Python Projects with source code

BITCOIN MINING

==============

from hashlib import sha256
MAX NONCE 189000000006
def SHA256(text):
    return sha256(text.encode("ascit")).hexdigest()
def mine(block_number,transactions,previous_hash,prefix_zeros):
    prefix_str='0'*prefix zeros
    for nonce in range(MAX_NONCE):
        text=str(block_number)+transactions+previous_hash+str(nonce)
        new_hash SHA256(text)
        if new_hash.startswith(prefix_str):
            print(f"Yay!Successfully mined bitcoins with nonce value:{nonce}")
            return new hash
    raise BaseException(f"Couldn't find correct has after trying(MAX_NONCE}times")
if_name='__ main__':
    transactions ***
    Dhaval->Bhavin->20,
   Mando->Cara->45
    ***
    difficultyd try changing this to higher number and you will see it will take more time
for wining as difficulty increases
    import time
    start=time.time()
    print("start mtning")
    new hash-
mine(5,transactions,'0000000xa036944e29568d0cff17edbe838f81288fecf9a66be9a2b8321c6ec7",
difficulty)
    total time str((tine.time()-start))
    print(frend mining.Mining took:(total time)seconds")
    print(new_hash)

Car Detection

=================

#import Libraries of python OpenCV
import cv2
#capture frames fromavideo
cap=cv2.VideoCapture('video.avi')
#Trained XML classifiers describes same features of
#some object we want to detect
car_cascade=cv2.Cascade Classifier('cars.xml')
#Loop runs if capturing has been initialized.
while True:
   #reads frames fromavideo
   ret,frames=cap.read()
   #convert to gray scale of each frames.
   gray cv2.cvt Color(frames,cv2.COLOR_BGR2GRAY)
   #Detects cars of different sizes in the input mage
   cars car_cascade.detectMultiscale(gray,1.1,1)
   #To drawarectangle in each cars
   for(x,y,w,h)in cars:
   CV2.rectangle(frames,(x,y),(x+w,y+h),(0,0,255),2)
   #Display frames inawindow
   cv2.imshow('video2',frames)
   #Watt for Esc key to stop
   if cv2.waitkey(33)=27:
       break
#De-allocate any associated memory usage
cv2.destroyAllWindows()

Face Detection

==============

import cv2
 Load the Cascade
face_cascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml')
 To capture video from webcam
cap cv2.VideoCapture(0)
ato useavideo file as input
while True:
      Read the frame
     ,ing cap.read()
      Convert to grayscale
    gray cv2.cvtColor(ing,cv2.COLOR_BGR2GRAY)
    #Deteri the faces
    faces=face_cascade.detectMultiscale(gray,1.1,4)
    #Draw the rectangle around each face
    for(x,y,w,h)in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
    cv2.imshow("img',img)
    #Stup of escape key is pressed
    k=cv2.wattKey(30)&exff
    ifk== 27:
        break
 Release the VideoCapture object
cap.release()

Phone Number Detail

===================

import phonenumbers
from phonenumbers import timezone,geocoder,carrier
phoneNumber=phonenumbers.parse("[phone]")
timezone=timezone.time_zones_for_number(phoneNumber)
Carrier=carrier.name_for_number(phoneNumber,'en')
Region=
print(phoneNumber)
print(timeZone)
print(Carrier)
print(Region)
         geocoder.description_for_number(phoneNumber,'en')