brain of your computer and the main component that executes the Python script. It fetches instructions from the script line by line, decodes them, and performs the necessary operations.
  2. Main Memory / RAM (Random Access Memory): This temporary storage holds the Python script itself while it’s being executed. It also stores variables and data used by the script during its operation. RAM is often referred to as a computer’s main memory, as opposed to the processor cache or other memory types. Random access memory is considered part of a computer’s primary memory. The Main Memory is used to store information that the CPU needs in a hurry. The main memory is nearly as fast as the CPU. But the information stored in the main memory vanishes when the computer is turned off.
  3. Secondary Memory / Storage Drive (HDD or SSD): This is where the Python script resides before execution and where the generated CSV files are saved. It also stores the MySQL database files (if the server is local). The Secondary Memory is also used to store information, but it is much slower than the main memory. The advantage of the secondary memory is that it can store information even when there is no power to the computer. Examples of secondary memory are disk drives or flash memory (typically found in USB sticks and portable music players).
  4. I/O – Network Card (Optional): The Input and Output Devices are simply our screen, keyboard, mouse, microphone, speaker, touchpad, etc. They are all of the ways we interact with the computer. These days, most computers also have a Network Connection to retrieve information over a network. We can think of the network as a very slow place to store and retrieve data that might not always be “up”. So in a sense, the network is a slower and at times unreliable form of Secondary Memory. If your MySQL server is on a different machine, the network card facilitates communication between your computer and the server for database interaction.

Software:

  1. Operating System (OS): The OS (e.g., Windows, macOS, Linux) manages the overall system resources, including memory, storage, and CPU allocation. It also provides an environment for the Python interpreter to run.
  2. Python Interpreter: This program translates Python code into instructions that the CPU can understand. It reads the script line by line, interprets its meaning, and executes the necessary actions.
  3. Python Libraries: Your script might import specific Python libraries (e.g., csv, mysql.connector) for working with CSV files and interacting with the MySQL server. These libraries provide pre-written functions and modules that simplify tasks like reading/writing files and connecting to databases.
  4. MySQL Server (Optional): If the MySQL server is local, it’s running in the background on your computer. If it’s remote, it’s running on a different machine on the network. The server manages the MySQL database, handling data storage, retrieval, and manipulation based on your script’s commands.

Execution Flow:

  1. Script Initiation: You double-click the Python script file or run it from a terminal/command prompt.
  2. OS Activation: The OS identifies the file as a Python script and locates the Python interpreter on your system.
  3. Interpreter Load: The OS loads the Python interpreter into memory (RAM) and allocates resources for the script’s execution.
  4. Script Execution: The interpreter starts reading the script line by line, translating the code into machine-readable instructions, and executing them using the CPU.
  • CSV Processing: Functions from the csv library are used to open and write multiple CSV files on the storage drive based on the script’s logic.
  • MySQL Interaction: Libraries like mysql.connector are used to establish a connection with the MySQL server (local or remote) using your provided credentials. The script then executes commands to insert data into the desired table.
  1. Resource Management: The OS manages memory allocation and keeps track of open files (CSVs) and database connections.
  2. Script Completion: Once the script finishes execution, the interpreter unloads from memory, and any open files or database connections are closed.

Additional Notes:

  • Depending on your script’s complexity, it might interact with additional software components like error handling modules or logging libraries.
  • Security measures like authentication and authorization might be involved when connecting to a remote MySQL server.

Detailed step-by-step account

When you execute a Python script that saves multiple CSV files to disk and writes a table to a MySQL server, a series of hardware and software processes occur. Here’s a detailed step-by-step account of what happens from the moment you execute the script:

Step 1: Script Execution Initiation

  1. User Command: You run the Python script from the command line or an IDE.bashCopy codepython your_script.py

Step 2: Operating System (OS) Interaction

  1. Process Creation: The operating system creates a new process for the Python interpreter. This involves allocating memory and other resources for the process.
  2. Script Loading: The OS loads the Python interpreter executable into memory, which then reads and begins to execute your script.

Step 3: Python Interpreter

  1. Interpreter Start: The Python interpreter starts and begins to parse and execute your script line by line.
  2. Module Import: The interpreter loads any required modules and libraries (e.g., pandas, mysql.connector) from the standard library or installed packages. This involves reading the necessary files from disk and loading them into memory.

Step 4: File System Interaction

  1. CSV File Writing:
    • Data Preparation: Your script prepares data to be written to CSV files, often involving data manipulation and formatting using libraries like pandas.
    • File Creation: The script creates or opens files on the disk. This involves OS-level file handling operations, including checking file permissions, creating file descriptors, and allocating disk space.
    • Data Writing: The data is written to these files. The OS manages buffering and ensures that data is correctly written to the storage medium.
    • File Closing: After writing the data, the script closes the files, ensuring that all buffers are flushed and file descriptors are released.

Step 5: Network Interaction (MySQL Server)

  1. Database Connection:
    • Network Socket Creation: Your script uses a library (e.g., mysql.connector) to create a network socket and establish a connection to the MySQL server. This involves DNS resolution (if connecting by hostname), network routing, and potentially firewall traversal.
    • Authentication: The MySQL server authenticates the connection using the credentials provided in your script.
  2. Data Transfer to MySQL:
    • Query Execution: Your script sends SQL commands over the established network connection to create tables and insert data. The MySQL server receives these commands, parses them, and executes them.
    • Data Storage: The MySQL server writes the data to its own storage system. This involves disk I/O operations, similar to the CSV file writing process but managed by the MySQL server software.

Step 6: Script Completion

  1. Resource Cleanup: Once the script has completed its tasks, it closes any remaining open files and database connections. The OS and Python interpreter ensure that all resources are properly released.
  2. Process Termination: The Python process terminates, and the OS cleans up any remaining resources associated with the process.

Detailed Internal Hardware and Software Processes

  1. CPU Operations:
    • Instruction Fetching and Execution: The CPU fetches and executes instructions from the Python interpreter and your script.
    • Context Switching: The CPU may switch between different processes (including your script and other running processes), managing execution time via the OS scheduler.
  2. Memory Management:
    • RAM Allocation: The OS allocates RAM for the Python process, script data, and any libraries being used. This includes memory for variables, data structures, and buffers.
    • Virtual Memory: The OS uses virtual memory to manage and optimize RAM usage, potentially swapping data to and from disk as needed.
  3. Disk I/O:
    • File Reading/Writing: The OS manages read/write operations to the disk. For writing CSV files, this involves creating files, writing data, and ensuring data integrity.
    • Database Storage: When writing to the MySQL server, the server’s storage engine (e.g., InnoDB) handles data writing, indexing, and storage management.
  4. Network I/O:
    • Data Packets: Data sent to and from the MySQL server is broken into packets, transmitted over the network, and reassembled at the destination.
    • Error Handling: Network errors (e.g., packet loss, latency) are managed through TCP/IP protocols, ensuring reliable data transfer.

So

When you execute your Python script:

  • The OS creates a process for the Python interpreter.
  • The interpreter reads and executes your script, loading necessary libraries.
  • The script writes data to CSV files via the file system, involving disk I/O operations.
  • The script connects to the MySQL server over the network, authenticates, and executes SQL commands to store data.
  • The OS and interpreter manage memory, CPU, and I/O resources throughout this process.
  • The process terminates, and the OS cleans up resources.

This sequence involves coordinated efforts between the CPU, memory, disk storage, network interfaces, and various layers of software (OS, Python interpreter, libraries, and MySQL server) to accomplish the tasks specified in your script. This is More with How A Py Script interacts with Computer. Let us Now deal in details with How a Python code executes:-

what happens when you run a Python code file (abc.py):

1. Invoking the Python Interpreter:

You run abc.py from the command line or an IDE by typing python abc.py.The operating system identifies Python as the interpreter for .py files and executes it accordingly.

  • When you execute python abc.py from your terminal, the operating system (OS) locates the Python interpreter (python) and launches it as a new process.
  • This process has its own memory space allocated by the OS.

2. Lexical Analysis (Scanning):

  • The interpreter first performs lexical analysis, breaking down the Python code into tokens (keywords, identifiers, operators, etc.). It identifies these tokens based on the Python language syntax.

Lexical Analysis (Tokenization)

  • Scanner (Lexer): The first stage in the compilation process is lexical analysis, where the lexer scans the source code and converts it into a stream of tokens. Tokens are the smallest units of meaning in the code, such as keywords, identifiers (variable names), operators, literals (constants), and punctuation (e.g., parentheses, commas).
  • Example:x = 10 + 20
  • This line would be tokenized into:
    • x: Identifier
    • =: Operator
    • 10: Integer Literal
    • +: Operator
    • 20: Integer Literal

3. Syntax Analysis (Parsing):

  • Next comes syntax analysis, where the interpreter checks if the token sequence forms a valid Python program according to the grammar rules. Syntax errors (e.g., missing colons, mismatched parentheses) are detected at this stage, resulting in an error message.

Syntax Analysis (Parsing)

  • Parser: The parser takes the stream of tokens produced by the lexer and arranges them into a syntax tree (or Abstract Syntax Tree, AST). The syntax tree represents the grammatical structure of the code according to Python’s syntax rules.
  • Example AST for x = 10 + 20:
    • Assignment Node
      • Left: Identifier x
      • Right: Binary Operation Node
        • Left: Integer Literal 10
        • Operator: +
        • Right: Integer Literal 20

4. Bytecode Compilation (Optional – Depending on Python Version):

  • For Python versions prior to 3.0 (CPython): The interpreter compiles the parsed code into bytecode, an intermediate representation that’s more portable and often faster to execute than the original source code. This bytecode is typically stored in a .pyc file.
  • For Python versions 3.0 and later (CPython): The interpreter might skip this step and directly generate the bytecode on the fly during execution using Just-In-Time (JIT) compilation. This can improve performance, especially for frequently executed code blocks.

5. Bytecode Execution:

Compilation: Python source code is compiled into bytecode (.pyc files) or directly into memory (if not saved to .pyc).

Execution: Bytecode is executed by the Python Virtual Machine (PVM), which is part of the interpreter. Each bytecode instruction is executed in sequence.

  • The Python Virtual Machine (PVM), a software component within the interpreter, executes the generated bytecode. Each bytecode instruction corresponds to a specific operation (e.g., variable assignment, function call, loop iteration).

6. Memory Management:

Memory Management:

  • Allocation: Memory is allocated dynamically as needed to store variables, constants, and data structures (like lists, dictionaries).
  • Deallocation: Python’s memory manager handles garbage collection via reference counting and a cyclic garbage collector, reclaiming memory from objects no longer in use.
  • The PVM manages memory used by the program’s data structures (variables, lists, dictionaries, etc.). Data types are stored in memory according to their size and layout requirements (e.g., integers occupy less space than strings).
  • The OS also has memory management tools (like garbage collection in CPython) to reclaim unused memory when objects become unreachable.

7. Top-Level Code Execution:

Code outside of function and class definitions at the top level of abc.py is executed sequentially as part of the __main__ module.Functions and classes are defined but not executed until they are called.

  • The PVM starts execution from the top-level code in the abc.py file, which includes:
    • Module-level statements (outside any function definitions) are executed in the order they appear in the file.
    • The __main__ block, if present, is executed only when the script is run directly (not imported as a module). This allows you to define code that specifically executes when the program is the main entry point.

8. Function Calls and Variable Scope:

Variables: Dynamically typed variables (e.g., x = 10 where x can be reassigned different types).

Constants: Python doesn’t have constants in the traditional sense; conventionally, constants are named in uppercase to indicate they should not be changed.

Data Types: Python supports various built-in data types such as integers, floats, strings, lists, tuples, dictionaries, etc. Each has its own memory management characteristics.

  • When a function is called, a new activation record (stack frame) is created on the call stack. This frame stores local variables, function arguments, and the return address (where to return after function execution).
  • Variable scope determines the visibility and lifetime of variables. Local variables are accessible only within the function’s scope (activation record) and are destroyed when the function exits.

9. Temporary Variables:

Temporary variables are typically local to functions or within the scope where they are defined.Python manages variable scope using namespaces (local, global, built-in) and manages memory accordingly.

  • The interpreter and PVM might create temporary variables in memory during execution for intermediate calculations or storing partial results. These temporary variables are typically short-lived and get garbage collected when no longer needed.

10. Output and Termination:

  • The program’s output (e.g., print statements) is displayed on the console or sent to the specified output stream.
  • Once all top-level code and functions have finished execution, the PVM and interpreter clean up any remaining resources, and the process terminates. The memory allocated for the program is released by the OS.

  • Exception Handling: If an exception occurs during execution (e.g., division by zero, file not found), the PVM throws an exception object, allowing you to handle errors gracefully using try...except blocks.
  • Modules and Imports: When a module (xyz.py) is imported using import xyz, the interpreter executes that module’s code (similar to running xyz.py). Functions and variables defined in xyz.py become available for use in the importing script.
  • Interactive Interpreter: Running Python interactively (python) provides a prompt where you can enter code line by line, which is immediately executed.

Written by HintsToday Team

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