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NumPy VS Contractbook

Compare NumPy VS Contractbook and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Contractbook logo Contractbook

Helping businesses scale with future-proof contracts
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Contractbook Landing page
    Landing page //
    2022-07-12

Contractbook turns static contracts into a database for the entire organization, unlocking the full value of your data - ensuring transparency and a seamless data flow between tools. Funded by investors including Tiger Global, Bessemer Venture Partners, and Gradient Ventures, Contractbook was founded in Copenhagen in 2017 and serves over 250,000 users in more than 85 countries. Step into the new era and take control of your contracts at contractbook.com.

NumPy

Website
numpy.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

Contractbook

Website
contractbook.com
Pricing URL
Official Contractbook Pricing
$ Details
paid $999.0 / Monthly (Foundation Plan (Contact us for more information))
Platforms
Salesforce Slack Hubspot Pipedrive
Release Date
2016 January
Startup details
Country
Denmark
State
Hovedstaden
City
Copenhagen
Founder(s)
Jarek Owczarek
Employees
50 - 99
Edit details

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.

Contractbook features and specs

  • Demo
    https://contractbook.com/book-a-meeting-partner
  • Partnership
    https://contractbook.com/partnership

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 Contractbook

Overall verdict

  • Overall, Contractbook is considered a reliable and efficient tool for businesses looking to digitize and automate their contract management processes. Its emphasis on seamless collaboration and automation makes it a valuable asset, especially for small to medium-sized enterprises seeking to optimize their legal and administrative workflows.

Why this product is good

  • Contractbook is a digital contract management platform designed to streamline the process of managing contracts throughout their lifecycle. It offers features like contract automation, electronic signatures, and collaboration tools that help businesses save time, reduce errors, and ensure compliance. Users often appreciate its user-friendly interface, integration capabilities with other tools, and the ability to automate repetitive tasks.

Recommended for

    Small to medium-sized businesses, legal teams, freelancers, and any organizations seeking to improve their contract management efficiency through digital solutions and automation.

NumPy videos

+ Add

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

Contractbook videos

+ Add

Contractbook Explainer

More videos:

  • Review - The Contractbook signing experience
  • Review - Creating and Managing Teams in Contractbook

Category Popularity

0-100% (relative to NumPy and Contractbook)

NumPy

Contractbook

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Contract Management
0 0%
Contract Management
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Contract Lifecycle Management
0 0%
Contract Lifecycle Management
100% 100

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 Contractbook

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.
Source: www.analyticsvidhya.com
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

Contractbook Reviews

Top 20 PandaDoc Alternatives and Competitors in 2024
Contractbook simplifies the entire contract lifecycle by keeping all your contracts in one place and saving detailed document history, making it a good option for collaboration with multiple stakeholders.
Source: oneflow.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 119 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 (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

Contractbook mentions (0)

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

What are some alternatives?

When comparing NumPy and Contractbook, 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.

PandaDoc - Boost your revenue with PandaDoc. A document automation tool that delivers higher close rates and shorter sales cycles. We've helped over 30,000+ companies.

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

ContractWorks - ContractWorks provides secure and easy-to-use contract management software that helps you gain control of your contracts.

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

DocuSign - Try DocuSign's interactive signing demo now! Send yourself an electronic document to digitally sign using our e-signature service.

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