Python 3.12.1 : pipx tool .

The pip is a general-purpose package installer for both libraries and apps with no environment isolation. pipx is made specifically for application installation, as it adds isolation yet still makes the apps available in your shell: pipx creates an isolated environment for each application and its associated packages.

Install the pipx tool :

python -m pip install --user pipx
Collecting pipx
  Downloading pipx-1.4.3-py3-none-any.whl.metadata (17 kB)
  ...

Upgrade the pipx tool:

python -m pip install --user --upgrade pipx

Using pipx to install an application by running :

python -m pipx install pyos
⡿ installing pyos  installed package pyos 0.8.0, installed using Python 3.12.1
  These apps are now globally available
    - psh.exe
    - pyos.exe
done! ✨ 🌟 ✨

Show the Python packages on the environment:

python -m pipx list
venvs are in C:\Users\catafest\AppData\Local\pipx\pipx\venvs
apps are exposed on your $PATH at C:\Users\catafest\.local\bin
manual pages are exposed at C:\Users\catafest\.local\share\man
   package pyos 0.8.0, installed using Python 3.12.1
    - psh.exe
    - pyos.exe

If an application installed by pipx requires additional packages, you can add them with pipx inject, and this can be seen with the list argument.

python -m pipx inject pyos matplotlib
  injected package matplotlib into venv pyos
done! ✨ 🌟 ✨
...
python -m pipx list
venvs are in C:\Users\catafest\AppData\Local\pipx\pipx\venvs
apps are exposed on your $PATH at C:\Users\catafest\.local\bin
manual pages are exposed at C:\Users\catafest\.local\share\man
   package pyos 0.8.0, installed using Python 3.12.1
    - psh.exe
    - pyos.exe
...    
python -m pipx list --include-injected
venvs are in C:\Users\catafest\AppData\Local\pipx\pipx\venvs
apps are exposed on your $PATH at C:\Users\catafest\.local\bin
manual pages are exposed at C:\Users\catafest\.local\share\man
   package pyos 0.8.0, installed using Python 3.12.1
    - psh.exe
    - pyos.exe
    Injected Packages:
      - matplotlib 3.8.3
      - test-py 0.3

This adds the matplotlib package to pyosenvironment.

If I try to inject into another environment name, then I will get an error:

python -m pipx inject catafest matplotlib
Can't inject 'matplotlib' into nonexistent Virtual Environment 'catafest'. Be sure to install the package first
with 'pipx install catafest' before injecting into it.

Create a Python file named test.py with this source code:

# test.py

# Requirements:
# requests
#
# The list of requirements is terminated by a blank line or an empty comment line.

import sys
import requests
project = sys.argv[1]
pipx_data = requests.get(f"https://pypi.org/pypi/{project}/json").json()
print(pipx_data["info"]["version"])

You can run it with:

python -m pipx run test.py pipx
1.4.3

I don't know how advanced the environment is built and I tested some simple scenarios but I found some inconsistencies in the scripts created by the user that can be run other than with a simple run and on several environments in the same folder. Theoretically, there should be such functionality.

Python 3.12.1 : The kaitai python module and IDE online tool.

Kaitai Struct is a declarative language used to describe various binary data structures, laid out in files or in memory: i.e. binary file formats, network stream packet formats, etc.

The main idea is that a particular format is described in Kaitai Struct language (.ksy file) and then can be compiled with ksc into source files in one of the supported programming languages. These modules will include a generated code for a parser that can read the described data structure from a file or stream and give access to it in a nice, easy-to-comprehend API.

Let's install the Python module:

python3 -m pip install --upgrade kaitaistruct
Python was not found; run without arguments to install from the Microsoft Store, or disable this shortcut from Settings > Manage App Execution Aliases.

C:\PythonProjects\kaitai_001>python -m pip install --upgrade kaitaistruct
Collecting kaitaistruct
  Downloading kaitaistruct-0.10-py2.py3-none-any.whl.metadata (2.5 kB)
Downloading kaitaistruct-0.10-py2.py3-none-any.whl (7.0 kB)
Installing collected packages: kaitaistruct
Successfully installed kaitaistruct-0.10

The Kaitai compiler can be downloaded from the official website.

After installation, you can use the compiler ...

kaitai-struct-compiler.bat --version
kaitai-struct-compiler 0.10
...
kaitai-struct-compiler.bat --help
kaitai-struct-compiler 0.10
Usage: kaitai-struct-compiler [options] ...

  ...                source files (.ksy)
  -t, --target   target languages (graphviz, csharp, rust, all, perl, java, go, cpp_stl, php, lua, python, nim, html, ruby, construct, javascript)
  -d, --outdir 
                           output directory (filenames will be auto-generated); on Unix-like shells, the short form `-d` requires arguments to be preceded by `--`
  -I, --import-path ;;...
                           .ksy library search path(s) for imports (see also KSPATH env variable)
  --cpp-namespace 
                           C++ namespace (C++ only, default: none)
  --cpp-standard 
                           C++ standard to target (C++ only, supported: 98, 11, default: 98)
  --go-package    Go package (Go only, default: none)
  --java-package 
                           Java package (Java only, default: root package)
  --java-from-file-class 
                           Java class to be invoked in fromFile() helper (default: io.kaitai.struct.ByteBufferKaitaiStream)
  --dotnet-namespace 
                           .NET Namespace (.NET only, default: Kaitai)
  --php-namespace 
                           PHP Namespace (PHP only, default: root package)
  --python-package 
                           Python package (Python only, default: root package)
  --nim-module     Path of Nim runtime module (Nim only, default: kaitai_struct_nim_runtime)
  --nim-opaque     Directory of opaque Nim modules (Nim only, default: directory of generated module)
  --opaque-types    opaque types allowed, default: false
  --ksc-exceptions         ksc throws exceptions instead of human-readable error messages
  --ksc-json-output        output compilation results as JSON to stdout
  --verbose         verbose output
  --no-auto-read           disable auto-running `_read` in constructor
  --read-pos               `_read` remembers attribute positions in stream
  --debug                  same as --no-auto-read --read-pos (useful for visualization tools)
  --help                   display this help and exit
  --version                output version information and exit

Steps to use this tool with Python. You need to use a defined kaitai file format for your file type - for example, gif file format, compile this kaitai then you can use it in this manner:

from kaitaistruct import __version__ as ks_version, KaitaiStruct, KaitaiStream, BytesIO
import mmap
print('kaitai version : ', ks_version)
f = open("python_giphy.gif", "rb")
with mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as buf:
    stream = KaitaiStream(BytesIO(buf))
    obj1 = print(stream)
    obj2 = print(stream)
    obj3 = print(stream)
stream.close()

I only test a little but is a great tool.

Kaitai Struct is free and open-source software, licensed under the following terms: Compiler and visualizer — GPLv3+ and these Runtime libraries:

• C++/STL — MIT
• C# — MIT
• Go — MIT
• Java — MIT
• JavaScript — Apache v2
• Lua — MIT
• Nim — MIT
• Perl — MIT
• PHP — MIT
• Python — MIT
• Ruby — MIT
• Rust — MIT
• Swift — MIT

Is easier to understand if you use the IDE on the web. On the left side you can see a cloud icon for upload, first, select the kaitai GIF type from formats/image/gif.ksy from web IDE, then select a GIF file from your computer and upload.

The default IDE looks like this:

You can use the kaitai online IDE.

Python 3.10.12 : YOLOv9 with GELAN-C model on colab notebook - part 045.

Today I tested YOLOv9 with GELAN-C model. Find the notebook on my GitHub repo.

Python 3.10.12 : Few example for CUDA and NVCC - part 044.

NVCC use CUDA C/C++ source code and allows developers to write high-performance GPU-accelerated applications by leveraging the power of NVIDIA GPUs for parallel processing tasks.

Today I test some simple examples with this tool on Google Colab using the nvcc4jupyter python package.

You need to install it with the pip and know how to use the CUDA C/C++ source code, or use the basic example from documentation.

pip install nvcc4jupyter

I change some source code because is need to install this library and I don't have time to learn and test.

But this will allow me to test better, because on my desktop I don't have a good hardware.

This is the source I change and I cut the source code linked on error_handling.h.

This is the changed source code , you can see more on my GitHub repo for Google Colab ! !

#include 
//#include "error_handling.h"

const int DSIZE = 4096;
const int block_size = 256;

// vector add kernel: C = A + B
__global__ void vadd(const float *A, const float *B, float *C, int ds){
    int idx = threadIdx.x + blockIdx.x * blockDim.x;
    if (idx < ds) {
        C[idx] = A[idx] + B[idx];
    }
}

int main(){
    float *h_A, *h_B, *h_C, *d_A, *d_B, *d_C;

    // allocate space for vectors in host memory
    h_A = new float[DSIZE];
    h_B = new float[DSIZE];
    h_C = new float[DSIZE];

    // initialize vectors in host memory to random values (except for the
    // result vector whose values do not matter as they will be overwritten)
    for (int i = 0; i < DSIZE; i++) {
        h_A[i] = rand()/(float)RAND_MAX;
        h_B[i] = rand()/(float)RAND_MAX;
    }

    // allocate space for vectors in device memory
    cudaMalloc(&d_A, DSIZE*sizeof(float));
    cudaMalloc(&d_B, DSIZE*sizeof(float));
    cudaMalloc(&d_C, DSIZE*sizeof(float));
    //cudaCheckErrors("cudaMalloc failure"); // error checking

    // copy vectors A and B from host to device:
    cudaMemcpy(d_A, h_A, DSIZE*sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(d_B, h_B, DSIZE*sizeof(float), cudaMemcpyHostToDevice);
    //cudaCheckErrors("cudaMemcpy H2D failure");

    // launch the vector adding kernel
    vadd<<<(DSIZE+block_size-1)/block_size, block_size>>>(d_A, d_B, d_C, DSIZE);
    //cudaCheckErrors("kernel launch failure");

    // wait for the kernel to finish execution
    cudaDeviceSynchronize();
    //cudaCheckErrors("kernel execution failure");

    cudaMemcpy(h_C, d_C, DSIZE*sizeof(float), cudaMemcpyDeviceToHost);
    //cudaCheckErrors("cudaMemcpy D2H failure");

    printf("A[0] = %f\n", h_A[0]);
    printf("B[0] = %f\n", h_B[0]);
    printf("C[0] = %f\n", h_C[0]);
    return 0;
}

This is result ...

A[0] = 0.840188
B[0] = 0.394383
C[0] = 0.000000

Python 3.12.1 : Simple view for sqlite table with PyQt6.

This is the source code that show you how to use QSqlDatabase, QSqlQuery, QSqlTableModel:

import sys
from PyQt6.QtWidgets import QApplication, QMainWindow, QTableView
from PyQt6.QtSql import QSqlDatabase, QSqlQuery, QSqlTableModel

class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()

        # Initialize the database
        self.init_db()

        # Set up the GUI
        self.table_view = QTableView(self)
        self.setCentralWidget(self.table_view)

        # Set up the model and connect it to the database
        self.model = QSqlTableModel(self)
        self.model.setTable('files')
        self.model.select()
        self.table_view.setModel(self.model)

    def init_db(self):
        # Connect to the database
        db = QSqlDatabase.addDatabase('QSQLITE')
        db.setDatabaseName('file_paths.db')
        if not db.open():
            print('Could not open database')
            sys.exit(1)

    def create_table(self):
        # Create the 'files' table if it doesn't exist
        query = QSqlQuery()
        query.exec('CREATE TABLE IF NOT EXISTS files (id INTEGER PRIMARY KEY, path TEXT)')

if __name__ == '__main__':
    app = QApplication(sys.argv)
    window = MainWindow()
    window.show()
    sys.exit(app.exec())

Python 3.12.1 : Simple browser with PyQt6-WebEngine.

This is a source code for a minimal browser with PyQt6 and PyQt6-WebEngine.

You need to install it with the pip tool:

pip install PyQt6 PyQt6-WebEngine

You can update the pip tool with

python.exe -m pip install --upgrade pip

Create a python script use the source code and run it.

Let's see the source code:

import sys
from PyQt6.QtCore import QUrl
from PyQt6.QtGui import QKeySequence, QAction
from PyQt6.QtWidgets import QApplication, QMainWindow, QLineEdit, QToolBar
from PyQt6.QtWebEngineWidgets import QWebEngineView
 
class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()
         
        # Create a web view
        self.web_view = QWebEngineView()
        self.web_view.setUrl(QUrl("127.0.0.1"))
        self.setCentralWidget(self.web_view)
 
        # Create a toolbar
        toolbar = QToolBar()
        self.addToolBar(toolbar)
         
        # Add a back action to the toolbar
        back_action = QAction("Back", self)
        back_action.setShortcut(QKeySequence("Back"))
        back_action.triggered.connect(self.web_view.back)
        toolbar.addAction(back_action)
         
        # Add a forward action to the toolbar
        forward_action = QAction("Forward", self)
        forward_action.setShortcut(QKeySequence("Forward"))
        forward_action.triggered.connect(self.web_view.forward)
        toolbar.addAction(forward_action)
         
        # Add a reload action to the toolbar
        reload_action = QAction("Reload", self)
        reload_action.setShortcut(QKeySequence("Refresh"))
        reload_action.triggered.connect(self.web_view.reload)
        toolbar.addAction(reload_action)
         
        # Add a search bar to the toolbar
        self.search_bar = QLineEdit()
        self.search_bar.returnPressed.connect(self.load_url)
        toolbar.addWidget(self.search_bar)
         
         
    def load_url(self):
        url = self.search_bar.text()
        if not url.startswith("http"):
            url = "https://" + url
        self.web_view.load(QUrl(url))
         
if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = MainWindow()
    window.show()
    app.exec()