Software Alternatives, Accelerators & Startups

NumPy VS CrankWheel

Compare NumPy VS CrankWheel and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

CrankWheel logo CrankWheel

Insanely simple, enterprise-friendly screen sharing, free for individual use.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • CrankWheel Landing page
    Landing page //
    2022-01-25

Share your screen to any device during a phone call. Just send a link via SMS, email, IM or say the URL to the session.

The viewer enters in seconds with one click. No prompts for registration, installation or downloads.

Features:

  • Share your entire screen, browser tab or program window

  • Grant control of the screen to the viewer

  • Stream HQ videos with sound

  • See what your viewer is seeing and how they engage with content

  • Post-session redirect to your landing page

  • Record your screen and share the recording

  • CTA widget for warm leads that alerts your sales team the second they request a call

Ideal for selling to hard-to-reach decision-makers such as individuals and small business owners.

Used in verticals where the product is better explained with visuals than words. Insurance sales, solar sales, SaaS sales, selling digital services, mortgage advice, financial services

CrankWheel

$ Details
freemium $15.0 / Monthly (Individual user)
Platforms
Google Chrome Firefox Windows Mac OSX Linux Web Browser Edge Opera
Release Date
2016 January
Startup details
Country
Iceland
Employees
1 - 9

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

CrankWheel features and specs

  • Screen sharing
  • Remote Desktop Access
  • Conference Calling
  • Video Sharing
  • Lead Capture
  • Screen Recorder
  • E-signature

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Analysis of CrankWheel

Overall verdict

  • CrankWheel is a solid choice for businesses seeking a straightforward, reliable screen sharing solution that does not require extensive technical setup or installation. It is particularly effective for use cases where time is of the essence, and simplicity is key.

Why this product is good

  • CrankWheel is often praised for its ease of use, quick setup, and seamless integration capabilities, especially for sales teams and customer service operations. It requires no software installation for viewers, which makes it extremely accessible as participants can join meetings instantly via their web browser. Its real-time screen sharing is noted for being reliable and fast, ensuring that users can effectively engage in presentations or demonstrations.

Recommended for

  • Sales teams needing a quick and reliable presentation tool.
  • Businesses that require consistent and accessible customer support solutions.
  • Organizations looking for a browser-based screen sharing service without the need for software installs for viewers.
  • Individuals or teams conducting software demos or training remotely.

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

CrankWheel videos

Share screen to desktop or tablet

More videos:

  • Review - Testimonials from insurance agents
  • Review - Testimonials from digital agency sales
  • Tutorial - Share screen to a mobile
  • Demo - Instant lead capture
  • Review - CrankWheel Interactive Webinar

Category Popularity

0-100% (relative to NumPy and CrankWheel)
Data Science And Machine Learning
Sales
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Customer Support
0 0%
100% 100

Questions & Answers

As answered by people managing NumPy and CrankWheel.

What makes your product unique?

CrankWheel's answer:

CrankWheel gives you instant screen sharing. Your viewers just click on a link. There are not pop-ups that nudge them to download an app or register first. You can also record your screen, give control or get electronic signatures in a screen share.

Why should a person choose your product over its competitors?

CrankWheel's answer:

CrankWheel is easier to use for everyone and you can share to any device without asking your viewers to download anything.

How would you describe the primary audience of your product?

CrankWheel's answer:

Salespeople who sell to remote clients. Health and Life insurance agents, solar sales agents, digital marketers and people selling home services and consultations to small business owners.

What's the story behind your product?

CrankWheel's answer:

An ex-Googler returned home after more than a decade abroad and met a childhood friend with over 15 years of experience in selling insurance over the phone. They decided to develop a solution for salespeople to show their screens without having to go to the prospect's home and show a laptop.

Which are the primary technologies used for building your product?

CrankWheel's answer:

CrankWheel is a browser-based screen sharing app that is based on WebRTC.

Who are some of the biggest customers of your product?

CrankWheel's answer:

  • Health Agents
  • SunRun
  • Yell
  • Yellow Pages
  • Connells Group
  • Vendasta

User comments

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Reviews

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

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

CrankWheel Reviews

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

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 122 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.

NumPy mentions (122)

View more

CrankWheel mentions (0)

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

What are some alternatives?

When comparing NumPy and CrankWheel, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Webnexs POS - Webnexs POS is a worldโ€™s most leading and comprehensive POS (point of sale) solution designed to let you sell from your one e-commerce website.

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

SellerCloud - SellerCloud is a multi-channel inventory and order management system.

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

Melissa Data Quality - Melissa helps companies to harness Big Data, legacy data, and people data (names, addresses, phone numbers, and emails).