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Postman VS Matplotlib

Compare Postman VS Matplotlib and see what are their differences

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Postman logo Postman

The Collaboration Platform for API Development

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Postman Landing page
    Landing page //
    2021-07-23
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Postman features and specs

  • User-Friendly Interface
    Postman features an intuitive and user-friendly interface that simplifies the process of constructing API requests and visualizing responses. This makes it accessible for both beginners and advanced users.
  • Collaboration
    Postman offers robust collaboration features, such as shared workspaces, collections, and real-time editing, enabling teams to work together more efficiently on API development.
  • Comprehensive Testing Tools
    Postman provides a suite of testing tools to create, automate, and manage test cases. It supports automated testing through its scripting environments, which ensure APIs perform as expected.
  • Extensive API Documentation
    Postman can automatically generate comprehensive API documentation, making it easier to maintain and share API specifications with stakeholders and other developers.
  • Mock Servers
    Postman allows users to create mock servers to simulate API responses. This is particularly useful for testing and development purposes when the actual API is not yet available.
  • Integration Capabilities
    Postman offers integrations with various CI/CD tools, version control systems, and other services like Jenkins, GitHub, and Slack, facilitating seamless integration into development workflows.

Possible disadvantages of Postman

  • Resource Intensive
    Postman can sometimes be resource-intensive, consuming substantial memory and CPU, which can impact the performance of your system, especially when dealing with large collections.
  • Steep Learning Curve for Advanced Features
    While Postman is generally user-friendly, some of its advanced features, like scripting and automation, can have a steep learning curve and might require additional effort to master.
  • Pricing
    Although Postman offers a free tier, many of its advanced features, such as enhanced collaboration tools and extended integrations, are locked behind paid plans, which may not be cost-effective for smaller teams or individual developers.
  • Dependency on Internet
    Some of Postman's features, particularly those related to collaboration and synchronization, require a stable internet connection, which can be a limitation in environments with poor connectivity.
  • Limited Native Support for Certain Protocols
    Postman primarily focuses on HTTP/HTTPS protocols and may offer limited or no native support for other protocols, which can be restricting for developers working with diverse sets of technologies.

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 Postman

Overall verdict

  • Yes, Postman is widely regarded as a good tool for API development and testing. Its combination of powerful features and ease of use makes it a popular choice among developers.

Why this product is good

  • Postman is considered a top choice for API development due to its user-friendly interface, extensive features for testing, automation, and collaboration, and strong community support. It simplifies the process of creating, managing, and testing APIs, making it accessible for both beginners and experienced developers.

Recommended for

  • Developers working on API integration
  • QA engineers involved in testing APIs
  • Teams in need of collaborative API development
  • Developers looking to automate API testing
  • Individuals looking for a comprehensive API testing tool

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.

Postman videos

POST/CON 2018 workshop in review: Running Postman Collections

More videos:

  • Review - POST/CON 2018 workshop in review: Postman Collections
  • Tutorial - How to Share Postman Collections

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Postman and Matplotlib)
API Tools
100 100%
0% 0
Data Science And Machine Learning
APIs
100 100%
0% 0
Technical Computing
0 0%
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 Postman and Matplotlib

Postman Reviews

Postman vs Apidog: Choosing the Suitable API Development Tool
Forking Existing Collections: One of Postmanโ€™s unique strengths is the ability to fork collections created by others. Developers can easily duplicate publicly available Postman collections, modifying them to fit their particular needs without starting from scratch. This feature saves time and encourages collaboration by allowing developers to build upon existing work.
Source: dev.to
Top 20 Open Source & Cloud Free Postman Alternatives (2024 Updated)
As the digital landscape evolves, the significance of APIs (Application Programming Interfaces) has surged, facilitating seamless communication between various software applications. Postman has been a leading tool in this space, offering a comprehensive platform for API development, testing, and documentation. However, recent shifts in its pricing model and user experience...
Source: medium.com
Best Postman Alternatives To Consider in 2025
- Focus on specific needs: Does the tool excel at SOAP APIs or cater to microservices? - Resource usage: Does it handle complex projects without impacting system performance? - Script reusability: Does it allow for efficient code sharing across projects?3. Is Postman the best API tool?Not all-encompassing. While Postman is powerful, the "best" tool depends on your specific...
Postman Alternatives for API Testing and Monitoring
Some engineers turn to Postman for API testing and monitoring needs. However, Postman is a costly and limited solution. QA, DevOps and other engineers may find it lacks capabilities that can answer their needs. In this blog post, we provide 12 Postman alternatives built for the enterprise.
Beeceptor vs Postman
You cannot download request log. Although, you can use Postman APIs to query and retrieve.
Source: beeceptor.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.
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.
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.
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...

Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Postman. It has been mentiond 114 times since March 2021. 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.

Postman mentions (30)

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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
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What are some alternatives?

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

DreamFactory - DreamFactory is an API management platform used to generate, secure, document, and extend APIs.

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

MuleSoft Anypoint Platform - Anypoint Platform is a unified, highly productive, hybrid integration platform that creates an application network of apps, data and devices with API-led connectivity.

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

Insomnia REST - Design, debug, test, and mock APIs locally, on Git, or cloud. Build better APIs collaboratively for the most popular protocols with a devโ€‘friendly UI, built-in automation, and an extensible plugin ecosystem.

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