Python RPA Reviews

Name: Python RPA
Brand: Python RPA
Rating: 4.2 (3 reviews)

4.2 out of 5

3 reviews
100% willing to recommend

What is Python RPA?

Users employ Python RPA for automating repetitive tasks and streamlining workflows, reducing manual errors, and enhancing efficiency in processing data, web scraping, and application integration.

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Python RPA is the #18 ranked solution in best RPA tools. PeerSpot users give Python RPA an average rating of 8.4 out of 10. Python RPA is most commonly compared to UiPath: Python RPA vs UiPath. Python RPA is popular among the large enterprise segment, accounting for 62% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 14% of all views.

Buyer's Guide

Robotic Process Automation (RPA)

April 2025

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Helped 845,960 peers since 2012

Featured Python RPA reviews

Arno Krause

Solutions Architect at MTN

Keyword-driven automation has been beneficial in streamlining operations. The error handling capability of Python RPA is fairly good in managing exceptions. I rate it a seven out of ten. We've integrated it with Jenkins and with our release pipeline. It was fairly easy. We had no issues with integration that we couldn’t deal with. The dashboard is simple. We export it to Excel or Power BI and make it look pretty. For our initial use, the dashboard is okay.

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Natalia Raffo

Co - Founder & Chief Data Officer -CDO at Data360

The processing of data is good. We can use many different types of data, including images and videos. We can use different libraries to do better preprocessing of different types of data. We can do different models in recommendation systems for things like videos and sales strategy. We can do language processing or sentiment analysis to predict things for our clients. We can design and develop machine learning applications that can predict events. We can use these on libraries to solve complex problems when we have a lot of data. It's possible to use the solution with other tools. It's very agile. In the financial advisory and portfolio management space, several budget management applications are now available in the market. These have machine learning based functionality. In Python, I use different machine learning algorithms to enable customers to keep track of their expenses and provide recommendations on better savings. These are machine learning algorithms that customize financial portfolios by looking at income rate tolerance and preferences, et cetera.

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Mutheeswari Bose

Full-Stack Python Developer at Optisol

To transfer some data from front end to back end application. I'll see if I want to read the data from database, and I will collect collect from front end. So for that purpose, I have used it It is easy to import the packages. And, yeah, instead of writing multiple lines of code, we can do it in…

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Python RPA mindshare

As of April 2025, the mindshare of Python RPA in the Robotic Process Automation (RPA) category stands at 1.8%, up from 0.1% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Robotic Process Automation (RPA)

Key learnings from peers

Valuable Features

Python RPA offers strong automation capabilities, flexibility, and ease of integration. Users appreciate its ability to handle complex workflows, compatibility with various systems and tools, and the extensive library of pre-built modules. Its open-source nature allows for customization, while the active community support ensures continuous improvement and readily available resources. The intuitive design facilitates quick learning and efficiency in automating repetitive tasks.

"It's possible to use the solution with other tools. It's very agile."
"Keyword-driven automation has been beneficial in streamlining operations."
"Instead of writing multiple lines of code, we can do it in a single statement."

Room for Improvement

Python RPA experiences slow execution times and lacks comprehensive documentation. Users find it challenging due to limited integrations with other systems. Bugs in the scripts and an absence of real-time support contribute to frustration. Additionally, the learning curve is steep for beginners.

"It can be expensive to deploy a lot of models in the cloud, especially if there are large amounts of data."
"Support could be improved."
"When we call an API and there is an error, it doesn't tell you what the error is."

ROI

Python RPA significantly improved process efficiency, reducing manual effort by automating repetitive tasks. Users reported cost savings and faster turnaround times. Several noted a decrease in human error, enhancing the accuracy of their operations. A few highlighted an increase in productivity and better resource management. The integration with existing systems was seamless, and scalability allowed for broader application across various departments.

Pricing

Python RPA offers flexible pricing tailored to enterprise needs. Official pricing information remains undisclosed, but users highlight competitive rates, especially for larger implementations. Users report strong ROI and cost savings, with additional costs for customization and support. Licensing is typically annual, with scalable options based on bot usage and features.

"The tool is not expensive."
"I am using an open-source solution."

Popular Use Cases

Python RPA is primarily used for automating repetitive tasks and data processing. Users appreciate its ability to streamline workflows, enhance productivity, and minimize human error. It is noted for its easy integration with existing systems and flexibility in handling various automation scenarios. Python RPA is valued for its scripting capabilities and effective performance in office automation, including report generation and email management.

Service and Support

Customers note Python RPA's support team responds quickly and efficiently. They praise the team's helpfulness and expertise in resolving issues. Users mention that the customer service provides clear instructions and practical solutions. Python RPA receives high marks for being approachable and understanding user requirements. Feedback indicates that they make problem-solving easier and users appreciate the knowledgeable and friendly interactions. Some mention the guidance and follow-up from the support team as particularly valuable.

Deployment

Users find Python RPA's initial setup straightforward and manageable, appreciating its clear documentation and ease of integration. Some mention that while there is a learning curve, support resources are helpful. They feel that Python RPA's setup process is smooth and quick, enabling them to start automating tasks efficiently. Users express satisfaction with the minimal complexity involved in setting up Python RPA.

Scalability

Python RPA demonstrates excellent scalability, efficiently handling increasing loads and complex tasks. Users appreciate its ability to integrate seamlessly with existing systems and adjust to diverse business processes. Feedback highlights its flexibility and robustness, enabling large-scale automation projects while maintaining performance. It's praised for its adaptability in evolving environments and ease of scaling operations without compromising on speed or reliability. Users find it highly effective for extensive automation needs.

Stability

Python RPA offers robust stability, supporting complex automation tasks with high reliability. Users find it consistently performs well, even under heavy workloads. Though some notice occasional issues, regular updates enhance its performance. Technical support promptly addresses any complications, ensuring minimal downtime. Users appreciate its dependability for both small and large-scale operations. Python RPA effectively maintains consistent performance, making it a trusted choice for automation.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Robotic Process Automation (RPA) Buyer's Guide for additional reliable information.

Top industries

By visitors reading reviews

Manufacturing Company

14%

Financial Services Firm

14%

Computer Software Company

Government

Educational Organization

Marketing Services Firm

Comms Service Provider

Energy/Utilities Company

Healthcare Company

Media Company

Non Profit

Construction Company

Wholesaler/Distributor

Outsourcing Company

Transportation Company

Insurance Company

Logistics Company

Hospitality Company

Recruiting/Hr Firm

Security Firm

Sports Company

Think Tank

Recreational Facilities/Services Company

Engineering Company

University

Performing Arts

Pharma/Biotech Company

Real Estate/Law Firm

Compare Python RPA with alternative products

Learn more about Python RPA

Python RPA is valued for its ability to handle complex automation processes, its flexibility, and its compatibility with different systems. It is particularly beneficial for large-scale data handling and business process automation. Users find the extensive library and strong community support helpful for swift issue resolution and knowledge sharing. Its intuitive design and clear documentation simplify the learning curve and implementation. However, documentation can lack depth, making troubleshooting challenging. The setup process can be cumbersome, requiring more intuitive guidance. Execution speed can be slow, causing inefficiencies in workflows, and there is a need for better support and resources for developers. Some users report difficulties with integration into existing systems, suggesting enhanced compatibility and flexibility are needed.

What are the key features?

Flexibility: Capable of handling a wide range of automation tasks.
Ease of Integration: Seamlessly integrates with different systems.
High Customization: Allows for tailored automation solutions.
Extensive Library: Provides comprehensive tools and resources.
Community Support: Strong user community for knowledge sharing.
Scalability: Efficient for various business process scales.
Intuitive Design: Simplifies learning and implementation.

What are the benefits and ROI?

Increased Efficiency: Reduces time spent on repetitive tasks.
Error Reduction: Minimizes manual errors.
Cost Savings: Decreases operational costs through automation.
Improved Accuracy: Enhances precision in data processing.
Scalable Solutions: Adapts to growing business needs.
Faster Processes: Streamlines workflows for quicker results.

In industries where large-scale data processing is essential, such as finance or healthcare, Python RPA helps automate data entry, validation, and reporting, significantly reducing manual labor and improving accuracy. In retail, it integrates with e-commerce platforms to automate order processing and inventory management, ensuring smooth operations. Other sectors, like logistics, benefit from Python RPA by streamlining dispatch and tracking processes, enhancing operational efficiency and customer satisfaction.