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NumPy VS Scrivener

Compare NumPy VS Scrivener and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Scrivener logo Scrivener

Scrivener is a content-generation tool for composing and structuring documents.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Scrivener Landing page
    Landing page //
    2021-10-16

FROM LITERATURE & LATTE WEBSITE: Scrivener is the go-to app for writers of all kinds, used every day by best-selling novelists, screenwriters, non-fiction writers, students, academics, lawyers, journalists, translators and more. Tailor-made for long writing projects, Scrivener banishes page fright by allowing you to compose your text in any order, in sections as large or small as you like. Got a great idea but don't know where it fits? Write when inspiration strikes and find its place later. Grow your manuscript organically, idea by idea. In Scrivener, everything you write is integrated into an easy-to-use project outline. So working with an overview of your manuscript is only ever a click away, and turning Chapter Four into Chapter One is as simple as drag and drop. Need to refer to research? In Scrivener, your background material is always at hand, and you can open it right next to your work. Write a description based on a photograph. Transcribe an interview. Take notes about a PDF file or web page. Or check for consistency by referencing an earlier chapter alongside the one in progress. Once you're ready to share your work with the world, compile everything into a single document for printing, self-publishing, or exporting to popular formats such as Word, PDF, Final Draft or plain text. You can even share using different formatting, so that you can write in your favorite font and still satisfy those submission guidelines.

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.

Scrivener features and specs

  • Comprehensive Organizational Tools
    Scrivener offers a robust suite of tools like the corkboard, outliner, and binder, allowing for seamless organization and structuring of complex documents, making it easier to manage large projects.
  • Distraction-Free Writing Mode
    Scrivener provides a distraction-free writing mode that helps users focus solely on their writing by hiding all other elements on the screen.
  • Research Integration
    Users can import and manage research materials directly within the application, including PDFs, images, and web pages, which helps in keeping all relevant data in one place.
  • Customizable Workspaces
    Scrivener allows for extensive customization of the workspace, enabling users to set up their writing environment according to their preferences and needs.
  • Versatile Export Options
    Offers a range of export options to various formats such as PDF, Word, ePub, and more, facilitating easy sharing and publishing.
  • Snapshot Feature
    The snapshot feature allows users to save versions of their work before making major changes, providing a safety net to revert back if needed.

Possible disadvantages of Scrivener

  • Steep Learning Curve
    Due to its extensive features and functionalities, new users may find Scrivener overwhelming and may require a significant amount of time to fully master the software.
  • Cost
    Scrivener is a paid software with a one-time purchase cost, which might be a deterrent for those who are looking for free writing tools.
  • Limited Collaboration Features
    Scrivener lacks robust real-time collaboration tools, making it less ideal for projects requiring simultaneous multi-user editing.
  • Compatibility Issues
    While Scrivener is available for both macOS and Windows, some users have reported compatibility issues and feature discrepancies between the two versions.
  • Mobile App Limitations
    The mobile version of Scrivener, though useful, is not as feature-rich as the desktop version, which might limit productivity on the go.
  • Complex Export Process
    Some users find the export process to be complicated and not as straightforward as they would like, requiring additional time to configure settings appropriately.

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

Scrivener videos

Scrivener vs Word: Review of What Scrivener Can Do For You

More videos:

  • Review - Ultimate Scrivener 3 Review
  • Review - Why I Think Scrivener is For Everyone (and why I like it so much)

Category Popularity

0-100% (relative to NumPy and Scrivener)
Data Science And Machine Learning
Writing Tools
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Markdown Editor
0 0%
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 Scrivener

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

Scrivener Reviews

11 Best Scrivener Alternatives
The app’s interface looks similar to Scrivener, but you get a different experience based on your level and interests. Scrivener’s learning curve is designed for intermediate or higher levels of writers, but Ulysses makes it easier by offering tutorials along with its features.
7 Best Scrivener Alternatives
This writing tool is a Scrivener alternative that is similar to a Scrivener. The appearance of the user interface is identical to Scrivener but a little bit more modern.
5 Free Scrivener Alternatives to Manage Writing Projects
Ask most experts what the best novel writing software is, and they’ll usually tell you Scrivener. It’s also a popular tool for organizing research for most writing projects, although it’s not free. While they’re not always as robust, free Scrivener alternatives help you accomplish similar results without any fees. For students, full-time writers, and even freelancers, these...
9 Scrivener Alternative Tools: Overview, Pros, And Cons
No direct import from Scrivener: Ulysses doesn’t handle Scrivener files, at least not directly. You have to export your content as MultiMarkdown files in Scrivener first, click Save, and drag the .mmd file into Ulysses’ library.
17 Top Evernote Alternatives for Note-Taking for 2019
If your notes have anything to do with any type of writing: outlines, notes on drafts, brain dumps on story ideas, blog posts, scripts, essays, anything like that—you should migrate all of it to Scrivener.

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 / 4 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 / 8 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 / 8 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 / 9 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 / 9 months ago
View more

Scrivener mentions (0)

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

What are some alternatives?

When comparing NumPy and Scrivener, 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.

Manuskript - Open-source tool for writers.

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

iA Writer - Minimal Design, Maximum Focus

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

yWriter - Free writing software designed by the author of the Hal Spacejock and Hal Junior series. yWriter6 helps you write a book by organising chapters, scenes, characters and locations in an easy-to-use interface.