Forem: Mate Technologies

DupCleaner PRO v4.1.0 – Professional Duplicate File Cleaner for Developers and Power Users

Mate Technologies — Wed, 15 Apr 2026 08:41:00 +0000

If you’ve ever worked with large datasets, design assets, or development projects, you know how quickly duplicate files can pile up. DupCleaner PRO v4.1.0 is a professional desktop tool designed to scan, detect, and clean duplicate files efficiently, safely, and reliably.

Why Developers & Power Users Will Love It

DupCleaner PRO isn’t just a basic cleaner — it’s engineered for performance and control:

Fast Multi-threaded Scanning: Groups files by size first, then hashes them using SHA256 for precise duplicate detection.
Safe Deletion: Files are moved to the Recycle Bin; permissions are fixed automatically if needed.
Smart Cleaning: Keeps the largest and newest version while safely removing redundant files.
Preview & Verify: Supports thumbnails and full-size previews for images (PNG, JPG, GIF, BMP, TIFF).
Export Detailed Reports: CSV reports with file paths, sizes, last modified dates, and hashes — perfect for auditing or record keeping.
How It Works
Add Files or Folders: Add individual files or entire directories. DupCleaner PRO can handle large datasets efficiently.
Scan: Files are grouped and hashed, duplicates detected. Progress is displayed in real-time, with pause/resume support.
Review Duplicates: Duplicate groups appear in the UI with file size, modification date, and thumbnail previews.
Smart Clean: Safely remove duplicates while keeping your most relevant files intact.
Export Report: Save a detailed CSV for auditing or documentation.
Built for Professionals

Whether you’re a developer, designer, data analyst, or IT professional, DupCleaner PRO simplifies file management, reduces clutter, and improves productivity.

Getting Started

DupCleaner PRO v4.1.0 is ready to use on Windows and comes with a modern, dark-themed interface. It’s designed to be fast, safe, and intuitive, even for large projects with thousands of files.

💻 Buy or download now: https://gum.new/gum/cmn028ko9000004l2dkhjcxt5

Key Features
✅ Multi-threaded scan & hash
✅ Safe deletion with Recycle Bin support
✅ Pause/resume scanning
✅ Smart Clean to retain the newest/largest file
✅ Image preview with thumbnails
✅ CSV report export

PDFSnap – Convert PDFs to PNG or JPG Effortlessly

Mate Technologies — Tue, 14 Apr 2026 13:00:00 +0000

Get PDFSnap Here →

If you often work with PDFs and need high-quality images for documentation, presentations, or archiving, PDFSnap is a Windows-based tool designed to make PDF-to-image conversion fast, flexible, and professional.

Overview

PDFSnap is a lightweight desktop application built with Python and ttkbootstrap
, providing a sleek dark-themed GUI. It allows:

Single PDF conversion
Batch folder mode
Automatic subfolder creation per PDF
Preservation of original page numbers in filenames
Threaded conversion with live progress logging

It supports output in both PNG and JPG formats.

Key Features
Convert PDF pages to images – High-resolution PNG or JPG output.
Batch folder mode – Process multiple PDFs in one go.
Organized output – Automatically create subfolders for each PDF.
Flexible naming – Preserve original page numbers or use custom prefixes.
Real-time feedback – Live log updates and progress bar.
Dark-themed GUI – Modern, user-friendly interface using ttkbootstrap.
How It Works
Select a PDF or Folder – Choose a single PDF or an entire folder containing PDFs.
Set Output Options – Choose PNG or JPG, select an output folder, and set naming preferences.
Start Conversion – Click Start Conversion. The app processes PDFs in a separate thread, showing live logs and progress.
Stop Anytime – The Stop button lets you safely halt the process if needed.
Advanced Options
Preserve Original Page Numbers: Keeps filenames like Page1, Page2, etc.
Create Subfolder per PDF: Keeps output organized automatically.
Batch Folder Mode: Perfect for handling large PDF collections efficiently.
Typical Use Cases
Converting multi-page PDFs into individual image files for documentation or web use.
Quickly exporting pages from a large PDF library into JPG/PNG format.
Professional workflows requiring organized image output from PDFs.
Installation & Requirements
Windows OS
Python 3.x (if using the source code) or precompiled executable
Ghostscript installed for PDF rendering (required for image conversion)
Developer & Support

PDFSnap
Developed by Mate Technologies
Purchase / Download PDFSnap

Tip: Use batch mode with subfolder creation to keep your output neat when processing multiple PDFs.

This version keeps it concise, highlights features, workflow, and use cases, and links directly to your Gumroad page.

CSVtoExcel PRO v3.0.0 – Convert CSV to Excel Effortlessly (Offline, Batch, Styled Export)

Mate Technologies — Mon, 13 Apr 2026 10:58:00 +0000

CSVtoExcel PRO is a professional desktop application built for developers, data analysts, business professionals, and researchers who need a fast, reliable, and fully offline solution to convert CSV files into clean, structured Excel workbooks.

Whether you’re working with large datasets, preparing reports, or migrating data, CSVtoExcel PRO simplifies your workflow with multi-sheet export, smart delimiter detection, batch processing, drag & drop support, and live progress tracking.

💻 Get it here: https://gum.new/gum/cmmxp3gh6000g04l8cxzjd0nq

Key Features

Multi-sheet Excel export for large CSV files

Automatic delimiter detection (comma, semicolon, tab, etc.)

Clean uneven or broken CSV rows automatically

Batch processing for multiple files or entire folders

Drag & drop support for faster workflow

Conversion history tracking with SQLite

Preview first 200 rows before converting

Bold headers and auto-adjusted column widths

Support for UTF-8, Latin1, UTF-16, CP1252 encodings

Live progress updates and cancel conversion anytime

Modern dark-themed interface built with Tkinter + ttkbootstrap

Optional Python source code for full customization

How It Works

Add Files or Folder – Select individual CSV files or load an entire folder.

Preview Data – Check the first 200 rows, auto-detect delimiters, and choose whether to use headers.

Configure Options – Set output folder, choose encoding, enable/disable headers.

Convert CSV to Excel – Start conversion with live progress, batch processing, and multi-sheet splitting for large files.

View History – Track all previous conversions and manage files.

All processing is local. No cloud uploads, no internet required. Your data remains fully secure.

Workflow & Productivity Tips

Batch Conversion – Convert hundreds of CSV files in one go.

Drag & Drop – Easily add multiple files.

Live Progress – Monitor current file, row progress, and total conversion percentage.

Cancel Anytime – Stop long-running conversions safely.

Styled Output – Excel sheets come with bold headers and auto-adjusted column widths.

History Tracking – Keep a full record of previous conversions for auditing or reuse.

Who Is This For?

Data Analysts & Researchers

Business Professionals & Accountants

Developers handling CSV exports

Students working with large datasets

Anyone who needs clean Excel exports from CSV files

Versions & Pricing

EXE Version: $7 – Ready-to-run Windows executable, no Python required

Full Python Source Code: $10 – Fully editable code for customization

EXE + Full Source Code: $12 – Best of both worlds

📥 Get it now: https://gum.new/gum/cmmxp3gh6000g04l8cxzjd0nq

System Requirements

Windows 10+ (EXE version)

Python 3.10+ (source code version)

Packages: xlsxwriter, Tkinter, ttkbootstrap

Optional: pandas (for custom CSV preprocessing)

Fully offline execution, no internet required

CSVtoExcel PRO is designed to make CSV → Excel conversion professional, fast, and completely offline. Whether you just want a ready-to-use EXE or the full Python source for customization, it’s your all-in-one solution for handling CSV files like a pro.

🔗 LinkVault PRO v2.0.0 – Professional Link Extraction Tool

Mate Technologies — Sun, 12 Apr 2026 12:52:00 +0000

LinkVault PRO is a production-ready Python tool designed for extracting URLs from TXT, PDF, and HTML files in a folder recursively. It supports file type filtering, duplicate removal, and exports results in TXT, JSON, or PDF formats with a glowing progress interface.

Get it here: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

Features
✅ Recursive folder scanning
✅ File type filtering: .txt, .pdf, .html/.htm
✅ Duplicate link filtering
✅ Glowing progress bar with ETA and speed
✅ Copy links to clipboard
✅ Open links by double-click
✅ Export results to TXT, JSON, or PDF
Installation

Install dependencies

pip install ttkbootstrap PyPDF2 reportlab

Download the executable version from Gumroad: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

How to Use
Launch LinkVault PRO.
Select your target folder.
Choose which file types to scan (.txt, .pdf, .html).
Click START EXTRACTION to begin.
Monitor the progress, ETA, and speed in real time.
Once complete, you can export results to TXT, JSON, or PDF.

💡 Tips:

Double-click a link in the results to open it.
Right-click a link to open the folder containing the source file.
Copy links to clipboard by clicking once.
Use STOP to safely cancel extraction anytime.
Export Options
TXT – One link per line, ideal for documentation or scripts.
JSON – Structured export with timestamp and version info.
PDF – Report-ready format with all links listed.
Developer Info

LinkVault PRO v2.0
Developed by MateTools

Gumroad Link →

Screenshots / UI Highlights
Clean, dark-themed interface using ttkbootstrap
Tree view for extracted links with copy, open, and folder navigation
Progress bar with ETA, speed, and live counter
Export buttons for all supported formats
Code Snippet – Extraction Engine

def extract_links_worker(folder, file_types):
    global link_results, link_count
    link_results.clear()
    link_count = 0

    files = [
        os.path.join(root, f)
        for root, _, fs in os.walk(folder)
        for f in fs
        if (f.endswith('.txt') and file_types['txt']) or
           (f.endswith('.pdf') and file_types['pdf']) or
           (f.endswith(('.html', '.htm')) and file_types['html'])
    ]

    for i, path in enumerate(files, 1):
        urls = []
        ext = os.path.splitext(path)[1].lower()
        if ext in ['.txt', '.html', '.htm']:
            with open(path, 'r', encoding='utf-8', errors='ignore') as f:
                urls = re.findall(r"https?://[^\s\"'>]+", f.read())
        elif ext == '.pdf':
            with open(path, 'rb') as f:
                reader = PyPDF2.PdfReader(f)
                for page in reader.pages:
                    text = page.extract_text()
                    if text: urls.extend(re.findall(r"https?://[^\s\"'>]+", text))

        for url in urls:
            if url not in link_results:
                link_results.append(url)

LinkVault PRO v2.0.0 is perfect for developers, researchers, content managers, or anyone who needs to quickly collect and organize links from multiple file types in bulk.

Grab your copy here: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

🚀 Build a CSV to Excel Desktop App (PySide6 + SQLite)

Mate Technologies — Sat, 11 Apr 2026 12:30:00 +0000

🔗 GitHub Repo: https://github.com/rogers-cyber/CSVtoExcel

In this tutorial, you’ll learn how to build a modern desktop app that:

Converts CSV → Excel (.xlsx)

Shows a preview of data

Saves history using SQLite

Supports batch processing

🧱 Step 1 — Install Dependencies

First, install required packages:

pip install PySide6 xlsxwriter

🧠 Step 2 — Project Structure

Create a simple structure:

csv_to_excel_app/
│
├── main.py
└── logo.ico (optional)
⚙️ Step 3 — Basic App Setup

Let’s create a minimal PySide6 app window.

import sys
from PySide6 import QtWidgets

app = QtWidgets.QApplication(sys.argv)

window = QtWidgets.QMainWindow()
window.setWindowTitle("CSVtoExcel")
window.resize(800, 500)

window.show()
sys.exit(app.exec())

👉 This gives you a blank desktop window.

🗂 Step 4 — Create App Data Folder

We store history (SQLite DB) in a system-safe location.

from pathlib import Path
import os
import sys

def get_app_dir() -> Path:
    if sys.platform.startswith("win"):
        base = Path(os.getenv('LOCALAPPDATA') or Path.home())
    elif sys.platform.startswith("darwin"):
        base = Path.home() / 'Library/Application Support'
    else:
        base = Path.home() / '.local/share'

    app_dir = base / "csv_to_excel_app"
    app_dir.mkdir(parents=True, exist_ok=True)
    return app_dir

🗄 Step 5 — Setup SQLite Database

We store conversion history.

import sqlite3

DB_PATH = get_app_dir() / "history.db"

def init_db():
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()

    c.execute("""
        CREATE TABLE IF NOT EXISTS history(
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            src_path TEXT,
            dest_path TEXT,
            timestamp TEXT,
            rows INTEGER,
            cols INTEGER
        )
    """)

    conn.commit()
    conn.close()

👉 Call this once when the app starts.

📥 Step 6 — Load CSV File

Let users pick a CSV file.

from PySide6.QtWidgets import QFileDialog

def open_csv():
    file, _ = QFileDialog.getOpenFileName(
        None,
        "Open CSV",
        "",
        "CSV Files (*.csv)"
    )
    return file

👁 Step 7 — Preview CSV Data

We read first 100 rows.

import csv

def preview_csv(path, limit=100):
    rows = []

    with open(path, encoding="utf-8", errors="replace") as f:
        reader = csv.reader(f)
        for i, row in enumerate(reader):
            if i >= limit:
                break
            rows.append(row)

    return rows

👉 This keeps the app fast even with large files.

📊 Step 8 — Convert CSV → Excel

Now the core feature 🔥

import xlsxwriter

def convert_to_excel(csv_path, output_path):
    with open(csv_path, encoding="utf-8", errors="replace") as f:
        reader = csv.reader(f)
        rows = list(reader)

    workbook = xlsxwriter.Workbook(output_path, {'strings_to_urls': False})
    sheet = workbook.add_worksheet()

    for r, row in enumerate(rows):
        for c, value in enumerate(row):
            sheet.write(r, c, value)

    workbook.close()

🧾 Step 9 — Save History

Every conversion is stored.

from datetime import datetime

def save_history(src, dest, rows, cols):
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()

    c.execute(
        "INSERT INTO history (src_path, dest_path, timestamp, rows, cols) VALUES (?, ?, ?, ?, ?)",
        (src, dest, datetime.utcnow().isoformat(), rows, cols)
    )

    conn.commit()
    conn.close()

🧵 Step 10 — Run Conversion in Background

We avoid freezing the UI using threads.

from PySide6.QtCore import QRunnable, QThreadPool

class Worker(QRunnable):
    def __init__(self, csv_path, output):
        super().__init__()
        self.csv_path = csv_path
        self.output = output

    def run(self):
        convert_to_excel(self.csv_path, self.output)

Run it:

pool = QThreadPool()
pool.start(Worker("input.csv", "output.xlsx"))

🖥 Step 11 — Build UI Layout

Add buttons + table preview.

layout = QtWidgets.QVBoxLayout()

btn_open = QtWidgets.QPushButton("Open CSV")
btn_convert = QtWidgets.QPushButton("Convert")

table = QtWidgets.QTableWidget()

layout.addWidget(btn_open)
layout.addWidget(btn_convert)
layout.addWidget(table)

🎨 Step 12 — Add Styling (QSS)

app.setStyleSheet("""
QPushButton {
    background: #1976d2;
    color: white;
    padding: 6px;
    border-radius: 6px;
}
QPushButton:hover {
    background: #125aa0;
}
""")

📦 Step 13 — Build EXE (Optional)

Use PyInstaller:

pip install pyinstaller
pyinstaller --onefile --windowed main.py

🎉 Final Result

You now have a desktop app that:

✅ Converts CSV to Excel
✅ Handles large files
✅ Saves history
✅ Has a modern UI

💡 Pro Tips

Add drag & drop support

Add batch folder conversion

Add encoding selector

Add preview table model (QTableView)

🔗 Full Source Code

👉 https://github.com/rogers-cyber/CSVtoExcel

MetaClean v2.0.0 – Professional Image Metadata Cleaner

Mate Technologies — Fri, 10 Apr 2026 12:46:00 +0000

Download MetaClean v2.0.0

Overview

MetaClean v2.0.0 is a class-based, production-ready desktop tool designed for professional image metadata management and privacy protection. With support for batch processing, drag-and-drop, and safe pixel re-encoding, you can remove EXIF, GPS, and hidden metadata from multiple images in just a few clicks — all without losing visual quality.

Perfect for photographers, content creators, and anyone concerned about privacy, MetaClean ensures your images are clean and safe to share.

Key Features
Complete Metadata Removal: EXIF, GPS, and hidden camera metadata.
Batch Processing: Handle multiple images at once with progress tracking.
Safe Pixel Re-Encoding: Maintains visual quality after cleaning.
Metadata Preview: Inspect metadata before performing the cleanup.
Overwrite Originals with Backup: Automatic backup to prevent accidental data loss.
Drag & Drop Support: Easily add files or entire folders.
Export Cleanup Reports: Save results as JSON or TXT for auditing.
Professional UI: Dark & light mode support, built with ttkbootstrap.
How It Works
Add Images: Click ➕ Add Images or drag images into the application window.
Choose Options: Decide whether to overwrite originals or export cleaned copies.
Start Cleanup: Click 🔒 REMOVE METADATA to begin processing.
Monitor Progress: Watch live progress and stop anytime with 🛑 STOP.
Export Reports: Save results in JSON or TXT formats for record-keeping.
Supported Formats

MetaClean supports the following image file types:

PNG
JPG / JPEG
WEBP
BMP
TIFF
Why MetaClean?

Sharing images online or sending them to clients can inadvertently expose sensitive data like location, camera details, and timestamps. MetaClean makes privacy-first image sharing effortless with professional-grade tools:

Fast, reliable, and lightweight
Batch operations save time
Easy-to-use interface with drag & drop support
Keeps backups when overwriting originals
Getting Started

MetaClean is ready to use after download — no complicated setup is required:

python MetaClean.py

For Windows users, simply double-click the .exe after building with PyInstaller or downloading the prebuilt package.

About the Developer

Mate Technologies is focused on building professional desktop tools for photographers and content creators.

Website & download: https://gum.new/gum/cmki9hb0s000204l402y17n9c

MetaClean v2.0.0 gives you complete control over your image metadata — safe, fast, and professional. Clean your images before sharing with confidence.

Building a Professional Image Converter in Python – Step by Step

Mate Technologies — Thu, 09 Apr 2026 06:16:00 +0000

You can find the full script here: Image_Convert_BUSINESS_PRO_v2.py

In this tutorial, we’ll build SnapConvert BUSINESS PRO, a professional image converter with a GUI, drag-and-drop support, license validation, history logging, and CSV export.

1️⃣ Importing Libraries

We start by importing all the necessary modules. This includes Python built-ins, GUI libraries, image processing, encryption, and threading.

import os
import sys
import csv
import time
import sqlite3   # for database storage
import hashlib
import base64
from threading import Thread
from PIL import Image, ImageTk

We also handle the resampling library, which is used for resizing images with high quality:

try:
    from PIL import ImageResampling
    RESAMPLE = ImageResampling.LANCZOS
except:
    RESAMPLE = Image.LANCZOS

Finally, we import GUI frameworks and encryption tools:

import ttkbootstrap as tb
from ttkbootstrap.constants import *
from tkinter import filedialog, messagebox, Listbox, Canvas, Scrollbar, simpledialog
from tkinterdnd2 import TkinterDnD, DND_FILES
from cryptography.fernet import Fernet

Tip: ttkbootstrap is like a modern theme for Tkinter, and tkinterdnd2 enables drag-and-drop support.

2️⃣ Application Info and Paths

Define basic app info and important paths:

APP_NAME = "SnapConvert BUSINESS PRO"
APP_VERSION = "2.1"

BASE_DIR = os.path.dirname(sys.argv[0])
DB_NAME = os.path.join(BASE_DIR, "snapconvert.db")
OUTPUT_DIR = os.path.join(BASE_DIR, "converted")
LOG_FILE = os.path.join(BASE_DIR, "conversion.log")
LICENSE_FILE = os.path.join(BASE_DIR, "license.key")

Why: Keeping paths centralized makes it easier to manage files and database locations.

3️⃣ License Management

We protect the app with a license system. Valid licenses are encrypted with Fernet.

SECRET_KEY = base64.urlsafe_b64encode(hashlib.sha256(b"MySuperSecretBusinessKey2026").digest())
fernet = Fernet(SECRET_KEY)
VALID_LICENSES = ["PRO-2026-XYZ123", "PRO-2026-ABC789"]

def encrypt_license(key: str) -> str:
    return fernet.encrypt(key.encode()).decode()

def decrypt_license(enc: str) -> str:
    try:
        return fernet.decrypt(enc.encode()).decode()
    except:
        return None

The app checks for a valid license file or prompts the user to enter one:

def check_license():
    if os.path.exists(LICENSE_FILE):
        with open(LICENSE_FILE,"r") as f:
            encrypted = f.read().strip()
        key = decrypt_license(encrypted)
        if key in VALID_LICENSES:
            return True
    key = simpledialog.askstring("License Required","Enter your license key:")
    if key in VALID_LICENSES:
        with open(LICENSE_FILE,"w") as f:
            f.write(encrypt_license(key))
        messagebox.showinfo("License Activated","License activated successfully!")
        return True
    else:
        messagebox.showerror("Invalid License","License key is invalid. Exiting application.")
        return False

4️⃣ Database for Conversion History

We use SQLite to store the history of converted images:

def init_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("""CREATE TABLE IF NOT EXISTS history(
        id INTEGER PRIMARY KEY,
        name TEXT,
        original TEXT,
        converted TEXT)""")
    conn.commit()
    conn.close()

Insert, fetch, and clear history functions:

def insert_db(name, orig, conv):
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("INSERT INTO history(name, original, converted) VALUES(?,?,?)",(name,orig,conv))
    conn.commit()
    conn.close()
def fetch_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("SELECT name, original, converted FROM history ORDER BY id DESC")
    rows = c.fetchall()
    conn.close()
    return rows
def clear_history():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("DELETE FROM history")
    conn.commit()
    conn.close()

Tip: Logging all conversions helps users track what they’ve done and export history to CSV.

5️⃣ Logging and Exporting History

We log events to a file:

def log_event(msg):
    with open(LOG_FILE,"a") as f:
        f.write(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] {msg}\n")

And provide a way to export conversion history:

def export_history_csv():
    rows = fetch_db()
    if not rows:
        messagebox.showinfo("Export History","No history to export")
        return
    path = filedialog.asksaveasfilename(defaultextension=".csv", filetypes=[("CSV file","*.csv")])
    if path:
        with open(path,"w", newline="", encoding="utf-8") as f:
            writer = csv.writer(f)
            writer.writerow(["Name","Original Path","Converted Path"])
            writer.writerows(rows)
        messagebox.showinfo("Export History", f"Exported {len(rows)} records")

6️⃣ Image Conversion Worker

We process images in a separate thread for smooth UI responsiveness:

def worker(images, fmt, out, quality, resize, keep, progress, finish):
    os.makedirs(out, exist_ok=True)
    total = len(images)
    count = 0

    for i, path in enumerate(images):
        try:
            with Image.open(path) as img:
                if resize>0:
                    img = img.resize((resize, resize), RESAMPLE)
                if fmt=="JPEG" and img.mode in ("RGBA","P"):
                    img=img.convert("RGB")
                name=os.path.splitext(os.path.basename(path))[0]
                if not keep:
                    name+=f"_{i+1}"
                out_path=os.path.join(out,f"{name}.{fmt.lower()}")
                c=1
                while os.path.exists(out_path):
                    out_path=os.path.join(out,f"{name}_{c}.{fmt.lower()}")
                    c+=1
                params={"quality":quality} if fmt=="JPEG" else {}
                img.save(out_path, fmt, **params)
                insert_db(name,path,out_path)
                count+=1
        except Exception as e:
            log_event(f"Error converting {path}: {e}")
        progress(int((i+1)/total*100))
    finish(count)

Tip: This ensures the UI doesn’t freeze when converting large batches.

7️⃣ Building the GUI

We use ttkbootstrap for a modern look and TkinterDnD for drag-and-drop:

Left panel: File list and buttons to add/remove images

Center panel: Thumbnail gallery of images

Right panel: Settings like format, quality, resize, and conversion button

Bottom: Conversion history table

class App:
    def __init__(self):
        if not check_license(): sys.exit()
        self.root = TkinterDnD.Tk()
        self.root.title(APP_NAME)
        self.root.geometry("1250x750")
        self.style = tb.Style("darkly")

        self.images=[]
        self.thumbs=[]

        self.create_menu()
        self.build_ui()
        self.load_history()

We register the drop target:

self.root.drop_target_register(DND_FILES)
self.root.dnd_bind("<<Drop>>", self.drop)

8️⃣ Running the App

Finally, initialize the database and start the app:

if __name__=="__main__":
    init_db()
    App().run()

✅ That’s it! You now have a fully functional image converter with GUI, drag-and-drop, database history, and licensing.

You can explore the full working version here: Image_Convert_BUSINESS_PRO_v2.py

LogSentinel v3.9 – Enterprise Log File Analyzer & Error Intelligence Tool

Mate Technologies — Wed, 08 Apr 2026 11:09:00 +0000

Managing massive log files can be a headache for developers, sysadmins, and IT teams. Enter LogSentinel v3.9 – Enterprise Edition, an ultra-fast log file analyzer designed to give you actionable insights without slowing you down.

Get LogSentinel v3.9 here →

Key Features
Ultra-Fast Analysis: Handle massive sets of .log and .txt files with a smooth, responsive UI.
Drag & Drop Support: Quickly add files or folders directly into the app (requires tkinterdnd2 for DnD support).
Advanced Filtering:
Include or exclude specific keywords.
Optional regex-based filters for precise searches.
Minimum log severity levels (DEBUG, INFO, WARNING, ERROR, CRITICAL).
Real-Time Log Intelligence:
Automatically detects log severity using built-in patterns.
Highlights CRITICAL, ERROR, and WARNING lines in the UI for fast triage.
Batch & Multi-Select: Scan multiple files at once and track progress in a treeview with checkboxes.
Export Results: Save selected results to a .txt file for reporting or sharing.
Smooth Progress Visualization: See live scanning stats and ETA with animated progress bars.
Cross-Platform Python App: Built with Tkinter, ttkbootstrap, and standard Python libraries.
Why Use LogSentinel?

Traditional log analysis often involves opening large files in editors or writing complex scripts. LogSentinel removes the friction by providing:

Speed – Handles hundreds of thousands of lines without freezing.
Focus – Highlight and filter the exact log entries you care about.
Flexibility – Regex, include/exclude keywords, and severity filters let you tailor your scans.
Ease of Use – Modern UI, drag & drop support, and one-click export.
Screenshots & Workflow
Drag & drop your log files or select a folder via the Browse button.
Set your filters: minimum severity, keywords, and optional regex.
Hit Start Scan – LogSentinel will analyze files in real time.
Check the results tree for log highlights and severity counts.
Export your findings to a text file for documentation.

Whether you’re debugging production errors, monitoring server logs, or analyzing app events, LogSentinel v3.9 gives you the power to process logs efficiently and intelligently.

Get it now on Gumroad →

Build a PDF Combiner GUI App in Python (Tkinter) — Step-by-Step Beginner Guide

Mate Technologies — Wed, 08 Apr 2026 05:04:00 +0000

In this tutorial, we will build PDFMate+, a full-featured PDF Combiner & Toolkit using Python and Tkinter.

By the end, you'll learn how to:

Merge PDFs
Convert images to PDF
Add drag & drop support
Create a page editor
Add progress bar & threading
Build a professional desktop UI

👉 Full Source Code:
https://github.com/rogers-cyber/PDFMatePlus

Step 1 — Install Dependencies

First install required packages:

pip install PyPDF2 pillow img2pdf tkinterdnd2 pypdf

Optional (for compression):

Install Ghostscript
https://ghostscript.com

Step 2 — Create Basic Tkinter Window

Start with a simple GUI window.

import tkinter as tk

root = tk.Tk()
root.title("PDFMate+")
root.geometry("900x600")

root.mainloop()

This creates the main application window.

Step 3 — Add Required Imports

Now we import all libraries needed for PDF processing and GUI.

import os
import threading
import tkinter as tk
from tkinter import ttk, filedialog, messagebox

from PIL import Image
from PyPDF2 import PdfWriter, PdfReader

These libraries help us:

Tkinter → UI
PIL → image conversion
PyPDF2 → merge PDFs
threading → background processing
Step 4 — Create Main App Class

We wrap everything in a class.

class PDFMateApp:
    def __init__(self, root):
        self.root = root
        self.root.title("PDFMate+")

        self.items = []

        self.build_ui()

This keeps code organized.

Step 5 — Build UI Layout

Now we create buttons and listbox.

def build_ui(self):
    frame = tk.Frame(self.root)
    frame.pack(fill="both", expand=True)

    self.listbox = tk.Listbox(frame)
    self.listbox.pack(fill="both", expand=True)

    btn = tk.Button(self.root, text="Add Files", command=self.add_files)
    btn.pack()

This gives us:

File list
Add button
Step 6 — Add File Selection

Now we allow users to select PDFs.

def add_files(self):
    files = filedialog.askopenfilenames(
        filetypes=[("PDF Files", "*.pdf")]
    )

    for file in files:
        self.items.append(file)
        self.listbox.insert(tk.END, file)

Users can now add multiple files.

Step 7 — Merge PDFs

This is the core feature.

def merge_pdfs(self):
    writer = PdfWriter()

    for file in self.items:
        reader = PdfReader(file)
        for page in reader.pages:
            writer.add_page(page)

    output = filedialog.asksaveasfilename(
        defaultextension=".pdf"
    )

    with open(output, "wb") as f:
        writer.write(f)

This merges all selected PDFs into one.

Step 8 — Add Merge Button

Add merge button to UI.

merge_btn = tk.Button(
    self.root,
    text="Merge PDFs",
    command=self.merge_pdfs
)
merge_btn.pack()

Step 9 — Add Image to PDF Support

Convert images before merging.

from PIL import Image

def image_to_pdf(self, image_path):
    img = Image.open(image_path).convert("RGB")
    temp = image_path + ".pdf"
    img.save(temp)
    return temp

This allows merging JPG/PNG.

Step 10 — Add Background Threading

Prevent UI freezing.

def start_merge(self):
    thread = threading.Thread(
        target=self.merge_pdfs,
        daemon=True
    )
    thread.start()

Now UI remains responsive.

Step 11 — Add Progress Bar

self.progress = ttk.Progressbar(
    self.root,
    orient="horizontal",
    mode="determinate"
)
self.progress.pack(fill="x")

Update during merge:

self.progress["value"] = percent

Step 12 — Add Drag & Drop Support

from tkinterdnd2 import TkinterDnD, DND_FILES

self.listbox.drop_target_register(DND_FILES)
self.listbox.dnd_bind("<<Drop>>", self.on_drop)

Handle dropped files:

def on_drop(self, event):
    files = self.root.tk.splitlist(event.data)
    for file in files:
        self.items.append(file)
        self.listbox.insert(tk.END, file)

Step 13 — Add Page Editor

Allow rotate/delete pages.

def rotate_page(page):
    page.rotate(90)

Delete pages:

writer = PdfWriter()

for i, page in enumerate(reader.pages):
    if i not in selected:
        writer.add_page(page)

Step 14 — Add Theme Toggle

def toggle_theme(self):
    self.dark = not self.dark

    bg = "#1e1e2f" if self.dark else "#ffffff"
    self.root.configure(bg=bg)

Step 15 — Final Main Function

def main():
    root = tk.Tk()
    app = PDFMateApp(root)
    root.mainloop()

if __name__ == "__main__":
    main()

Final Result

You now have a full desktop PDF tool:

✔ Merge PDFs
✔ Convert images
✔ Drag & drop
✔ Page editor
✔ Progress bar
✔ Threaded processing
✔ Theme toggle

Full Project

Complete production-ready code:

https://github.com/rogers-cyber/PDFMatePlus

What You Learned
Tkinter GUI
PDF merging
Image conversion
Threading
Drag & drop
Page editing
Desktop app architecture
Next Improvements

You can add:

PDF watermark
password protection
OCR
EXE build (PyInstaller)
auto update

Step-by-Step Guide: Building a Professional Image Converter in Python

Mate Technologies — Tue, 07 Apr 2026 06:02:00 +0000

In this tutorial, we’ll walk through building a desktop image converter in Python using Tkinter, Pillow, and ttkbootstrap. The full script is available here: GitHub link
.

We’ll cover:

Project setup

Database logging

Image conversion logic

GUI creation with drag-and-drop support

License verification system

1️⃣ Project Setup and Dependencies

First, install the required packages:

pip install pillow ttkbootstrap tkinterdnd2

Then, import the required modules:

import os, sys, sqlite3, csv, time
from threading import Thread
from PIL import Image, ImageTk

Optional for better resizing quality

try:
    from PIL import ImageResampling
    RESAMPLE = ImageResampling.LANCZOS
except:
    RESAMPLE = Image.LANCZOS

import ttkbootstrap as tb
from ttkbootstrap.constants import *
from tkinter import filedialog, messagebox, Listbox, Canvas, Scrollbar, simpledialog
from tkinterdnd2 import TkinterDnD, DND_FILES

Explanation:

Pillow handles image processing.

ttkbootstrap provides modern Tkinter themes.

tkinterdnd2 adds drag-and-drop file support.

We try to use ImageResampling.LANCZOS for better resizing but fallback if unavailable.

2️⃣ App Info and Paths

Define your app metadata and file paths:

APP_NAME = "Image Convert BUSINESS PRO"
APP_VERSION = "2.0"

BASE_DIR = os.path.dirname(sys.argv[0])
DB_NAME = os.path.join(BASE_DIR, "snapconvert.db")
OUTPUT_DIR = os.path.join(BASE_DIR, "converted")
LOG_FILE = os.path.join(BASE_DIR, "conversion.log")
LICENSE_FILE = os.path.join(BASE_DIR, "license.key")

Explanation:
This section sets up paths for your database, output folder, log file, and license file.

3️⃣ Database for Conversion History

We will log converted images into a SQLite database:

def init_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("""CREATE TABLE IF NOT EXISTS history(
        id INTEGER PRIMARY KEY,
        name TEXT,
        original TEXT,
        converted TEXT
    )""")
    conn.commit()
    conn.close()

To insert and fetch history:

def insert_db(name, orig, conv):
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("INSERT INTO history(name, original, converted) VALUES(?,?,?)", (name, orig, conv))
    conn.commit()
    conn.close()

def fetch_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("SELECT name, original, converted FROM history ORDER BY id DESC")
    rows = c.fetchall()
    conn.close()
    return rows

Explanation:

Every converted image is logged in the database with its original and converted paths.

History is fetched in descending order to show the latest conversions first.

4️⃣ Logging and Exporting History

Keep a log file of events:

def log_event(msg):
    with open(LOG_FILE, "a") as f:
        f.write(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] {msg}\n")

Export history as a CSV:

def export_history_csv():
    rows = fetch_db()
    if not rows:
        messagebox.showinfo("Export History","No history to export")
        return
    path = filedialog.asksaveasfilename(defaultextension=".csv", filetypes=[("CSV file","*.csv")])
    if path:
        with open(path,"w", newline="", encoding="utf-8") as f:
            writer = csv.writer(f)
            writer.writerow(["Name","Original Path","Converted Path"])
            writer.writerows(rows)
        messagebox.showinfo("Export History", f"Exported {len(rows)} records")

Explanation:

Every event is logged in a conversion.log file.

Users can export their history to a CSV for reference.

5️⃣ License System

You can secure your app using a simple license check:

VALID_LICENSES = ["PRO-2026-XYZ123", "PRO-2026-ABC789"]

def check_license():
    if os.path.exists(LICENSE_FILE):
        with open(LICENSE_FILE,"r") as f:
            key = f.read().strip()
        if key in VALID_LICENSES:
            return True
    key = simpledialog.askstring("License Required","Enter your license key:")
    if key and key in VALID_LICENSES:
        with open(LICENSE_FILE,"w") as f:
            f.write(key)
        messagebox.showinfo("License Activated","License activated successfully!")
        return True
    else:
        messagebox.showerror("Invalid License","The license key is invalid. App will exit.")
        return False

Explanation:

Checks for an existing license file.

Prompts the user if no valid license is found.

6️⃣ Image Conversion Worker

Core function to resize, convert, and save images:

def worker(images, fmt, out, quality, resize, keep, progress, finish):
    os.makedirs(out, exist_ok=True)
    total = len(images)
    count = 0

    for i, path in enumerate(images):
        try:
            with Image.open(path) as img:
                if resize>0:
                    img = img.resize((resize,resize), RESAMPLE)
                if fmt=="JPEG" and img.mode in ("RGBA","P"):
                    img = img.convert("RGB")
                name = os.path.splitext(os.path.basename(path))[0]
                if not keep:
                    name += f"_{i+1}"
                out_path = os.path.join(out, f"{name}.{fmt.lower()}")
                img.save(out_path, fmt, quality=quality if fmt=="JPEG" else None)
                insert_db(name, path, out_path)
                count += 1
        except Exception as e:
            log_event(f"Error converting {path}: {e}")
        progress(int((i+1)/total*100))
    finish(count)

Explanation:

Supports resizing and format conversion.

Handles JPEG transparency by converting to RGB.

Updates a progress bar and logs every conversion.

7️⃣ GUI Setup with Tkinter and ttkbootstrap

We’ll build a drag-and-drop GUI with a left file list, center gallery, and right settings panel. Example of adding files:

def add_files(self):
    self.add_images(filedialog.askopenfilenames())

def add_folder(self):
    folder = filedialog.askdirectory()
    imgs = []
    for r, _, f in os.walk(folder):
        for x in f:
            if x.lower().endswith(("png","jpg","jpeg","bmp","gif")):
                imgs.append(os.path.join(r, x))
    self.add_images(imgs)

Explanation:

Users can add single files or entire folders.

Only valid image extensions are accepted.

8️⃣ Run the App

Initialize the database and start the GUI:

if __name__=="__main__":
    init_db()
    App().run()

Explanation:

init_db() ensures the database exists.

App().run() launches the GUI.

✅ Full Script Reference

You can access the complete script here:
Image Convert BUSINESS PRO on GitHub

AutoDateInserter v1.2.0 – Professional Batch File Timestamp Renamer

Mate Technologies — Mon, 06 Apr 2026 11:06:00 +0000

Manage and organize your files effortlessly with AutoDateInserter v1.2.0 – a production-ready, class-based tool for batch renaming files with timestamps. Whether you need to prepend or append timestamps, preview changes, or safely undo actions, this tool has you covered.

Get AutoDateInserter here →

Features
Prepend or append timestamps to files for organized naming.
Preview planned renames before executing.
Undo last rename operation for safety.
Drag & drop support for files and folders.
Include subfolders recursively.
Dry-run mode for testing changes without touching files.
Pause & resume long operations.
ETA and throughput tracking.
Safe renaming with automatic conflict resolution.
Why AutoDateInserter?

Renaming files manually can be tedious and error-prone, especially when dealing with hundreds of documents or photos. AutoDateInserter automates the process while keeping it safe:

Keep photos in chronological order by prepending timestamps.
Track project file versions by appending timestamps.
Ensure unique filenames before backups.
Quickly batch rename scripts, documents, and reports.
Test renames safely with dry-run mode.
How It Works
Click ➕ Add Files or 📂 Add Folder (or drag & drop files).
Choose Prepend or Append timestamps.
Enable options like Include subfolders or Dry-run if needed.
Click 🔁 Preview to see the planned renames.
Click 🕒 RENAME FILES to execute, or ↩ UNDO LAST to revert.
Under the Hood

Built with Python, Tkinter, and ttkbootstrap, AutoDateInserter is:

Lightweight and portable.
Multi-threaded for smooth UI experience.
Compatible with drag & drop via tkinterdnd2 (if installed).
Logs all renaming actions for audit and undo functionality.
Who Should Use It?
Photographers organizing large photo libraries.
Developers & designers managing multiple file versions.
Students & professionals preparing files for backup.
Anyone needing a safe and fast batch renaming tool.
Developer & Support

AutoDateInserter v1.2.0
Developed by Mate Technologies
Official page: https://gum.new/gum/cmkqn8mu7000204ieg6mpbgb7

Download AutoDateInserter Now →

🚀 Build a Professional Image Converter GUI in Python (Step-by-Step)

Mate Technologies — Sun, 05 Apr 2026 05:37:00 +0000

👉 Full source code:
https://github.com/rogers-cyber/python-tiny-tools/blob/main/63-Image-resizer/ImageConvertPRO.py

🧠 What You’ll Build

In this tutorial, we’ll create a modern desktop app that can:

📂 Add images (files, folders, drag & drop)

🖼 Preview thumbnails

🔄 Convert formats (PNG, JPEG, WEBP, etc.)

📏 Resize images

💾 Save conversion history (SQLite)

⚡ Run conversions in background (no freezing UI)

📦 Step 1: Install Dependencies
pip install pillow ttkbootstrap tkinterdnd2
🔍 Why we need them:

Pillow → image processing

ttkbootstrap → modern UI styling

tkinterdnd2 → drag & drop support

📁 Step 2: Project Setup

Create a Python file:

image_convert_pro.py
⚙️ Step 3: Import Libraries

import os
import sys
import sqlite3
from threading import Thread
from PIL import Image, ImageTk

🧠 Explanation:

os, sys → file handling

sqlite3 → local database

Thread → run tasks without freezing UI

PIL → image processing

Handle Image Resampling (Important!)

try:
    from PIL import ImageResampling
    RESAMPLE = ImageResampling.LANCZOS
except:
    RESAMPLE = Image.LANCZOS

✔ This ensures compatibility across Pillow versions.

🎨 Step 4: Import UI Libraries

import ttkbootstrap as tb
from ttkbootstrap.constants import *
from tkinter import filedialog, messagebox, Listbox, Canvas, Scrollbar
from tkinterdnd2 import TkinterDnD, DND_FILES

🏷 Step 5: App Configuration

APP_NAME = "ImageConvert PRO"

APP_VERSION = "1.1"
📂 Step 6: Setup Paths

BASE_DIR = os.path.dirname(sys.argv[0])
DB_NAME = os.path.join(BASE_DIR, "snapconvert.db")
OUTPUT_DIR = os.path.join(BASE_DIR, "converted")

🗄 Step 7: Create Database
Create table

def init_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("""CREATE TABLE IF NOT EXISTS history(
        id INTEGER PRIMARY KEY,
        name TEXT,
        original TEXT,
        converted TEXT)""")
    conn.commit()
    conn.close()

Insert data

def insert_db(name, orig, conv):
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("INSERT INTO history(name, original, converted) VALUES(?,?,?)",(name,orig,conv))
    conn.commit()
    conn.close()
Fetch history
def fetch_db():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("SELECT name, original, converted FROM history ORDER BY id DESC")
    rows = c.fetchall()
    conn.close()
    return rows

Clear history

def clear_history():
    conn = sqlite3.connect(DB_NAME)
    c = conn.cursor()
    c.execute("DELETE FROM history")
    conn.commit()
    conn.close()

ℹ️ Step 8: About Dialog

def show_about():
    messagebox.showinfo(
        f"About {APP_NAME}",
        f"{APP_NAME} v{APP_VERSION}\n\n"
        "Professional Image Converter\n\n"
        "© 2026 Mate Technologies\n"
        "https://matetools.gumroad.com"
    )

⚡ Step 9: Image Processing Worker (Core Logic)
def worker(images, fmt, out, quality, resize, keep, progress, finish):
os.makedirs(out, exist_ok=True)
🔍 Loop through images

    for i, path in enumerate(images):
        try:
            with Image.open(path) as img:
Resize (optional)
                if resize > 0:
                    img = img.resize((resize, resize), RESAMPLE)
Convert format safely
                if fmt == "JPEG" and img.mode in ("RGBA","P"):
                    img = img.convert("RGB")
Save file
                img.save(out_path, fmt)
Update progress
        progress(int((i+1)/total*100))

Finish callback
finish(count)
🖥 Step 10: Build Main App Class

class App:
    def __init__(self):
        self.root = TkinterDnD.Tk()
        self.root.title(APP_NAME)
        self.root.geometry("1200x750")

📋 Step 11: Menu Bar

def create_menu(self):
    menubar = tb.Menu(self.root)
    help_menu = tb.Menu(menubar, tearoff=0)
    help_menu.add_command(label="About", command=show_about)
    menubar.add_cascade(label="Help", menu=help_menu)
    self.root.config(menu=menubar)

🧩 Step 12: Build UI Layout

We divide into 3 sections:

LEFT → File list

self.listbox = Listbox(left, bg="#1e1e1e", fg="white")

Buttons:

Add Images

Add Folder

Remove

Clear

CENTER → Image preview

self.canvas = Canvas(center, bg="#121212")

✔ Scrollable gallery

RIGHT → Settings panel

self.format = tb.Combobox(right, values=["PNG","JPEG","WEBP","BMP","TIFF"])

Options:

Format

Quality

Resize

Keep filename

Convert button
tb.Button(right, text="🚀 Convert", command=self.convert)
🖱 Step 13: Drag & Drop Support

self.root.drop_target_register(DND_FILES)
self.root.dnd_bind("<<Drop>>", self.drop)

🖼 Step 14: Render Image Gallery

def render_gallery(self):
    for i, path in enumerate(self.images[:50]):
        img = Image.open(path)
        img.thumbnail((150,150))

✔ Displays thumbnails in grid layout

🔄 Step 15: Convert Images (Threaded)

def convert(self):
    Thread(target=worker, args=(...), daemon=True).start()

🧠 Why threading?

Without it:
❌ UI freezes
With it:
✅ Smooth experience

📊 Step 16: Progress Bar

self.progress = tb.Progressbar(right)

Update:

self.progress.config(value=v)

🗑 Step 17: Delete History

def delete_history(self):
    if messagebox.askyesno("Confirm", "Delete all history?"):
        clear_history()

▶️ Step 18: Run the App

if __name__ == "__main__":
    init_db()
    App().run()

🎉 Final Result

You now have a fully functional desktop app with:

✅ Modern UI
✅ Drag & drop
✅ Image conversion
✅ Resize + quality control
✅ History tracking
✅ Multithreading

💡 Bonus Ideas (for improvement)

🔍 Add search in history

🌙 Light/Dark mode toggle

📦 Export history to CSV

⚡ Batch rename rules

🧠 AI auto image optimization