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Postman VS Pandas

Compare Postman VS Pandas and see what are their differences

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Postman logo Postman

The Collaboration Platform for API Development

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Postman Landing page
    Landing page //
    2021-07-23
  • Pandas Landing page
    Landing page //
    2023-05-12

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.

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

Postman videos

+ Add

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

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Category Popularity

0-100% (relative to Postman and Pandas)

Postman

Pandas

API Tools
100 100%
API Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
APIs
100 100%
APIs
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Pandas

Postman Reviews

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...
Source: www.hypertest.co
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.
Source: www.blazemeter.com
Beeceptor vs Postman
You cannot download request log. Although, you can use Postman APIs to query and retrieve.
Source: beeceptor.com
Top 15 MuleSoft Competitors and Alternatives
Postman is an API platform with the world’s largest public API hub that helps developers design, build, test, and iterate APIs. In 2022, Postman served over 20 million developers and 500,000 organizations.
Source: bstrategyhub.com

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Social recommendations and mentions

Based on our record, Pandas should be more popular than Postman. It has been mentiond 219 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)

  • Best API Mocking Platforms in 2024
    Postman (postman.com) is a comprehensive API platform that goes beyond mocking, offering a full suite for API development, testing, and monitoring. With its mock server feature, Postman enables teams to simulate responses for various endpoints, making it a popular choice for end-to-end API management. - Source: dev.to / 6 months ago
  • 10 Best API Mocking Tools (2024 Review)
    Postman is a widely used tool for API testing and interaction. Its "Mock Servers" feature lets you create a mock version of your API, returning specific responses for testing. While useful, Postman may lack advanced mock server management features compared to other tools. - Source: dev.to / 7 months ago
  • The 3 Best Tools for API Design for Software Architects
    Postman is a widely adopted tool for API design and development, offering an intuitive interface for creating, testing, and documenting APIs. It simplifies the API design process, allowing architects to quickly prototype and refine their designs. - Source: dev.to / 10 months ago
  • How to use ApyHub to Build a Serverless Function in NodeJs?
    Once deployed, thoroughly test your serverless function to confirm it behaves as expected. Invoke the function manually from the cloud platform’s console or use tools like Postman, Apidog, or Fusion ( Fusion is ApyHub’s own API Client ) to test HTTP-triggered functions. Ensure the function executes correctly and handles errors gracefully. - Source: dev.to / about 1 year ago
  • Mastering Microservices: A Hands-On Tutorial with Node.js, RabbitMQ, Nginx, and Docker
    To test the API endpoints, you can use Postman. Download and install Postman from Postman's official website. - Source: dev.to / over 1 year ago
View more

Pandas mentions (219)

  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 22 days ago
  • How to import sample data into a Python notebook on watsonx.ai and other questions…
    # Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 1 month ago
  • How I Hacked Uber’s Hidden API to Download 4379 Rides
    As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 1 month ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • Sample Super Store Analysis Using Python & Pandas
    This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
View more

What are some alternatives?

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

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

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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

OpenCV - OpenCV is the world's biggest computer vision library

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