
# Import Splinter, BeautifulSoup, and Pandas
from splinter import Browser
from bs4 import BeautifulSoup as soup
import pandas as pd
from webdriver_manager.chrome import ChromeDriverManager
import time


# Set the executable path and initialize Splinter
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('chrome', **executable_path, headless=False)


# Visit the mars nasa news site
url = 'https://redplanetscience.com/'
browser.visit(url)

# Optional delay for loading the page
browser.is_element_present_by_css('div.list_text', wait_time=1)


# Convert the browser html to a soup object and then quit the browser
html = browser.html
news_soup = soup(html, 'html.parser')

slide_elem = news_soup.select_one('div.list_text')

slide_elem.find('div', class_='content_title')


# 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()
news_title

# Use the parent element to find the paragraph text
news_p = slide_elem.find('div', class_='article_teaser_body').get_text()
news_p


# JPL Space Images Featured Image

# Visit URL
url = 'https://spaceimages-mars.com'
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')
img_soup


# find the relative image url
img_url_rel = img_soup.find('img', class_='fancybox-image').get('src')
img_url_rel

# Use the base url to create an absolute url
img_url = f'https://spaceimages-mars.com/{img_url_rel}'
img_url


# Mars Facts

df = pd.read_html('https://galaxyfacts-mars.com')[0]
df.head()

df.columns=['Description', 'Mars', 'Earth']
df.set_index('Description', inplace=True)
df

df.to_html()

# D1: Scrape High-Resolution Mars’ Hemisphere Images and Titles

# 1. Use browser to visit the URL 
url = 'https://marshemispheres.com/'

browser.visit(url)


# 2. Create a list to hold the images and titles.
hemisphere_image_urls = []

for i in range(4):
    print(i)
    browser.find_by_tag('h3')[i].click()
    time.sleep(3)
    
    #parse with soup
    html = browser.html
    hem_soup = soup(html, 'html.parser')
    
    #Find the image
    img_link = hem_soup.find('div', class_= "downloads")
    
    img_div = (img_link.find('a').get('href'))
    print(img_div)
    
    time.sleep(3)
    
    hemisphere_title = hem_soup.select_one('h2.title').text
    print(hemisphere_title)
    
    #add to a dictionary the img and the title
    hemisphere_dict = {
        "img": f'{url}{img_div}',
        "title": hemisphere_title
      }
    
    hemisphere_image_urls.append(hemisphere_dict)
    browser.back()

# 4. Print the list that holds the dictionary of each image url and title.
hemisphere_image_urls


# 5. Quit the browser
browser.quit()





