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AWS Data Wrangler VS Cucumber

Compare AWS Data Wrangler VS Cucumber and see what are their differences

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AWS Data Wrangler logo AWS Data Wrangler

Pandas on AWS. Contribute to awslabs/aws-data-wrangler development by creating an account on GitHub.

Cucumber logo Cucumber

Cucumber is a BDD tool for specification of application features and user scenarios in plain text.
  • AWS Data Wrangler Landing page
    Landing page //
    2023-08-29
  • Cucumber Landing page
    Landing page //
    2022-01-19

AWS Data Wrangler videos

+ Add

AWS Tutorials - Introduction to AWS Data Wrangler

More videos:

  • Review - AWS Data Wrangler: Get Glue Catalog Table Description
  • Review - AWS Data Wrangler: Write Parquet to AWS S3

Cucumber videos

+ Add

Madam Kilay Skin Magical Review / Orange cucumber review

More videos:

  • Review - Puff Bar - Cucumber Review (Best Disposable Vape Brand)
  • Review - THE CUCUMBER CHALLENGE! (1 MILLION SUBSCRIBER SPECIAL)
  • Tutorial - Cucumber automation suit

Category Popularity

0-100% (relative to AWS Data Wrangler and Cucumber)

AWS Data Wrangler

Cucumber

Databases
100 100%
Databases
0% 0
Automated Testing
0 0%
Automated Testing
100% 100
Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Testing
0 0%
Testing
100% 100

User comments

Share your experience with using AWS Data Wrangler and Cucumber. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare AWS Data Wrangler and Cucumber

AWS Data Wrangler Reviews

We have no reviews of AWS Data Wrangler yet.
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Cucumber Reviews

5 Selenium Alternatives to Fill in Your Top Testing Gaps
Business testers are likely to prefer to use Cucumber over Selenium since script Cucumber lets you write test scenarios using a plain-English scripting language called Gherkin. Using Gherkin instead of code makes test script creation a much simpler process, since anyone can read, write, and understand the scripts regardless of testing experience.
Source: www.perfecto.io
Top 20 Best Automation Testing Tools in 2018 (Comprehensive List)
Cucumber is an open-source tool that is designed over the concept of BDD (Behavior-driven development). It is used to perform the automated acceptance testing by running the examples that best describe the behavior of the application. It gets you a single up-to-date living document that is having both specification and test documentation.
Source: www.softwaretestinghelp.com

Social recommendations and mentions

Based on our record, AWS Data Wrangler should be more popular than Cucumber. It has been mentiond 4 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.

AWS Data Wrangler mentions (4)

  • Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
    I had no problem with awswrangler (https://github.com/aws/aws-sdk-pandas) and it supports reading and writing partitions which was really helpful and a few other optimizations that made it a great tool. Source: 5 months ago
  • Redshift API vs. other ways to connect?
    Awslabs has developed their own package for this and given it's for their product, seem likely to maintain it. https://github.com/awslabs/aws-data-wrangler. Source: over 2 years ago
  • Parquet files
    AWS data wrangler works well. it's a wrapper on pandas: https://github.com/awslabs/aws-data-wrangler. Source: over 2 years ago
  • Go+: Go designed for data science
    Yep, agreed. Go is a great language for AWS Lambda type workflows. Python isn't as great (Python Lambda Layers built on Macs don't always work). AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) provides pre-built layers, which is a work around, but something that's as portable as Go would be the best solution. - Source: Hacker News / about 3 years ago

Cucumber mentions (1)

What are some alternatives?

When comparing AWS Data Wrangler and Cucumber, you can also consider the following products

Dask - Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love

Selenium - Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Robot framework - Robot Framework is a generic test automation framework for acceptance testing and acceptance...

Kafka - Apache Kafka is publish-subscribe messaging rethought as a distributed commit log.

JUnit - JUnit is a simple framework to write repeatable tests.

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