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Python RPA vs Turbotic comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Python RPA
Ranking in Robotic Process Automation (RPA)
14th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Turbotic
Ranking in Robotic Process Automation (RPA)
83rd
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2026, in the Robotic Process Automation (RPA) category, the mindshare of Python RPA is 1.1%, down from 1.8% compared to the previous year. The mindshare of Turbotic is 0.2%, up from 0.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Robotic Process Automation (RPA) Mindshare Distribution
ProductMindshare (%)
Python RPA1.1%
Turbotic0.2%
Other98.7%
Robotic Process Automation (RPA)
 

Featured Reviews

Natalia  Raffo - PeerSpot reviewer
Co - Founder & Chief Data Officer -CDO at Data360
Robust and good for data processing while being helpful for building data science use cases
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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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
12%
Construction Company
9%
Marketing Services Firm
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What do you like most about Python RPA?
Keyword-driven automation has been beneficial in streamlining operations.
What needs improvement with Python RPA?
I've worked with file detection for secure transactions. I use a machine learning model to predict events related to security transactions by predicting possible routes in advance. They need to imp...
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Comparisons

No data available
 

Overview

 

Sample Customers

Home Credit, Silimed, Hilton, Al Hilal Bank, Baskin and Robbins
1. Atlassian2. Baidu3. Cisco4. Dell Technologies5. Google6. IBM7. Intel8. JPMorgan Chase9. LinkedIn10. Microsoft11. Oracle12. SAP13. Salesforce14. ServiceNow15. Siemens16. Spotify17. Tesla18. Toyota19. Twitter20. Uber21. Visa22. Walmart23. WeWork24. World Bank25. Xiaomi26. Zoom27. Zynga
Find out what your peers are saying about UiPath, Automation Anywhere, Microsoft and others in Robotic Process Automation (RPA). Updated: March 2026.
886,174 professionals have used our research since 2012.