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Google Cloud Natural Language API vs Postman: What are the differences?
Developers describe Google Cloud Natural Language API as "Derive insights from unstructured text using Google machine learning". You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage. On the other hand, Postman is detailed as "Only complete API development environment". Postman is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.
Google Cloud Natural Language API can be classified as a tool in the "NLP / Sentiment Analysis" category, while Postman is grouped under "API Tools".
From a StackShare Community member: "I just started working for a start-up and we are in desperate need of better documentation for our API. Currently our API docs is in a README.md file. We are evaluating Postman and Swagger UI. Since there are many options and I was wondering what other StackSharers would recommend?"
I use Postman because of the ease of team-management, using workspaces and teams, runner, collections, environment variables, test-scripts (post execution), variable management (pre and post execution), folders (inside collections, for better management of APIs), newman, easy-ci-integration (and probably a few more things that I am not able to recall right now).
I use Swagger UI because it's an easy tool for end-consumers to visualize and test our APIs. It focuses on that ! And it's directly embedded and delivered with the APIs. Postman's built-in tools aren't bad, but their main focus isn't the documentation and also, they are hosted outside the project.
I recommend Postman because it's easy to use with history option. Also, it has very great features like runner, collections, test scripts runners, defining environment variables and simple exporting and importing data.
Postman supports automation and organization in a way that Insomnia just doesn't. Admittedly, Insomnia makes it slightly easy to query the data that you get back (in a very MongoDB-esque query language) but Postman sets you up to develop the code that you would use in development/testing right in the editor.
Pros of Google Cloud Natural Language API
Pros of Postman
- Easy to use490
- Great tool369
- Makes developing rest api's easy peasy276
- Easy setup, looks good156
- The best api workflow out there144
- It's the best53
- History feature53
- Adds real value to my workflow44
- Great interface that magically predicts your needs43
- The best in class app35
- Can save and share script12
- Fully featured without looking cluttered10
- Collections8
- Option to run scrips8
- Global/Environment Variables8
- Shareable Collections7
- Dead simple and useful. Excellent7
- Dark theme easy on the eyes7
- Awesome customer support6
- Great integration with newman6
- Documentation5
- Simple5
- The test script is useful5
- Saves responses4
- This has simplified my testing significantly4
- Makes testing API's as easy as 1,2,34
- Easy as pie4
- API-network3
- I'd recommend it to everyone who works with apis3
- Mocking API calls with predefined response3
- Now supports GraphQL2
- Postman Runner CI Integration2
- Easy to setup, test and provides test storage2
- Continuous integration using newman2
- Pre-request Script and Test attributes are invaluable2
- Runner2
- Graph2
- <a href="http://fixbit.com/">useful tool</a>1
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Cons of Google Cloud Natural Language API
- Multi-lingual2
Cons of Postman
- Stores credentials in HTTP10
- Bloated features and UI9
- Cumbersome to switch authentication tokens8
- Poor GraphQL support7
- Expensive5
- Not free after 5 users3
- Can't prompt for per-request variables3
- Import swagger1
- Support websocket1
- Import curl1
