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Mastering Python for Networking and Security

You're reading from   Mastering Python for Networking and Security Leverage the scripts and libraries of Python version 3.7 and beyond to overcome networking and security issues

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781839217166
Length 538 pages
Edition 2nd Edition
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Author (1):
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José Manuel Ortega José Manuel Ortega
Author Profile Icon José Manuel Ortega
José Manuel Ortega
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Table of Contents (22) Chapters Close

Preface 1. Section 1: The Python Environment and System Programming Tools
2. Chapter 1: Working with Python Scripting FREE CHAPTER 3. Chapter 2: System Programming Packages 4. Section 2: Network Scripting and Extracting Information from the Tor Network with Python
5. Chapter 3: Socket Programming 6. Chapter 4: HTTP Programming 7. Chapter 5: Connecting to the Tor Network and Discovering Hidden Services 8. Section 3: Server Scripting and Port Scanning with Python
9. Chapter 6: Gathering Information from Servers 10. Chapter 7: Interacting with FTP, SFTP, and SSH Servers 11. Chapter 8: Working with Nmap Scanner 12. Section 4: Server Vulnerabilities and Security in Python Modules
13. Chapter 9: Interacting with Vulnerability Scanners 14. Chapter 10: Identifying Server Vulnerabilities in Web Applications 15. Chapter 11: Security and Vulnerabilities in Python Modules 16. Section 5: Python Forensics
17. Chapter 12: Python Tools for Forensics Analysis 18. Chapter 13: Extracting Geolocation and Metadata from Documents, Images, and Browsers 19. Chapter 14: Cryptography and Steganography 20. Assessments 21. Other Books You May Enjoy

Development environments for Python scripting

In this section, we will review PyCharm and Python IDLE as development environments for Python scripting.

Setting up a development environment

In order to rapidly develop and debug Python applications, it is absolutely necessary to use an Integrated Development Environment (IDE). If you want to try different options, we recommend you check out the list that is on the official site of Python, where you can see the tools according to your operating systems and needs:

https://wiki.python.org/moin/IntegratedDevelopmentEnvironments

Between all the environments, the following two are what we will look at:

PyCharm

PyCharm is an IDE developed by Jetbrains, based on the company’s IntelliJ IDEA, the same company’s IDE, but focused on Java, and is the Android Studio base.

PyCharm is multi-platform and we can find binaries for operating systems running Windows, Linux, and macOS X. There are two versions of PyCharm – community and technical, with variations in functionality relating to web framework integration and support for databases. In the following URL, we can see a comparison between both editions:

http://www.jetbrains.com/pycharm

The main advantages of this development environment are as follows:

  • Autocomplete, syntax highlighter, analysis tool, and refactoring
  • Integration with web frameworks such as Django and Flask
  • An advanced debugger
  • Connection with version-control systems, such as Git, CVS, and SVN

In the following screenshot, we can see how to configure virtualenv in PyCharm:

Figure 1.1 – Configuring virtualenv in PyCharm

Figure 1.1 – Configuring virtualenv in PyCharm

In the preceding screenshot, we are setting the configuration related to establishing a new environment for the project using virtualenv.

Debugging with PyCharm

In this example, we are debugging a Python script that accepts two input parameters. An interesting topic is the possibility of adding a breakpoint to our script.

In the following screenshot, we are setting a breakpoint in the view_parameters method:

Figure 1.2 – Setting a breakpoint in PyCharm

Figure 1.2 – Setting a breakpoint in PyCharm

With the View Breakpoint option, we can see the breakpoint established in the script:

Figure 1.3 – Viewing breakpoints in PyCharm

Figure 1.3 – Viewing breakpoints in PyCharm

In the following screenshot, we can visualize the values of the parameters that contain the values we are debugging:

Figure 1.4 – Debugging variables in PyCharm

Figure 1.4 – Debugging variables in PyCharm

In this way, we can know the state of each of the variables at runtime, as well as modify their values to change the logic of our script.

Debugging with Python IDLE

Python IDLE is the default IDE that comes installed by default when you install Python in your operating system. When executing Python IDLE, it offers the possibility to debug your script and see errors and exceptions in the Python shell console:

Figure 1.5 – Running a script in the Python shell

Figure 1.5 – Running a script in the Python shell

In the preceding screenshot, we can see the output in the Python shell and the exception is related to File not found.

You have been reading a chapter from
Mastering Python for Networking and Security - Second Edition
Published in: Jan 2021
Publisher: Packt
ISBN-13: 9781839217166
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