Python 3.13.16 : React frontend and python on Reflex Cloud.

Today, this simple test with artificial intelligence from reflex chat bot show how good and fast can be with one simple task.

Reflex compiles to a React frontend and a Starlette backend—the ASGI server that powers FastAPI. A familiar web stack, accessible to every Python developer. pandas, SQLAlchemy, scikit-learn, ...

After I ask to create a simple G.U.I. interface with all features from reflex, the chat bot result is this:

I built a one-page interactive playground that shows how a React-powered interface responds to Python state. Visitors can try five demos: a counter with event history, live preview controls, form validation, a searchable collection, and a dialog and toast.

Size: about 1,150 lines of Python across the page, four component modules, and four state modules. The integration section describes possibilities; it does not claim that external services are connected.

The interaction tests passed, and the page renders in the browser. I don’t have a reliable elapsed-time measurement for the build, so I can’t give an accurate creation time.

... the time of build was 4 minutes ...

Reflex comes with free features:

• Publish 1 app on Reflex Cloud
• Limited free usage for AI generation and hosting
• Refills periodically
• Public apps and public GitHub repos
• App code download and file editing
• Public sign-in with Reflex Auth
• Managed database

See the result online : this webpage.

Python 3.13.13 : using webz.io with python.

The webz.io can be used with python:

import requests

response = requests.get(
    "https://api.webz.io/api/news?token=YOUR-TOKEN&q=%28category%3A%22economy%2C+business+and+finance%22+OR+category
    %3A%22war%2C+conflict+and+unrest%22+OR+category%3A%22science+and+technology%22+OR+category%3A%22disaster+and+accident%22
    +OR+category%3A%22environment%22+
    OR+category%3A%22labor%22%29&sort=crawled&ts=1790410006113&format=json&size=10&
    webz_reporter=true&includeSyndicated=false&allowNewsHistory=false",
    headers={"Accept": "application/json"},
)
print(response.json())

tkinter : testing RapidFuzz.

RapidFuzz is a fast and powerful Python library used for fuzzy string matching and similarity scoring. It is designed as a drop-in, high-performance alternative to the popular fuzzywuzzy library, offering significantly faster execution speeds because its core algorithms are implemented in C++ (via pybind11).

​What Can RapidFuzz Do?

​Calculate String Similarity:

It measures how similar two strings are using various mathematical distances (such as Levenshtein distance, Hamming distance, Jaro-Winkler, and Normalized Similarity metrics), returning a score typically ranging from 0 (completely different) to 100 (exact match).

​Smart Search & Extraction (process module):

You can query a list of items (such as filenames, database records, or user inputs) and instantly extract the best matches, even if the user query contains typos, misspellings, or partial words.

​Data Cleaning & Deduplication:

It helps clean messy datasets by grouping entries that represent the same entity despite slight spelling variations (e.g., matching "John Smith" with "Jon Smith").

​Lightweight & Efficient:

Unlike heavy deep learning frameworks, RapidFuzz has minimal dependencies and runs smoothly across different environments—making it ideal for desktop applications, servers, and mobile development environments like Pydroid 3.

tkinter : fast image tool on pydroid3.

Today, one simple example fast tool for images:

Let's see this start source code:

# -*- coding: utf-8 -*-
"""Image Editor - consistent GUI sizes (Pydroid / Android)"""
import os
import shutil
import zipfile
from datetime import datetime
import tkinter as tk
from tkinter import ttk, filedialog, messagebox, font as tkfont
from PIL import Image, ImageTk, ImageOps, ImageEnhance
VALID_EXTS = (".png", ".jpg", ".jpeg", ".bmp", ".webp", ".gif", ".tiff", ".tif")
def get_android_start_dir():
    candidates = [
        "/storage/emulated/0", "/sdcard",
        "/storage/emulated/0/Download", "/sdcard/Download",
        "/storage/emulated/0/DCIM", "/sdcard/DCIM",
        "/storage/emulated/0/Pictures", "/sdcard/Pictures",
        os.path.expanduser("\~"), "/",
    ]
    for path in candidates:
        if os.path.isdir(path) and os.access(path, os.R_OK):
            return path
    return os.getcwd()
...

tkinter : basic portfolio for market with simulations ...

Today, one simple script tool for market. this allow to set one portofolio and use with simulations.

Let'see some screenshots:

The basic intro source code ...

import datetime
import json
import threading
import urllib.request
import tkinter as tk
from tkinter import ttk, messagebox

import matplotlib
matplotlib.use("TkAgg")
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg


def fetch_yahoo_history(symbol, period_years=1):
    """Descarcă istoricul zilnic de pe Yahoo Finance."""
    end_date = int(datetime.datetime.now().timestamp())
    start_date = int((datetime.datetime.now() - datetime.timedelta(days=365 * period_years)).timestamp())
    
    url = f"https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?period1={start_date}&period2={end_date}&interval=1d"
    req = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})
    
    try:
        with urllib.request.urlopen(req, timeout=10) as resp:
            data = json.loads(resp.read().decode("utf-8"))
            result = data["chart"]["result"][0]
            timestamps = result["timestamp"]
            closes = result["indicators"]["quote"][0]["close"]
            
            history = []
            for ts, cl in zip(timestamps, closes):
                if cl is not None:
                    dt = datetime.datetime.fromtimestamp(ts)
                    history.append((dt, float(cl)))
            return history
    except Exception as e:
        print(f"Eroare la descărcare {symbol}: {e}")
        return []
        ...

News : OpenAI python library released.

The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.10+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by HTTPX2.

See the official webpage.

News : PyPy new 8.0.0 version.

The PyPy team is proud to release version 8.0.0 of PyPy after the previous release on May 26, 2026. This is a major new version, hence the bump to 8.0.0. It is our first release of Python 3.12, which may still have some bugs so we are calling it "beta" quality.

PyPy is written in RPython, and has code generation to translate RPython into C as part of the VM build process. We have made some improvements to code generation in attempts to speed up the base interpreter.

See the official website.

tkinter : simple marshmallow demo.

About the marshmallow package

• It checks if your data has the correct fields.
• It verifies that each field has the right type.
• It helps you validate JSON before using it.
• It can convert Python data into clean JSON.

About your this source code:

• It loads the marshmallow package when the app starts.
• It reads the JSON you type in the input box.
• It tries to convert that text into Python data.
• It validates the data using your marshmallow schema.
• It shows the result or the error directly in the output box.
• It does not use print or message boxes.

Why this tool is useful

• You can test JSON visually.
• You can see validation errors instantly.
• You avoid console output.
• You keep everything inside the GUI.

Let's see the sourve code:

import json
import tkinter as tk
from tkinter import ttk

# ------------------ Package Load Test ------------------

try:
    from marshmallow import Schema, fields, ValidationError
    package_status = "Package marshmallow loaded successfully."
except Exception as e:
    package_status = "PACKAGE LOAD ERROR: " + str(e)


# ------------------ Marshmallow Schema ------------------

class PersonSchema(Schema):
    full_name = fields.Str(required=True)
    city = fields.Str(required=True)
    birth_date = fields.Date(required=True)
    nicknames = fields.List(fields.Str(), required=True)


schema = PersonSchema()


# ------------------ Tkinter UI ------------------

def process_json():
    raw = editor.get("1.0", tk.END).strip()

    output.delete("1.0", tk.END)

    # Step 1: package status
    output.insert(tk.END, package_status + "\n\n")

    # Step 2: show raw JSON
    output.insert(tk.END, "RAW JSON RECEIVED:\n" + raw + "\n\n")

    # Step 3: JSON parsing
    try:
        data = json.loads(raw)
        output.insert(tk.END, "JSON PARSED OK.\n\n")
    except Exception as e:
        output.insert(tk.END, "JSON ERROR:\n" + str(e))
        return

    # Step 4: Marshmallow validation
    try:
        result = schema.dump(data)
        output.insert(tk.END, "SCHEMA VALIDATION OK.\n\n")
    except ValidationError as e:
        output.insert(tk.END, "SCHEMA ERROR:\n" + json.dumps(e.messages, indent=2))
        return

    # Step 5: Final result
    output.insert(tk.END, "FINAL RESULT:\n" + json.dumps(result, indent=2))


root = tk.Tk()
root.title("Marshmallow Diagnostic Full Output")
root.geometry("750x550")

frm = ttk.Frame(root, padding=10)
frm.pack(fill="both", expand=True)

ttk.Label(frm, text="JSON Input:").pack(anchor="w")

editor = tk.Text(frm, height=14, width=90)
editor.pack(fill="x")

editor.insert(
    tk.END,
    json.dumps(
        {
            "full_name": "Catalin George Festila",
            "city": "Falticeni",
            "birth_date": "1976-03-07",
            "nicknames": ["catafest", "mythcat"]
        },
        indent=2
    )
)

ttk.Button(frm, text="Run", command=process_json).pack(pady=10)

ttk.Label(frm, text="Output:").pack(anchor="w")

output = tk.Text(frm, height=14, width=90)
output.pack(fill="both", expand=True)

root.mainloop()

News : Real-Time Stock & ETF Analyzer in using tvscreener and Tkinter and pydroid3.

The tvscreener is a lightweight Python library designed to extract and analyze real-time financial data directly from TradingView's API without requiring paid API keys or complex authentication. It provides quick access to technical indicators, fundamental metrics, historical performance, and volume data for international stocks and ETFs. Explore the source code and documentation on the official tvscreener GitHub repository. The script provides a desktop interface (Tkinter GUI) powered by tvscreener logic to query market data on demand. This allow to choose a ticker symbol from the dropdown list (such as GOOGL, NVDA, AAPL, or ETFs like VUAA). Clicking Check triggers a background HTTP request without freezing the user interface, while displaying real-time progress via the progress bar. The script formats the API response into four core metric categories: Performance, Technical Indicators, Fundamentals, and Volume and Liquidity. Clicking Copy transfers the complete output directly to your system clipboard for quick sharing or note-taking.

News : Inkscape MCP coding agent python module.

With Inkscape MCP, your coding agent can do everything a designer does in Inkscape — sketch and reshape paths, apply effects and filters, render LaTeX equations, generate barcodes and QR codes, convert between formats, query and rewrite document structure — through plain conversation instead of menu clicks.

See the oficial webpage.

News : Official Django developers survey 2026.

...the data set includes 3,468 responses.

See this survey on the official website.

News : SymPy youtube playlist ...

See the official youtube channel.

News : win a Golden Ticket with Google Cloud: All-Access Pass to NVIDIA GTC Berlin 2026..

The Google Cloud and NVIDIA teams are excited to announce an opportunity for you to win the ultimate developer experience! We are sending one lucky member from our developer community to NVIDIA GTC Berlin 2026 in Berlin, Germany (Oct 20-22). This is a unique opportunity for our developer community, and we hope you will participate in the contest! Be sure to read all the details below to learn how to enter your submission before the deadline on September 10, 2026.

The "Golden Ticket" winner will receive a premier experience:

✈️ Travel & Pass: One complimentary NVIDIA GTC Berlin Conference Pass to attend in person, including a round-trip travel to Berlin and accommodations. Winners must be able to travel to this event in person to accept the prize.

💻 NVIDIA merchandise gift bag.

⭐ VIP Access: VIP seating for NVIDIA CEO Jensen Huang’s keynote on October 21, 2026.

🧠 Access to NVIDIA community special events.

See the official website.