你用 Python 写过哪些牛逼的程序/脚本？

# Thanking everyone who wished me on my birthday
import requests
import json

# Aman's post time
AFTER = 1353233754
TOKEN = '  '

def get_posts():
    """Returns dictionary of id, first names of people who posted on my wall
    between start and end time"""
    query = ("SELECT post_id, actor_id, message FROM stream WHERE "
            "filter_key = 'others' AND source_id = me() AND "
            "created_time > 1353233754 LIMIT 200")
    payload = {'q': query, 'access_token': TOKEN}
    r = requests.get('https://graph.facebook.com/fql', params=payload)
    result = json.loads(r.text)
    return result['data']

def commentall(wallposts):
    """Comments thank you on all posts"""
    #TODO convert to batch request later
    for wallpost in wallposts:
        r = requests.get('https://graph.facebook.com/%s' %
                wallpost['actor_id'])
        url = 'https://graph.facebook.com/%s/comments' % wallpost['post_id']
        user = json.loads(r.text)
        message = 'Thanks %s :)' % user['first_name']
        payload = {'access_token': TOKEN, 'message': message}
        s = requests.post(url, data=payload)
        print "Wall post %s done" % wallpost['post_id']

if __name__ == '__main__':
    commentall(get_posts())

import cv2
import sys
import os,random,string
#choices=['Add a name']
import os
current_directory=os.path.dirname(os.path.abspath(__file__))
from Tkinter import Tk
from easygui import *
import numpy as np

x= os.listdir(current_directory)
new_x=[]
testing=[]
for i in x:
if i.find('.')==-1:
new_x+=[i]
else:
testing+=[i]
x=new_x
g=x
choices=['Add a name']+x
y= range(1,len(x)+1)
def get_images_and_labels():
global current_directory,x,y,g
if x==[]:
return (False,False)
image_paths=[]
for i in g:
path=current_directory+''+i
for filename in os.listdir(path):
final_path=path+''+filename
image_paths+=[final_path]
# images will contains face images
images = []
# labels will contains the label that is assigned to the image
labels = []
for image_path in image_paths:
# Read the image and convert to grayscale
img = cv2.imread(image_path,0)
# Convert the image format into numpy array
image = np.array(img, 'uint8')
# Get the label of the image
backslash=image_path.rindex('')
underscore=image_path.index('_',backslash)
nbr = image_path[backslash+1:underscore]
t=g.index(nbr)
nbr=y[t]
# If face is detected, append the face to images and the label to labels
images.append(image)
labels.append(nbr)
#cv2.imshow("Adding faces to traning set...", image)
#cv2.waitKey(50)
# return the images list and labels list
return images, labels
# Perform the tranining
def train_recognizer():
recognizer = cv2.createLBPHFaceRecognizer()
images, labels = get_images_and_labels()
if images==False:
return False
cv2.destroyAllWindows()
recognizer.train(images, np.array(labels))
return recognizer
def get_name(image_path,recognizer):
global x,choices
#if recognizer=='':
# recognizer=train_recognizer()
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
#recognizer=train_recognizer()
x1=testing
global g
print image_path
image = cv2.imread(image_path)
img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
predict_image = np.array(img, 'uint8')
faces = faceCascade.detectMultiScale(
img,
scaleFactor=1.3,
minNeighbors=5,
minSize=(30, 30),
flags = http://cv2.cv.CV_HAAR_SCALE_IMAGE
)
for (x, y, w, h) in faces:
f= image[y:y+w,x:x+h]
cv2.imwrite('temp.jpg',f)
im='temp.jpg'
nbr_predicted, conf = recognizer.predict(predict_image[y: y + h, x: x + w])
predicted_name=g[nbr_predicted-1]
print "{} is Correctly Recognized with confidence {}".format(predicted_name, conf)
if conf>=140:
continue
msg='Is this '+predicted_name
reply = buttonbox(msg, image=im, choices=['Yes','No'])
if reply=='Yes':
reply=predicted_name
directory=current_directory+''+reply
if not os.path.exists(directory):
os.makedirs(directory)
random_name=''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(7))
path=directory+''+random_name+'.jpg'
cv2.imwrite(path,f)
else:
msg = "Who is this?"
reply = buttonbox(msg, image=im, choices=choices)
if reply == 'Add a name':
name=enterbox(msg='Enter the name', title='Training', strip=True)
print name
choices+=[name]
reply=name
directory=current_directory+''+reply
if not os.path.exists(directory):
os.makedirs(directory)
random_name=''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(7))
path=directory+''+random_name+'.jpg'
print path
cv2.imwrite(path,f)


# calculate window position
root = Tk()
pos = int(root.winfo_screenwidth() * 0.5), int(root.winfo_screenheight() * 0.2)
root.withdraw()
WindowPosition = "+%d+%d" % pos


# patch rootWindowPosition
rootWindowPosition = WindowPosition
def detect_faces(img):
global choices,current_directory
imagePath = img
faceCascade = cv2.CascadeClassifier(cascPath)
image = cv2.imread(imagePath)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.3,
minNeighbors=5,
minSize=(30, 30),
flags = http://cv2.cv.CV_HAAR_SCALE_IMAGE
)


print "Found {0} faces!".format(len(faces))
m=0
for (x, y, w, h) in faces:
m+=1
padding=0
f= image[y-padding:y+w+padding,x-padding:x+h+padding]
cv2.imwrite('temp.jpg',f)
im='temp.jpg'
msg = "Who is this?"
reply = buttonbox(msg, image=im, choices=choices)
if reply == 'Add a name':
name=enterbox(msg='Enter the name', title='Training', strip=True)
print name
choices+=[name]
reply=name
directory=current_directory+''+reply
if not os.path.exists(directory):
os.makedirs(directory)
random_name=''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(7))
path=directory+''+random_name+'.jpg'
print path
cv2.imwrite(path,f)
def new(img,recognizer):
imagePath = current_directory+''+img
print imagePath
get_name(imagePath,recognizer)
cascPath = 'haarcascade_frontalface_default.xml'
b=0
os.system("change_name.py")
for filename in os.listdir("."):
b+=1
if b%10==0 or b==1:
os.system("change_name.py")
recognizer=train_recognizer()
if filename.endswith('.jpg') or filename.endswith('.png'):
print filename
imagePath=filename
#detect_faces(imagePath)
new(imagePath,recognizer)
os.remove(filename)
raw_input('Done with this photograph')

import mechanize,os,urllib2,urllib,requests,getpass,time
start_time = time.time()
from bs4 import BeautifulSoup
br=mechanize.Browser()
br.open('https://nalanda.bits-pilani.ac.in/login/index.php')
br.select_form(nr=0)
    

name=''
while name=='':
    try:
        print '*******'
        username=raw_input('Enter Your Nalanda Username: ')
        password=getpass.getpass('Password: ')
        br.form['username']=username
        br.form['password']=password
        res=br.submit()
        response=res.read()
        soup=BeautifulSoup(response)
        name=str(soup.find('div',attrs={'class':'logininfo'}).a.string)[:-2]
    except:
        print 'Wrong Password'
f=open('details.txt','w')
f.write(username+'n'+password)
f.close()
print 'Welcome, '+name
print 'All the files will be downloaded in your Drive C in a folder named "nalanda"'
#print soup.prettify()
div=soup.find_all('div',attrs={'class':'box coursebox'})


l=len(div)
a=[]
for i in range(l):
    d=div[i]
    s=str(d.div.h2.a.string)
    s=s[:s.find('(')]
    c=(s,str(d.div.h2.a['href']))
    path='c:nalanda'+c[0]
    if not os.path.exists(path):
        os.makedirs(path)
    a+=[c]
#print a
overall=[]
for i in range(l):
    response=br.open(a[i][1])
    page=response.read()
    soup=BeautifulSoup(page)
    li=soup.find_all('li',attrs={'class':'section main clearfix'})
    x=len(li)
    t=[]
    folder=a[i][0]
    print 'Downloading '+folder+' files...'
    o=[]
    for j in range(x):
        g=li[j].ul
        #print g
        #raw_input('')
        if g!=None:
            temp=http://g.li['class'].split(' ')
            #raw_input('')
            if temp[1]=='resource':
                #print 'yes'
                #print '********************'
                o+=[j]
                h=li[j].find('div',attrs={'class':'content'})
                s=str(h.h3.string)
                path='c:nalanda'+folder
                if path[-1]==' ':
                    path=path[:-1]
                path+=''+s
                if not os.path.exists(path):
                    os.makedirs(path)
                f=g.find_all('li')
                r=len(f)
                z=[]
                for e in range(r):
                    p=f[e].div.div.a
                    q=f[e].find('span',attrs={'class':'resourcelinkdetails'}).contents
                    link=str(p['href'])
                    text=str(p.find('span').contents[0])
                    typ=''
                    if str(q[0]).find('word')!=-1:
                        typ='.docx'
                    elif str(q[0]).find('JPEG')!=-1:
                        typ='.jpg'
                    else:
                        typ='.pdf'
                    if typ!='.docx':
                        res=br.open(link)
                        soup=BeautifulSoup(res.read())
                        if typ=='.jpg':
                            di=soup.find('div',attrs={'class':'resourcecontent resourceimg'})
                            link=di.img['src']
                        else:
                            di=soup.find('div',attrs={'class':'resourcecontent resourcepdf'})
                            link=di.object['data']
                    try:
                        if not os.path.exists(path+''+text+typ):
                            br.retrieve(link,path+''+text+typ)[0]
                    except:
                        print 'Connectivity Issues'
                    z+=[(link,text,typ)]
                t+=[(s,z)]
    if t==[]:
        print 'No Documents in this subject'
    overall+=[o]
    #raw_input('Press any button to resume')
#print overall
print 'Time Taken to Download: '+str(time.time()-start_time)+ ' seconds'
print 'Do you think you can download all files faster than this :P'
print 'Closing in 10 seconds'
time.sleep(10)