def wrap(*args, **kwargs):
if args:
raise PositionalArgumentsNotSupported()
data = urlencode(kwargs)
if PY3:
data = bytes(data, 'utf-8')
req = Req(url, data=data)
try:
res = urlopen(req).read().decode()
except HTTPError as e:
raise SmappiServerError('%s (for "%s")' % (e, url))
except URLError as e:
raise SmappiServerError('%s for %s' % (e.args[0], url))
if self._fmt == 'json':
res = json.loads(res)
if isinstance(res, dict) and 'error' in res:
error = res['error']
if isinstance(error, dict):
message = error.pop('message', '')
if 'code' in error:
message += ' (code: %s)' % error['code']
raise SmappiAPIError(message, **error)
else:
raise SmappiAPIError(error)
return res
def getMostBoughtData():
my_url = 'https://finance.yahoo.com/u/yahoo-finance/watchlists/most-bought-by-hedge-funds/'
# saves the information from the url into the client
Client = Req(my_url)
# saves
page_hmtl = Client.read()
Client.close()
# parses the html of the website
page_soup = soup(page_hmtl, "html.parser")
# finds all the parts of the webpage that would hold the titles
symbols = page_soup.findAll("h2", {"class": "Fz(m)"})
tickers = page_soup.findAll("a", {"class": "Fw(b)"})
prices_html = page_soup.findAll(
"td", {"class": "data-col2 Ta(end) Pstart(10px) Pend(6px) Fw(b)"})
changes_html = page_soup.findAll(
"td", {"class": "data-col4 Ta(end) Pstart(10px) Pend(6px)"})
volumes_html = page_soup.findAll(
"td", {"class": "data-col6 Ta(end) Pstart(10px) Pend(6px)"})
avg_volumes_html = page_soup.findAll(
"td", {"class": "data-col7 Ta(end) Pstart(10px) Pend(6px)"})
sym = int(symbols[1].text[0:2])
x = 0
data = []
while x < 48 - 1:
if len(tickers[x].text
) > 5 or tickers[x].text == "Tech" or tickers[x].text == "News":
x = x + 1
else:
break
y = x
while x < y + sym:
ticker = tickers[x].text
price = prices_html[x - (y + sym)].text
change_str = changes_html[x - (y + sym)].text
if change_str.startswith('+'):
change = change_str[1:]
else:
change = change_str
volume = volumes_html[x - (y + sym)].text
avg_volume = avg_volumes_html[x - (y + sym)].text
data.append((ticker, price, change, volume, avg_volume))
x = x + 1
return data
def get_insider_trading_data():
my_url = 'http://openinsider.com/screener?s=&o=&pl=&ph=&ll=&lh=&fd=730&fdr=&td=0&tdr=&fdlyl=&fdlyh=&daysago=&xp=1&vl=&vh=&ocl=&och=&sic1=-1&sicl=100&sich=9999&grp=0&nfl=&nfh=&nil=&nih=&nol=&noh=&v2l=&v2h=&oc2l=&oc2h=&sortcol=0&cnt=1000&page=1'
Client = Req(my_url)
page_html = Client.read()
Client.close()
page_soup = soup(page_html, "html.parser")
# finds the ticker locations using this method
findsT = page_soup.findAll("a",{"onmouseout":"UnTip()"})
# finds the title of the person that was insider trading
findsTi = page_soup.findAll("td")
# finds the title of the person trading on the inside
findsNum = page_soup.findAll("td",{"align":"right"})
x = 0 # variable for the title
y = 22 # finds the price of the stock when bought
z = 23 # finds the quantity of stocks purchased
w = 24 # finds the number of stocks already owned
a = 72 # finds the title of the person insider trading
data = []
while x < 1000:
findT = findsT[x]
findT = findT["href"].replace("/", "")
findP = findsNum[y].text
findQ = findsNum[z].text
findO = findsNum[w].text
findTi = findsTi[a].text
data.append((findT, findTi, findP, findQ, findO))
x += 1
y += 12
z += 12
w += 12
a += 17
return data
import bs4
from urllib.request import urlopen as Req
from bs4 import BeautifulSoup as soup
my_url = 'https://www.newegg.com/Video-Cards-Video-Devices/Category/ID-38?Tpk=graphics%20card'
uclient = Req(my_url)
page_html = uclient.read()
uclient.close()
page_soup = soup(page_html, "html.parser")
containers = page_soup.findAll("div", {"class": "item-container"})
filename = "products_newegg.csv"
f = open(filename, "w")
headers = "Brand, Product_name\n"
f.write(headers)
for container in containers:
brand = container.div.div.a.img["title"]
title_container = container.findAll("a", {"class": "item-title"})
product_name = title_container[0].text
print("Brand: " + brand)
print("Product Name: " + product_name)
f.write(brand + "," + product_name.replace(",", "|") + "\n")
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as Req
url = "https://www.flipkart.com/search?q=iphone&otracker=search&otracker1=search&marketplace=FLIPKART&as-show=on&as=off"
Client = Req(url)
page_html = Client.read()
page_soup = soup(page_html, "html.parser")
# print(page_soup.contents)
containers = page_soup.findAll("div", {"class": "_3O0U0u"})
container = containers[0]
print(container.div.img['alt'])
price = container.findAll("div", {"class": "col col-5-12 _2o7WAb"})
print(price[0].text)
rating = container.findAll("div", {"class": "hGSR34"})
print(rating[0].text)
filename = "flpphn.csv"
f = open(filename, "w")
headers = "Products_Name,Pricing,Ratings\n"
Thrasher Magazine's website is parsed for infomation about the recent video
uploads. The code is activated with voice commands via an Amazon Echo, Dot,
or Spot."""
import os
from urllib.request import Request as Req
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
import html.parser as parser
from flask import Flask
from flask_ask import Ask, statement, question, session
app = Flask(__name__)
ask = Ask(app, "/")
my_url = Req("http://www.thrashermagazine.com/articles/videos/", headers={"User-Agent":"Mozilla/5.0"})
# open connection, grabbing the page
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
# html parsing
page_soup = soup(page_html, "html.parser")
descriptions = page_soup.findAll("div", {"class":"post-description"})
titles = page_soup.findAll("div", {"class":"post-thumb-container"})
img_url = "https://s3-us-west-1.amazonaws.com/thrasherskill/thrasher-logo.png"
def get_info():
for tit, des in zip(titles, descriptions):
titled = tit.a.img["alt"].strip()
title = parser.HTMLParser().unescape(titled)
description = des.text.strip()
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 14 17:47:10 2020
@author: akhil
"""
from urllib.request import urlopen as ureq
from urllib.request import Request as Req
from bs4 import BeautifulSoup as soup
from selenium import webdriver
import pandas as pd
from selenium.webdriver.common.by import By
url = 'https://www.lviglobal.com/course-schedule/'
req = Req(url, headers={'User-Agent': 'Chrome/80.0'})
x = ureq(req)
y = x.read()
x.close()
page_soup = soup(y, 'html.parser')
y
a = page_soup.findAll('div', {'class': 'event-desc'})
print(a[0].a['href'])
t = a[0].strings
for string in a[0].strings:
print(string)
course_names = []
for i in range(len(a)):
def GetUrl(url):
Uclient = Req(url)
page_html = Uclient.read()
Uclient.close()
page_soup = Soup(page_html, "html.parser")
return page_soup
from urllib.request import urlopen as Req
from bs4 import BeautifulSoup as soup
import csv
base = "http://www.achemenet.com/"
accumulator = []
# parsing for website name begins. Here we go!
for index in range(1, 11):
head, tail = "http://www.achemenet.com/fr/tree/?/sources-textuelles/textes-par-publication/Wunsch_CM_20/", "/24/0#set"
site = head + str(index) + tail
page_html = Req(site).read()
pg_soup = soup(page_html, "html.parser")
for product in pg_soup.find_all("div", class_="item"):
target = base + product.find("a").get('href')
accumulator.append(target)
#!/usr/bin/env python3 #import Python libraries regex, statistics, urllib.request and Beautiful Soup import locale import re from statistics import mean from urllib.request import urlopen as Req from bs4 import BeautifulSoup as soup # Declare my_url variable my_url = "https://www.carfax.com/Used-Honda-Civic-Type-R_t10063" # Load my_url contents into Scrapee variable Scrapee = Req(my_url) # Extract html to variable Scrapee_html Scrapee_html = Scrapee.read() # Close web page Scrapee.close() # Parse html into node tree and strip html tags, store as variable Scrapee_soup Scrapee_soup = soup(Scrapee_html, "html.parser") #Find matching class data and store into three variables