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I have the following function using selenium that works - but I am unable to pass it on. I get the error: InvalidSchema: No connection adapters were found for 'data:image/jpeg;base64,/9j (full image link below - it works when I stick in a browser tab) when it gets to the response.get() portion of the code.

Is there a way to bypass opening and saving the image? I just want to be able to upload the full picture of Barry O to Twitter without saving to my local machine. Or do I have to download, save, and re-upload for my "push to Twitter" function? Am I missing a decoding here? Or mis-using the request.get()? If I don't have to use requests, that's fine by me!

import requests
import base64
from selenium import webdriver
from selenium.webdriver.common.keys import Keys

# test image for scrape
testing = "Barack Obama"

# Function to scrape picture ----
def pic_scrape(plain_name):

    # selenium setup
    driver = webdriver.Chrome(executable_path = r"/Users/username/Documents/chromedriver")
    driver.get('https://www.google.com/imghp?hl=en&authuser=0&ogbl')
    search_box = driver.find_element_by_xpath("//input[@name='q']")

    # search test term ('testing' variable above)
    search_box.send_keys(str(plain_name), Keys.ENTER)

    # finds elements - all works
    elements = driver.find_element_by_class_name('rg_i')
    elements.click()
    element = driver.find_element_by_class_name('v4dQwb')
    celeb_pic = element.find_element_by_class_name('n3VNCb')
    pic_url = celeb_pic.get_attribute("src")
    driver.close()

    # where the code fails
    response = requests.get(pic_url)
    print(response)

    return response

# Main function ----
if __name__ == '__main__':
    pic_scrape(testing)

Full error for requests.get() with image coding (image url works, if put in browser search):

InvalidSchema: No connection adapters were found for 'data:image/jpeg;base64,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'
papelr
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1 Answers1

0

The response is not a URL its a base64 encode for MIME data:image/jpeg, so you cannot use it for request.get().

import base64
imgdata = base64.b64decode(src.split(",")[1])
filename = 'some_image.jpg'  # I assume you have a way of picking unique filenames
with open(filename, 'wb') as f:
    f.write(imgdata)

if you want to save the image you could use something like the above code

PDHide
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  • Is there a way I can just pass it on, without saving? I just want to scrape and then upload directly to Twitter. Rather not save it – papelr Mar 31 '21 at 02:09
  • Img data will have the data you want , try returning imgdata – PDHide Mar 31 '21 at 02:16
  • Was able to return the `imgdata` into my push function - but question - would that return the actual picture, or will I have to convert it to an actual image for upload? – papelr Mar 31 '21 at 13:19
  • it depends on what is your endpoint expects – PDHide Mar 31 '21 at 13:24
  • Guessing, from this post: https://stackoverflow.com/questions/31748444/how-to-update-twitter-status-with-image-using-image-url-in-tweepy - that I *must* download the file and then remove it. Sad, but oh well – papelr Mar 31 '21 at 16:34