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The intersection of robotic process automation (RPA) and Python can revolutionize the intelligent automation landscape. RPA are software bots for automating time-consuming and repetitive tasks. Their programming flexibility makes them useful across a wide range of industries. However, after implementation, between 30-50% of RPA projects fail. One reason could be a lack of compatibility and poor integration with existing applications.
To solve that challenge, adopters could use no-code RPA tools that have in-built connectivity plugins and can easily be deployed. Another option is using a python RPA tool that leverages python programming language. In this article, we will explain how developers can take advantage of Python packages and frameworks to create adaptable RPA applications.
What is Python?
Python is an open-source programming language for creating a flexible and versatile automation project. Python automation use cases include:
These have made Python a darling amongst web developers, making it the #1 programming language from 2021 onwards (Figure 1).
Python has a wide range of libraries, in-built tools, and modules for different automation tasks. For example, the Pandas library can be used to automate data cleaning and data wrangling tasks, while the PyAutoGUI library can be used for GUI automation.
What is Python RPA?
Python RPA (Robotic Process Automation) is the use of Python programming language to create software robots that can automate repetitive, time-consuming tasks in business processes. RPA allows organizations to automate tasks that are typically performed by human workers, such as data entry, form filling, and report generation.
Python is a popular language for RPA because of its simplicity, flexibility, and wide range of libraries and frameworks that make it easy to automate complex workflows. Python RPA typically involves the use of libraries, such as PyAutoGUI, allowing Python to simulate user input and interact with graphical user interfaces (GUIs). Another example could be BeautifulSoup, which is used for automated web scraping and data extraction.
What are the use cases of using Python and robotic process automation?
Python can be used to create RPA bots to automate business processes. Python’s simple code and open source libraries make it a strong candidate for creating advanced intelligent applications. Specifically, use cases of Python and RPA include:
1. Creating RPA automation processes
Users can use Python packages to automate repetitive, time consuming tasks. For example, Python scripts can be used for creating customized bots from scratch for scraping a web page or manipulating elements in a file. Alternatively, Python’s data visualization libraries, such as Matplotlib and Seaborn, enable users to present large amounts of data in the form of charts and graphs.
2. Expanding RPA use cases
Some robotic process automation tools provide APIs that allow developers to access and integrate their Python code with the RPA software. This enables the bot to interact with external desktop applications to quickly automate complex, repeated tasks, such as querying a database, and accessing an API.
3. RPA analytics
Python can be used for data analysis and visualization in RPA processes for better project management. For example, Python scripts can be used to analyze both performance metrics or generate reports on RPA process efficiency.
4. Machine learning
Python’s machine learning libraries, such as Scikit-Learn and TensorFlow, can be used to train bots to perform more complex tasks, such as image recognition or natural language processing.
Sponsored:
Argos Labs’ no-code RPA allows users to create, run, and manage software robots from a control room. The major differentiator of Argos Labs is their POT SDK toolset that leverages python’s code formatting to build customized workflows, receive analytics reports, and build a plug-in for artificial intelligence/machine learning engines. Other benefits of using Argos Labs’ RPA include:
- Fully customizable low-code platform to meet customers’ needs
- Affordable license schemes for different business needs
- Programmable by entry level engineers and citizen developers who don’t have extensive coding expertise
What are the benefits of using Python RPA?
1. Easy to Learn and Use
The Python script is known for its simple syntax and readability, making it easy to learn and use for developers of all skill levels. With Python, developers can quickly develop and test RPA bots, reducing the deployment time.
2. Wide Range of Libraries and Modules
Python has a vast collection of libraries and modules that can be used to develop RPA bots, including libraries specifically for web scraping, data processing, and machine learning. These libraries provide a set of tools and functionalities that put programmers on the fast track for automating that make it easy for developers to automate repetitive and time-consuming tasks.
3. Cross-Platform Compatibility
Python is a cross-platform programming language. This makes it usable on different OS systems, such as Windows, macOS, and Linux. In extension, this makes it easy for businesses to define, deploy, and install RPA robots on various platforms.
However, note that the same applications written in Python might work well on one platform, but not in another. So there’s always the possibility of disintegration.
4. Scalable
Python is a scalable programming language that can be used to develop RPA bots of different sizes and complexities. This makes it an excellent choice for businesses looking to automate simple and complex tasks, as they can easily scale their automation efforts as their needs change.
5. Integration with Other Technologies
Python is compatible with many other technologies, making it easy to integrate with existing systems and applications. This integration enables developers to create customized automation workflows that meet specific business needs.
6. Open-Source and Cost-Effective
Python is an open-source programming language, meaning each python package is free to use, edit, and distribute. This makes it an excellent choice for businesses looking to cut costs while developing RPA solutions. Additionally, the vast collection of open-source Python libraries and modules means that businesses can leverage existing solutions without having to develop their own from scratch.
7. Active Community
Python has a large and active community of developers who constantly contribute to the language’s growth and development. This means that there is a vast pool of resources, tutorials, and forums available to developers, making it easier for them to solve problems and develop RPA solutions quickly and efficiently.
8. Robustness
Python is a robust language that can handle a high volume of datasets and complex business processes. This is especially important for businesses that demand much needed flexibility and scalability from their RPA package.
For more on RPA
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