Python and robotic process automation (RPA) together have the potential to revolutionize intelligent automation fundamentally.
While RPA software bots may help many different businesses, between 30-50% of RPA deployment projects fail.
One challenge with RPA is creating bots using drag-and-drop user interfaces (UIs) or programming languages like Visual Basic, which have become less common over time.
Python remains popular due to its diverse libraries and powerful integration features with other applications; developers use this language to write bots using its RPA technologies by utilizing Python libraries. This article details its benefits, use cases, and definition.
What Is Python?
Python is an open-source programming language designed for creating flexible and versatile automation projects. Use cases include: Web Scraping, Extraction and Browser Automation, System Admin, DevOps Services, Financial Analysis, and Beyond.
Python has quickly become one of the premier web programming languages, becoming the number one programming language since.
Python boasts an abundance of libraries, inbuilt tools, and modules specifically tailored for automating specific automation tasks; for instance, the Pandas library can automate data cleaning while the PyAutoGUI library automates GUI tasks.
What Is Robotic Process Automation (RPA)?
RPA stands for robotic process automation and utilizes software robots to perform digital activities typically undertaken by human workers.
RPA gives you software technology - known as 'bots' - which you can program yourself to perform business processes efficiently and reliably.
Automation bots ('bots') provide an effective means for handling low-value, repetitive jobs more cost-effectively and more quickly while freeing your staff members up for higher-value operations.
According to research, up to 44.55% of employee time could be freed through current automation technology solutions.
Robotic Process Automation allows you to build individual software bots to help automate complex processes. They replicate actions by performing step-by-step instructions; RPA bots interact with all systems and applications just like humans would, but unlike them, they work faster with greater accuracy than human beings can.
What Is Python RPA (Robotic Process Automation)?
Automating repetitive, time-consuming business tasks using Python software robots provides organizations with the capability of eliminating manual labor tasks like data entry, form filling, image file moves and report generation while saving costs and increasing operational efficiencies.
Python has quickly become the language of choice for RPA due to its ease, versatility, and wide array of libraries and frameworks that enable it to automate complex workflows easily.
Python RPA often involves libraries like PyAutoGUI, which is capable of simulating user input while interacting with GUIs; another such library would be BeautifulSoup, which automates web page scraping and data extraction processes.
What Are The Use Cases Of Python RPA?
Python can be an ideal candidate for automating business processes using RPA bots, with its simple code and open-source libraries making it suitable for creating advanced intelligent apps.
Common use cases of python RPA method are:
Establish RPA Automation Processes
Users of Python packages can utilize their packages to automate repetitive, time-consuming tasks. Python scripts may be utilized for web page maintenance tasks, as well as developing customized bots from scratch for scraping a website or manipulating elements within files.
Meanwhile, data visualization libraries like Matplotlib and Seaborn enable users to present large amounts of data visually through charts and graphs.
Expansion Of RPA Use Cases
Some robotic process automation (RPA) tools offer APIs that enable developers to integrate their Python code with RPA software, enabling a bot to quickly automate complex, repetitive tasks like querying databases or accessing APIs quickly and reliably.
RPA Analytics
Python can facilitate RPA process analysis and visualization for improved project management. Python scripts may also help track human error metrics or generate reports regarding RPA process efficiency.
Machine Learning
Python's machine learning libraries, such as Scikit-Learn and TensorFlow, provide tools for training bots to complete more complicated tasks, including image recognition or natural language processing.
What Are The Benefits Of Python RPA?
Here are some benefits of Python RPA:
Easy To Learn And Utilize
The Python programming language is known for its straightforward syntax and readability, making it accessible for developers of all skill levels to develop RPA bots quickly, thus shortening deployment times.
Wide Variety Of Libraries And Modules
Python provides developers with access to a vast collection of libraries and modules which make developing robotic process automation bots (RPA bots) much simpler, including libraries specifically tailored for web scraping, data processing and machine learning.
Programmers using these libraries quickly automate repetitive or time-consuming tasks via these libraries' set of tools and functionalities that put automating on autopilot for developers.
Cross-Platform Compatibility
Python is an accessible programming language designed for use on platforms like Windows, macOS, and Linux. We must not forget the potential downside to writing applications with Python; its code might work fine on one platform and not another, potentially disintegrating.
Scalable
Python is an extremely scalable programming language that makes an excellent option for businesses that wish to automate both simple and complex tasks; its programming language offers flexible solutions as businesses' automation requirements evolve.
Businesses using this method of automation will find scaling easy as their requirements change over time.
Coordination Between Technologies
Python's versatility enables it to integrate smoothly with various technologies and applications, enabling developers to easily develop automated workflows or tools tailored specifically for business requirements.
Open-Source And Cost-Effective Technology Solutions
Python is an open-source programming language, meaning each Python package can be freely edited, distributed, and used.
As such, it makes an ideal solution for businesses attempting to reduce RPA development costs without incurring expensive custom solutions from scratch. In addition, its vast library of open-source libraries and modules enables organizations to leverage existing solutions without starting from scratch.
Active Community
Python boasts a vibrant community of developers who make significant contributions to its development and evolution, giving rise to an abundance of tutorials, forums and resources available for them to solve RPA solutions quickly and effectively.
A global Python developer community works tirelessly on new tools and libraries designed to automate processes. Should any issues or needs arise with automation efforts, you should easily be able to find support online as needed.
Robustness
Python is an exceptionally capable programming language capable of managing large datasets and intricate business processes with relative ease - this makes it the go-to option for businesses requiring maximum flexibility and scalability from their RPA solution.
Reasons Why Python RPA May Be Beneficial In Your Automation
No Lock-In
Python automations are written entirely in code. Any editor or platform of your choosing can be used to develop bots and run automation wherever desired.
Sharing of these processes among team members can then take place as desired, with many available tools and frameworks for you to utilize within projects being an added option as well.
Cost
With low-code platforms' licensing models and usage fees escalating quickly as automation efforts expand, license management becomes an ongoing burden that erodes ROI on projects.
Python RPA's pure code architecture means no license fees or usage restrictions apply - making building and deploying your automations without incurring extra expenses, making more projects with an attractive ROI possible.
Scalability And Performance
Python RPA outshines low-code platforms by being more scalable, supported by integration with tools and technologies, and performing faster (3x-20x).
With it, you can build complex automation (web, desktop, legacy Android apps) and manage large volumes of data storage without using elastic computing (VMs, containers, or serverless), which scale as capacity demands change.
Skill Development
Python training can be very cost-effective, and learning it becomes even more affordable when there are 14 million developers around the globe, as well as numerous free courses offering valuable techniques that could be applied across other projects (Data Science, DevOps, etc.).
By understanding programming concepts better through Python learning, you will become a more efficient developer capable of meeting an array of client demands more easily.
Flexibility
Low-code RPA platforms may be user-friendly for nontechnical users. Yet, they are quite limited when it comes to customization and requirements.
By contrast, Python gives access to over 440,000 packages and tools making possible highly sophisticated automation across web, desktop, mobile, and legacy systems.
Read More: Revolutionizing Automation: Streamlining Processes with Python
What Kinds Of Robotic Process Automation Exist?
Robotic process automation (RPA) falls into three main categories: attended, unattended and hybrid RPA.
Attended Automation
This variety of RPA lives on a user's device and usually activates only upon their request or command. Ideal applications of Attended Automation would include automating situations involving sensitive information, trigger processes, or audit trails, an excellent solution for customer-facing workers or sensitive tasks such as fraud or AML checks.
Unattended Automation
This RPA type works independently by following rules-based processes for completion. It is ideal for reducing labor loads associated with back-office employees.
Processes like invoice or account processing fall within this category.
Hybrid RPA
This form of robotic process automation combines attended and unattended bots for end-to-end automation. It is ideal for automating activities across front-office work and back-office operations and scaling automation up/down.
RPA In Operation
Build
The initial step to creating RPA bots is installing them and programming their process instructions. Building RPA bots should be user-friendly but may occasionally require technical expertise.
However, many platforms provide no-code or low-code solutions that allow 'drag and drop' automation. Building bots is done either by recording the process itself or designing it through definition documents.
Operating
Operation depends on whether your automation solution requires attended, unattended, or hybrid handling. When operating RPA solutions, a user typically triggers bots to begin and stop working as required by their task or function; on occasion, they might require further input, such as login details, to do their tasks correctly.
Unattended RPA can function autonomously without human oversight. It uses trigger events to inform bots when to begin and stop working on tasks.
The bots run quietly in the background on either a server or a virtual machine.
Orchestrate
It offers you the ability to manage and administer RPA bots efficiently and effectively, such as turning different bots on/off, grouping them into groups, prescribing workflows for them, etc.
Orchestration of RPA can be critical when deployed across an expansive enterprise environment, as you must likely operate bots on hundreds or even thousands of devices to automate numerous different tasks at any one time.
Are RPA Software Systems A Form Of Cognitive Technology Or AI?
RPA does not utilize cognitive technology or artificial intelligence; rather, it provides the foundation of intelligent process automation and cognitive automation technologies.
Although RPA and cognitive automation differ substantially in function and purpose, many similarities remain the same; RPA uses structured digital data, while cognitive automation converts unstructured inputs to structured formats, which RPA uses later to complete processes.
Artificial Intelligence (AI) is often misconstrued to refer to any technology using software or bots to carry out tasks traditionally carried out by humans.
However, RPA should not be confused as part of AI, as RPA's approach relies upon logic-driven input. At the same time, AI uses unstructured input and develops its own set of rules to complete its work.
RPA and AI have increasingly become common components of intelligent automation platforms, providing organizations with greater benefits from RPA deployments.
Although RPA itself does not fall under the cognitive technology umbrella, these two technologies work very well when combined as part of intelligent process automation platforms for organizations looking to reap maximum returns from RPA use.
RPA Developers Can Use Python Libraries
Let us delve deeper into these Python development libraries for RPA developers.
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PyAutoGUI: It is an automated GUI library written for Python.
It makes automating GUI interactions such as clicking buttons, typing text into boxes or moving the mouse much simpler.
Especially helpful for automating repetitive tasks involving GUI interactions.
- Openpyxl: It is an Excel automation library used for reading and writing spreadsheets in RPA projects. Openpyxl allows for reading/writing spreadsheet files directly within an RPA project using its powerful Python library interface, making spreadsheet management simpler for project teams.
- Pywinauto: It can automate Windows applications, providing users with control and interaction over GUI elements in Windows applications.
- Selenium: It is the popular web automation library that can be used for automating browsers. You can write scripts that interact with web pages, fill forms out correctly and perform other tasks that involve browsers - making Selenium an essential tool for RPA developers automating web tasks.
- Pytesseract: It can help with optical character recognition (OCR), allowing users to extract text from images and PDF documents with OCR technology. This feature can come in handy when extracting information from invoices, purchase order docs or similar sources.
- PyPDF2: PyPDF2 is a library designed for working with PDF files, offering users tools for merging or splitting PDFs as well as extracting text or images from them automatically.
- OpenCV: It, or an open-source computer vision library, can be utilized in robotic process automation (RPA) environments for image and video processing tasks like recognition, object detection and comparison. OpenCV offers powerful automation of tasks which include images or video data processing.
- Numpy: It is the numerical computing library written for Python and features functions for working with arrays and matrices - making it perfect for data processing tasks in RPA like analysis, manipulation and visualization.
- Pandas For Python: It is an invaluable data analysis library with features geared specifically toward working with data frames - perfect for data manipulation and analysis tasks such as cleaning, transformation and visualization in RPA environments.
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Conclusion
Python RPA offers businesses seeking efficient process automation a compelling solution. Combining Python's accessibility and flexibility with RPA robots' automation power makes this an attractive proposition that organizations looking to streamline operations should seriously consider deploying.
Our Python development services provide user-friendly environments which facilitate script integration alongside RPA bots so developers can automate processes more effortlessly.
