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scraping.py
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scraping.py
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# Import dependencies
from splinter import Browser
from bs4 import BeautifulSoup as soup
from webdriver_manager.chrome import ChromeDriverManager
import pandas as pd
import datetime as dt
def scrape_all():
# Initiate headless driver for deployment
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('chrome',**executable_path,headless=True)
news_title, news_paragraph = mars_news(browser)
hemispheres = hemisphere_data(browser)
# Run all scraping functions and store results in dictionary
data = {"news_title": news_title,
"news_paragraph": news_paragraph,
"featured_image": featured_image(browser),
"facts": mars_facts(),
"hemispheres": hemispheres,
"last_modified": dt.datetime.now()}
# Stop webdriver and return data
browser.quit()
return data
def mars_news(browser):
# Visit the mars nasa news site
url = 'https://data-class-mars.s3.amazonaws.com/Mars/index.html'
browser.visit(url)
# Optional delay for loading the page
browser.is_element_present_by_css('div.list_text',wait_time=1)
# Convert browser text to a soup object
html = browser.html
news_soup = soup(html,'html.parser')
# Add try/except for error handling
try:
slide_elem = news_soup.select_one('div.list_text')
# Use the parent element to find the first 'a' tag and save it as 'news_title'
news_title = slide_elem.find('div',class_='content_title').get_text()
# Use the parent element to find the paragraph text
news_p = slide_elem.find('div',class_='article_teaser_body').get_text()
except AttributeError:
return None, None
return news_title, news_p
def featured_image(browser):
# Visit URL
url = 'https://data-class-jpl-space.s3.amazonaws.com/JPL_Space/index.html'
browser.visit(url)
# Find and click the full image button
full_image_elem = browser.find_by_tag('button')[1]
full_image_elem.click()
# Parse the resulting html with soup
html = browser.html
img_soup = soup(html,'html.parser')
# Add try/except for error handling
try:
# Find the relative image url
img_url_rel = img_soup.find('img',class_='fancybox-image').get('src')
except AttributeError:
return None
# Use the base URL to create an absolute URL
img_url = f'https://data-class-jpl-space.s3.amazonaws.com/JPL_Space/{img_url_rel}'
return img_url
def mars_facts():
# Add try/except for error handling
try:
# Use read_html to scrape the facts table into a dataframe
df = pd.read_html('http://data-class-mars-facts.s3.amazonaws.com/Mars_Facts/index.html')[0]
except BaseException:
return None
# Assign columns and set the index of the dataframe
df.columns=['Description','Mars','Earth']
df.set_index('Description',inplace=True)
# Convert dataframe into HTML format and return
return df.to_html(classes="table table-striped")
def hemisphere_data(browser):
# 1. Use browser to visit the URL
url = 'https://marshemispheres.com/'
browser.visit(url)
html = browser.html
bs = soup(html,'html.parser')
# 2. Create a list to hold the images and titles.
hemisphere_image_urls = []
# 3. Write code to retrieve the image urls and titles for each hemisphere.
# in for loop we should use range(len(bs.find('div',class_='item'))) instead of range(4)
# but could not fix error
for i in range(4):
# Create empty dictionary to store urls and titles for full images
hemispheres = {}
# click on hemisphere link
browser.links.find_by_partial_text('Enhanced')[i].click()
# navigate to full-resolution image page
html = browser.html
bs = soup(html,'html.parser')
rel_img_path = bs.find('ul').find('li').find('a')['href']
title = bs.find('div',class_='cover').find('h2').text
# retrieve the full resolution image URL string and title
hemispheres['img_url'] = url + rel_img_path
hemispheres['title'] = title
#navigate back to beginning to get the next hemisphere image
browser.back()
hemisphere_image_urls.append(hemispheres)
# 4. Print the list that holds the dictionary of each image url and title.
return hemisphere_image_urls
if __name__ == "__main__":
# If running as script, print scraped data
print(scrape_all())