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TestComplete VS Matplotlib

Compare TestComplete VS Matplotlib and see what are their differences

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Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

TestComplete logo TestComplete

TestComplete Desktop, Web, and Mobile helps you create repeatable and accurate automated tests across multiple devices, platforms, and environments easily and quickly.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • TestComplete Landing page
    Landing page //
    2023-09-20
  • Matplotlib Landing page
    Landing page //
    2023-06-14

TestComplete features and specs

  • Ease of Use
    TestComplete has a user-friendly interface that allows both technical and non-technical users to create automated tests with ease.
  • Scriptless Testing
    The tool supports keyword-driven testing, enabling users to create automated tests without any scripting knowledge.
  • Multi-Technology Support
    TestComplete supports testing for a wide range of technologies, including desktop, web, and mobile applications, making it a versatile tool.
  • Integration Capabilities
    It easily integrates with other SmartBear tools and third-party tools like JIRA, Jenkins, and Azure DevOps, facilitating a smooth CI/CD process.
  • Parallel Test Execution
    TestComplete allows for parallel test executions, which can significantly reduce the total testing time and speed up the development cycle.
  • Object Recognition
    The tool includes advanced object recognition methods that ensure automated tests are stable and resilient to changes in the application's UI.
  • Comprehensive Reporting
    TestComplete provides detailed test reports and logs, helping teams quickly diagnose and address any issues that arise during testing.

Possible disadvantages of TestComplete

  • Cost
    TestComplete is relatively expensive compared to other automated testing tools, which can be a significant investment for small and medium-sized businesses.
  • Resource Intensive
    The tool can be resource-intensive, requiring significant system resources for smooth operation, which might affect performance on less powerful machines.
  • Learning Curve
    Despite its user-friendly interface, there can be a steep learning curve for users who want to utilize its more advanced features.
  • Limited Community Support
    Compared to some other popular testing tools, TestComplete has a smaller user community, which can make it challenging to find solutions to uncommon issues.
  • Complex Licensing Model
    The licensing model can be complex, potentially confusing for new users who need to understand different types of licenses and their limitations.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of TestComplete

Overall verdict

  • Overall, TestComplete is considered a robust and comprehensive tool for automated testing. Its user-friendly interface and powerful testing capabilities make it a worthwhile investment for many organizations aiming to improve their software testing processes.

Why this product is good

  • TestComplete is a popular automation tool for UI testing, known for its ease of use, broad range of supported applications, and testing capabilities. It supports multiple scripting languages, such as JavaScript, Python, and VBScript, allowing testers with varying coding skills to utilize it effectively. Its record-and-playback feature makes creating tests straightforward, and its extensive integration options with other tools enhance its functionality and flexibility. Additionally, TestComplete automates functional, regression, and performance testing, which contributes to higher-quality software releases.

Recommended for

    TestComplete is recommended for organizations seeking a reliable UI testing tool that supports both desktop, mobile, and web applications. It is especially beneficial for testers who appreciate the flexibility of choosing from multiple scripting languages or those who prefer a record-and-playback approach. It suits both small teams looking for straightforward solutions and larger enterprises that require more advanced integration and automation capabilities.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

TestComplete videos

+ Add

TestComplete: The Easiest-to-Use Automated UI Testing Tool

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to TestComplete and Matplotlib)

TestComplete

Matplotlib

Automated Testing
100 100%
Automated Testing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Website Testing
100 100%
Website Testing
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare TestComplete and Matplotlib

TestComplete Reviews

Best Automation Testing Tools (Free and Paid) | July 2022
TestComplete is a commercial testing tool and it allows you to create reusable tests for all web applications including modern JavaScript frameworks like React and Angular on 2050+ browser and platform configurations.
Source: www.softwaretestingmaterial.com
Top 10 Best Selenium Alternatives You Should Try
TestComplete is an influential and tough automated tool for testing mobile, desktop and web applications. It can be integrated with open source tools like Selenium, Jenkins etc. TestComplete supports few name mapping functions and GUI features that are not available with Selenium.
Source: www.softwaretestinghelp.com
Top 6 Complete Automation Testing Solutions
TestComplete is an automation testing tool developed by SmartBear and used for web, mobile and desktop applications. The main feature of this tool is the object recognition engine that can detect dynamic elements from a UI.
Source: dzone.com
Top 20 Best Automation Testing Tools in 2019 (Comprehensive List)
TestComplete is the top automation testing tool for desktop, mobile and web applications. With TestComplete, you can build and run functional UI tests via robust record & replay capabilities or by scripting in your favorite languages, including Python, JavaScript, VBScript and more.
Source: www.softwaretestinghelp.com
Top 20 Best Automation Testing Tools in 2018 (Comprehensive List)
TestComplete is the top automation testing tool for desktop, mobile and web applications. With TestComplete, you can build and run functional UI tests via robust record & replay capabilities or by scripting in your favorite languages, including Python, JavaScript, VBScript and more.
Source: www.softwaretestinghelp.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than TestComplete. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of TestComplete. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

TestComplete mentions (2)

  • How to create step recording program like testcomplete?
    I've been working with Selenium and Python for the past two years and I can say I've good enough experience with them about now. One thing that has always bothered me is how much manual work I have to do in order to implement the steps I need my program to make. So I've been thinking of making my own "step recorder", something in the vein of TestComplete. I've been using PyAutoGui too and the thought of crossing... Source: over 3 years ago
  • Looking for OS automation software
    SmartBear TestComplete and Ranorex both offer 30-day free trials to try them out. Their suites make it easy to automate desktop apps, but licensing is expensive. Part of what you pay for is being able to write "codeless" tests by recording your mouse and keyboard activity and validating whatever you want on the app. Source: over 4 years ago

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing TestComplete and Matplotlib, you can also consider the following products

Sauce Labs - Test mobile or web apps instantly across 700+ browser/OS/device platform combinations - without infrastructure setup.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Ranorex Studio - Accelerate testing with Ranorex Studio, the all-in-one tool for test automation. For desktop, web, or mobile app testing, with easy codeless automation tools, a full IDE, robust object recognition, flexible reporting and built-in Selenium WebDriver.

NumPy - NumPy is the fundamental package for scientific computing with Python

soapUI - SoapUI Pro is one of the most prominent API testing platforms around, allowing developers to quickly prototype the functions of their apps and get them to market with little hassle.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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