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Embeddable VS assertpy

Compare Embeddable VS assertpy and see what are their differences

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Embeddable logo Embeddable

The toolkit for building fast, interactive, fully-custom analytics experiences into your app.

assertpy logo assertpy

A straightforward assertion library for Python.
  • Embeddable Headless Embedded Analytics
    Headless Embedded Analytics //
    2025-03-18

Build Remarkable Analytics Experiences. No more 'Build vs. Buy'. Embeddable is the embedded analytics tool where you own the front-end code and we handle everything else. Now you can build fully-bespoke, fast-loading charts and dashboards in your app without the engineering costs. Delight your customers, reduce engineering overheads, and deliver your dream experience, fast. Compatible with all major databases. Cloud & Self-hosted. Multi-tenancy. Open source component library + more

  • assertpy Landing page
    Landing page //
    2022-11-06

assertpy

Website
github.com
$ Details
-
Release Date
-
Categories

Embeddable features and specs

  • Cloud-Hosted Option
  • Self-Hosted Option
  • Frontend SDK
  • No-code Dashboard Builder
  • Performant Embedding
  • Row-Level Security
  • Configurable Cache
  • Compatible with Major Databases
  • Compatible with Charting Libraries
  • Template Charting Components Provided
    Included
  • Dedicated Account Management
  • Version Control
  • Audit Logs
  • Documentation

assertpy features and specs

  • Fluent API
    Assertpy offers a fluent API that makes assertions more readable and expressive, enabling developers to write assertions in a natural language style that is easy to understand.
  • Chainable Assertions
    It allows for chainable assertions, enabling multiple checks to be performed in a single line of code, thereby reducing verbosity and enhancing clarity.
  • Comprehensive Assertion Methods
    The library provides a wide range of built-in assertion methods, catering to various types of data validations, such as checking for size, type, value, and more.
  • Extensibility
    Assertpy supports extending its functionality by defining custom assertions, allowing developers to tailor it to their specific needs.
  • Pythonic
    Designed with Pythonic principles in mind, Assertpy fits seamlessly into Python projects, enabling idiomatic and consistent code style.

Possible disadvantages of assertpy

  • Learning Curve
    Developers new to the library may encounter a learning curve due to the distinct approach of using fluent and chainable assertions as opposed to traditional methods.
  • Limited by Python Version
    The library may have limitations in terms of compatibility with older versions of Python, requiring users to ensure their environment is up-to-date.
  • Performance Overhead
    The additional abstraction layer introduced by a fluent interface might introduce some performance overhead, especially in performance-critical or resource-constrained environments.
  • Less Community Support
    Compared to more established testing libraries, Assertpy might have less community support and fewer resources available for resolving issues or getting help.
  • Dependency Management
    Using a third-party library introduces additional dependencies to manage, which could complicate project maintenance and compatibility.

Analysis of assertpy

Overall verdict

  • assertpy is a well-regarded, lightweight assertion library for Python that provides a fluent, chainable API for writing readable and expressive test assertions, making it a solid choice for improving test clarity.

Why this product is good

  • Offers a fluent, chainable assertion syntax that makes tests more readable and self-documenting
  • Comprehensive built-in assertions for strings, numbers, lists, dicts, files, dates, and more
  • Produces clear, descriptive failure messages that speed up debugging
  • Lightweight with minimal dependencies and easy to integrate into existing test suites
  • Framework-agnostic, working seamlessly with pytest, unittest, and other test runners
  • Actively maintained open-source project with good documentation and community support

Recommended for

  • Python developers who want more readable and expressive test assertions
  • Teams using pytest or unittest looking to enhance assertion clarity
  • Projects that value descriptive failure messages for faster debugging
  • Developers coming from fluent assertion libraries in other languages (like AssertJ or Chai)
  • QA engineers and testers writing maintainable, self-documenting test code

Category Popularity

0-100% (relative to Embeddable and assertpy)
Business Intelligence
100 100%
0% 0
Testing
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Python
0 0%
100% 100

Questions & Answers

As answered by people managing Embeddable and assertpy.

How would you describe the primary audience of your product?

Embeddable's answer

Software companies who care about the UX and loading speed of their customer-facing analytics.

What makes your product unique?

Embeddable's answer

Get the best of 'Build vs. Buy' in one stack-agnostic solution. Embeddable gives you full control over the frontend of your analytics experience, and handles the backend for you. No longer do you have to choose between a limited out-of-the-box solution, or building everything from scratch.

What's the story behind your product?

Embeddable's answer

Embeddable is from the team behind Trevor.io -- a popular internal BI tool which also allows you to embed dashboards into your app. We realised embedding dashboards from a BI tool into your app wasn't the 'dream solution', and building analytics from scratch was super expensive... so we built Embeddable from the ground up to enable teams to deliver fully-bespoke, highly-performant analytics in their apps for their customers in 10% of the time.

Who are some of the biggest customers of your product?

Embeddable's answer

  • Scalapay
  • Adthena
  • Irwin
  • EtonX
  • Resident Advisor
  • Facilities Solutions Group (FSG)
  • Multibrain
  • Raydiant
  • ThinkCERCA
  • Tixly
  • Softools
  • Faheem App
  • Just Move In
  • Any Creek

Why should a person choose your product over its competitors?

Embeddable's answer

If you want full control over the UX of your customer-facing analytics experience, but don't want to invest months of developer time on building and maintaining a fully-custom build -- OR -- if you're using an embedded analytics too already that loads slowly and doesn't look and feel like the rest of your platform.

User comments

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Reviews

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

Embeddable Reviews

6 Best Looker alternatives
After a successful, oversubscribed Private Beta, Embeddable is now publicly available. More information on how to work with Embeddable can be found on their homepage at embeddable.com. Get in touch with the Embeddable team for pricing.
Source: trevor.io
Power BI Embedded vs Looker Embedded: Everything you need to know
The main differences between Power BI Embedded and Embeddable are performance, price, and customizability. Embeddable gives you full control over your charting components and data models. Itโ€™s also built from the ground up to enable companies to deliver fully bespoke, highly-performant analytics experiences to their customers, without requiring an expensive in-house build....
Source: embeddable.com
Embedded analytics in B2B SaaS: A comparison
Iโ€™m happy to say that weโ€™ve enrolled in the beta program of Embeddable. After learning all the above it seems like this is the option weโ€™d want to invest in. Weโ€™ll keep you posted on how this pans out, but weโ€™re excited about what Embeddable is building and is going to offer.
Source: medium.com

assertpy Reviews

We have no reviews of assertpy yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Embeddable seems to be more popular. It has been mentiond 2 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.

Embeddable mentions (2)

  • AI in BI tools: why we're not there yet
    Then comes data modeling. BI tools such as Embeddable need to know how different tables and fields relate to each other. Someone has to define what terms like โ€œtop customerโ€ or โ€œQ3 revenueโ€ actually mean. Without this, the AI won't know where to look or how to answer even basic questions. - Source: dev.to / over 1 year ago
  • Apache Superset
    Itโ€™s still pretty new but build by an experienced team. Itโ€™s commercial software though. https://embeddable.com/. - Source: Hacker News / over 2 years ago

assertpy mentions (0)

We have not tracked any mentions of assertpy yet. Tracking of assertpy recommendations started around Mar 2021.

What are some alternatives?

When comparing Embeddable and assertpy, you can also consider the following products

Luzmo - From data to decisions, damn fast. Embed beautiful, easy-to-use dashboards in your SaaS product in days, not months.

grappa - grappa is an declarative, verbose, and expressive assertion library for Python.

Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

POWr - POWr is a library of free and customizable forms, galleries, social streams, e-commerce, countdowns, and more.

Vizzly - Customer-facing dashboards for your app. Build in days, not months.