Book Image

Python for Secret Agents - Volume II - Second Edition

By : Steven F. Lott, Steven F. Lott
Book Image

Python for Secret Agents - Volume II - Second Edition

By: Steven F. Lott, Steven F. Lott

Overview of this book

Python is easy to learn and extensible programming language that allows any manner of secret agent to work with a variety of data. Agents from beginners to seasoned veterans will benefit from Python's simplicity and sophistication. The standard library provides numerous packages that move beyond simple beginner missions. The Python ecosystem of related packages and libraries supports deep information processing. This book will guide you through the process of upgrading your Python-based toolset for intelligence gathering, analysis, and communication. You'll explore the ways Python is used to analyze web logs to discover the trails of activities that can be found in web and database servers. We'll also look at how we can use Python to discover details of the social network by looking at the data available from social networking websites. Finally, you'll see how to extract history from PDF files, which opens up new sources of data, and you’ll learn about the ways you can gather data using an Arduino-based sensor device.
Table of Contents (12 chapters)
Python for Secret Agents Volume II
About the Author
About the Reviewer

What are they posting?

To gather images being posted, we'll modify our query that retrieves tweets. We'll get the media URL from the tweet, use urllib.request to get the image file, and use Pillow to confirm that it's a valid image and create a thumbnail of the image. While there are a lot of steps, each of them is something we've already seen.

We'll break this function into two parts: the Twitter part and the image processing part. Here's the first part, making the essential Twitter request:

import urllib.request
import urllib.parse
from PIL import Image
import io
def tweet_images_by_screen_name(screen_name):
    api = TwitterAPI(consumer_key,
    response= api.request( 'statuses/user_timeline',
                              {'screen_name':screen_name, 'count':30} )
    for item in response.json():
        text= item['text']
        entities= item['entities']
        if 'media' in entities: