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figshare VS assertpy

Compare figshare VS assertpy and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

figshare logo figshare

Securely store and manage your research outputs in the cloud, or make them openly available and citable.

assertpy logo assertpy

A straightforward assertion library for Python.
  • figshare Landing page
    Landing page //
    2023-10-21
  • assertpy Landing page
    Landing page //
    2022-11-06

figshare features and specs

  • Open Access
    Figshare allows researchers to make their data, results, and publications freely accessible, promoting transparency and enhancing the visibility and reach of their work.
  • Versatility
    It supports a wide range of file types and formats, which makes it versatile for different types of research outputs from datasets to videos and presentations.
  • DOI Assignment
    Figshare assigns a Digital Object Identifier (DOI) to every uploaded item, ensuring that users receive a permanent, citable link for their work.
  • User-friendly Interface
    The platform has an intuitive interface that makes it easy for users to upload, manage, and share their research outputs without technical difficulties.
  • Embeddable
    Research outputs on Figshare can be easily embedded into other websites and platforms, enhancing their visibility and ease of access among various audiences.

Possible disadvantages of figshare

  • Storage Limitations
    While Figshare offers free storage, there are limitations to the amount of data a user can store without incurring costs, which might not suffice for large datasets.
  • Cost for Extended Features
    Some advanced features and larger storage require payment, which can be a barrier for individuals or institutions with limited funding.
  • Limited Customization
    Users may find the level of customization for their data presentations limited compared to other specialized repositories.
  • Data Privacy
    Due to its open access nature, sensitive data needs to be properly anonymized or withheld, which could be a concern for certain types of research.
  • Competition and Redundancy
    With many other repositories available, there might be redundancy in data sharing, and some users may prefer platforms that are more specific to their research field.

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

figshare videos

Figshare for Institutions Admin User Guide Video: Reviewing Items

More videos:

  • Review - Figshare for Institutions โ€” The All in One Repository
  • Demo - Figshare repository demonstration

assertpy videos

No assertpy videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to figshare and assertpy)
Research Tools
100 100%
0% 0
Testing
0 0%
100% 100
Education
100 100%
0% 0
Python
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, figshare seems to be more popular. It has been mentiond 3 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.

figshare mentions (3)

  • 1,600 Days of a Failed Hobby Data Science Project
    I'll put a shoutout for https://zenodo.org/ and https://figshare.com/ as places to put your data, where you'll get a DOI and can let someone that's not a company look after hosting and backing it up. Zenodo is hosted as long as CERN is around (is the promise) and figshare is backed by the CLOCKSS archive (multiple geographically distributed universities). - Source: Hacker News / over 1 year ago
  • My super useful websites collection for you all!
    -Crystal growing information Http://xrayweb.chem.ou.edu/notes/xtalgrow.html Https://www.chemistryviews.org/details/education/2538901/Tips\_and\_Tricks\_for\_the\_Lab\_Growing\_Crystals\_Part\_2.html Free science Figures Https://smart.servier.com/ Https://phil.cdc.gov/ Databases of molecules and data Https://www.ebi.ac.uk/chembl/ - database of bioactive molecules with drug-like... Source: almost 5 years ago
  • Want to post my research
    I am a PhD student and conducting a clinical trial in eczema. I have used figshare.com to make my work public, which is used by many universities and academics to disseminate their work for free! No doubt that publishing in journals is the best way to reach your target audience, however there might be cost implications. Source: almost 5 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 figshare and assertpy, you can also consider the following products

Zenodo - Network & Admin and Remote Work & Education

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

Open Science Framework - Open Science Framework provides project management with collaborators, and project sharing with the public.

ORCHID - Platform is a flexible, business application development tool to quickly create web business...

arXiv - arXiv is a free distribution service and an open-access archive for scholarly articles.

Crosspost - Write once, publish everywhere.