import speedtest

def check_internet_speed():
    print("testing internet speed...")
    st = speedtest.Speedtest()

    st.get_best_server()
    
    download_speed = st.download() / 1_000_000
    
    upload_speed = st.upload() / 1_000_000
    
    ping = st.results.ping

    print(f"Download speed: {download_speed:.2f} Mbps")
    print(f"Upload Speed: {upload_speed:.2f} Mbps")
    print(f"Ping: {ping:.2f} ms")

if __name__ == "__main__":
    check_internet_speed()

speedtest kutubxonasi - bu internet tezligini tekshirish uchun ishlatiladi

O'RNATISH:

pip install speedtest-cli

#speedtest #speedtestlibrary

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def home():
    return {"xabar": "Hello world"}

FastAPI - bu kutubxona kuchli va tez ishlaydigan API lar yasash uchun ishlatidadi va siz FastAPI yordamidan API dan tashqari web saytlar yasash ham mumkin

O'RNATISH:

pip install fastapi

#fastapi

Flask - bu uncha katta va murakkal bo'lmagan web saytlar yasash uchun mo'ljallangan

O'RNATISH:

pip install flask

#flask

Pytubefix - bu pytube kutubxonasining tuzatilgan variyanti bo'lib bu kutubxonada hozircha hech qanday muammolar yo'q

O'RNATISH:

pip install pytubefix

#pytube #pytubefix #python #python3

Instagram sahifamga ham obuna bo'lib qo'ying uyerda python dasturlash tilidagi kutubxonalarni qanday ishlatishni ko'rsatib boraman

Pythonda rasmning orqa fonini o'chirish

O'RNATISH

pip install rembg
pip install onnxruntime

#python #rembg

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Pythonda rasm ichiga xabar joylash

O'RNATISH

pip install pillow stepic

import cv2
import mediapipe as mp 
import numpy as np
import screen_brightness_control as sbc

mp_hands = mp.solutions.hands
mp_drawing = mp.solutions.drawing_utils

cap = cv2.VideoCapture(0)

with mp_hands.Hands(min_detection_confidence=0.7, min_tracking_confidence=0.7) as hands:
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        
        frame = cv2.flip(frame, 1)
        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = hands.process(rgb_frame)
        
        if results.multi_hand_landmarks:
            for hand_landmarks in results.multi_hand_landmarks:
                mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
                
                index_tip = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
                thumb_tip = hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP]
                
                h, w, _ = frame.shape
                ix, iy = int(index_tip.x * w), int(index_tip.y * h)
                tx, ty = int(thumb_tip.x * w), int(thumb_tip.y * h)
                
                distance = np.sqrt((ix - tx)**2 + (iy - ty)**2)

                brightness = int(np.interp(distance, [20, 200], [0, 100]))
                sbc.set_brightness(brightness)

                cv2.putText(frame, f'Yorug\'lik: {brightness}%', (10, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
                cv2.line(frame, (ix, iy), (tx, ty), (0, 255, 0), 2)
                cv2.circle(frame, (ix, iy), 10, (0, 255, 0), cv2.FILLED)
                cv2.circle(frame, (tx, ty), 10, (0, 255, 0), cv2.FILLED)

        cv2.imshow('Yoruglikni barmoqlar bilan boshqarish', frame)
        
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

Pythonda opencv-python kutubxonasi yordamida kompyuter ekran yorug'ligini boshqarish

O'RNATISH

pip install opencv-python

import cv2
import numpy as np
from PIL import Image

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    lower_blue = np.array([100, 150, 50])
    upper_blue = np.array([130, 255, 255])

    lower_green = np.array([40, 70, 70])
    upper_green = np.array([80, 255, 255])

    mask_blue = cv2.inRange(hsv, lower_blue, upper_blue)
    mask_green = cv2.inRange(hsv, lower_green, upper_green)

    kernel = np.ones((5, 5), np.uint8)
    mask_blue = cv2.erode(mask_blue, kernel, iterations=1)
    mask_blue = cv2.dilate(mask_blue, kernel, iterations=2)

    mask_green = cv2.erode(mask_green, kernel, iterations=1)
    mask_green = cv2.dilate(mask_green, kernel, iterations=2)

    bbox_blue = Image.fromarray(mask_blue).getbbox()
    bbox_green = Image.fromarray(mask_green).getbbox()

    # Draw rectangles
    if bbox_blue:
        x1, y1, x2, y2 = bbox_blue
        frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 0), 2)

    if bbox_green:
        x1, y1, x2, y2 = bbox_green
        frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)

    cv2.imshow("Color Detection (Blue & Green)", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Python yordamida ko'k va yashil rangli obyektlarni aniqlovchi dastur

O'RNATISH

pip install opencv-python

@BackendDevs_uz - backend yo’nalishiga oid yangi kanal ochildi. Bu kanalda nafaqat python bali C++ java va shunga o’xshash boshqa backend yo’nalishidagi dasturlash tillar bo’yicha quizlar va foydali malumotlar qo’yiladi.

O’tib obuna bo’lib qo’yilar

from aiogram import Bot, Dispatcher, types
from aiogram.types import Message
from aiogram.filters import Command
import asyncio
import os

BOT_TOKEN = "bot_token"

dp = Dispatcher()

@dp.message(Command(commands=["start"]))
async def start(message: Message):
    await message.answer("👋 Hello! I am an Echo Bot. Send me any message and I will repeat it!")

@dp.message()
async def echo(message: Message):
    await message.answer(message.text)

async def main():
    try:
        bot = Bot(token=BOT_TOKEN)
        await dp.start_polling(bot)
    finally:
        await bot.session.close()

if __name__ == "__main__":
    asyncio.run(main())

Pythonda telegram bot yasash

O’RNATISH

pip install aiogram

import instaloader

def InstagramDownloader(shortcode: str):
    L = instaloader.Instaloader()
    post = instaloader.Post.from_shortcode(L.context, shortcode)
    return {'title': post.title, "caption": post.caption, "rasm": post.url, "video": post.video_url, "turi": post.typename}

# https://www.instagram.com/reel/DNehZkaR6LI/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA== # shortcode (id): DNehZkaR6LI
print(InstagramDownloader("DNehZkaR6LI")) 

Pythonda Instagramdan video va rasmlar yuklash

O'RNATISH

pip install instaloader

Instagram Sahifamga ham obuna bo'lamiz. U yerda harxil qisqa video darsliklarga o'xshash videolar chiqariladi

from langchain_huggingface import HuggingFaceEmbeddings
from langchain.vectorstores import FAISS
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.chains.conversational_retrieval.base import ConversationalRetrievalChain
from langchain.memory import ConversationBufferMemory
from langchain_google_genai import ChatGoogleGenerativeAI
import os

os.environ["HUGGINGFACEHUB_API_TOKEN"] = "HUGGINGFACE_API_TOKEN"
os.environ["GOOGLE_API_KEY"] = "GOOGLE_API_KEY"

loader = PyPDFLoader("fayl.pdf")
documents = loader.load()

splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
docs = splitter.split_documents(documents)

embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")

vectorstore = FAISS.from_documents(docs, embeddings)

llm = ChatGoogleGenerativeAI(model="gemini-2.5-pro", temperature=0.3)

memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)

qa = ConversationalRetrievalChain.from_llm(
    llm=llm,
    retriever=vectorstore.as_retriever(),
    memory=memory
)

print("📚 PDF Chatbot ready! Type 'exit' to quit.\n")
while True:
    query = input("You: ")
    if query.lower() in ["exit", "quit"]:
        break
    result = qa({"question": query})
    print("Bot:", result["answer"])

Savollaringizga Javob beruvchi ChatBot

Bu Chatbot siz ulagan PDF faylingiz asosida siz so'ragan savollaringizga javob beradi va suhbad davomida u oldingiz aytganlaringizni eslab qoladi. Bu Gemini-2.5-pro Model asosida ishlaydi. Siz o'zingiz xohalganingizdek Gemini-2.5-pro ni o'rniga Gemini-1.5-pro, Gemini-2.5-flash Gemini-1.5-flash modellarini ishlatishingiz mumkin

O'RNATISH

pip install -r requirements.txt

requirements.txt fayli shu postning izohida

Ishga tushirganingizga xatolik chiqarib oxirida yana qaysidir kutubxonalarni o'rnatish kerak ekanligini ko'rsatadi. Ularni ham o'rnating (o'zim ham aytsam bo'ladi lekin esimga kemaydi qaysilar ekanligi)

Gemini API Keyni olish:
Ro'yxatdan o'tmagan bo'lsangiz ro'yxatdan o'ting
shu websaytga kiring
"Create API Key" tugmasiga bosing
API Keyingizni xohalgan nomingizni bering va "Create Key" ni bosing

Huggingfacedan API Tokenni olish:
Ro'yxatdan o'tmagan bo'lsangiz ro'yxatdan o'ting
shuyerga kiring
"Crete new token"ga bosing
Tokeningizga nom bering
O'zingizga kerakli ruxsatlarni bering va pastga tushib "Create token"ni bosing

Xoxishga qarab ChatGPT yoki Claudeni ulasa ham bo'ladi. Lekin tekin variant qilib Gemini ulavordim

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