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htop VS NumPy

Compare htop VS NumPy and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

htop logo htop

htop - an interactive process viewer for Unix. This is htop, an interactive process viewer for Unix systems. It is a text-mode application (for console or X terminals) and requires ncurses. Latest release: htop 2.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • htop Landing page
    Landing page //
    2021-09-20
  • NumPy Landing page
    Landing page //
    2023-05-13

htop features and specs

  • User-friendly Interface
    htop features a colorful, visually appealing interface that displays system processes in a tree structure, which makes it easier to understand process hierarchies and relationships.
  • Interactive Process Management
    You can easily manage processes in htop by using keyboard shortcuts to kill, renice, or trace processes without needing to type out commands.
  • Customizable Display
    htop allows users to customize which metrics are displayed and in what order, enabling more efficient monitoring tailored to individual needs.
  • Resource Usage Meters
    It provides live updating meters and histograms for CPU, memory, and swap usage, offering a quick overview of system performance.
  • Process Filtering and Sorting
    htop includes advanced filtering and sorting options that make it easy to find specific processes or sort them by criteria like CPU usage, memory usage, or user.
  • Cross-Platform Compatibility
    htop is compatible with a variety of Unix-like systems including Linux, FreeBSD, OpenBSD, and macOS, making it versatile for use in different environments.

Possible disadvantages of htop

  • Resource Consumption
    Because htop provides live updates and a rich graphical interface, it consumes more system resources compared to simpler tools like top.
  • Limited Remote Monitoring
    htop does not natively support remote monitoring of systems, which can make it less useful in distributed or cloud environments without additional tools or configurations.
  • Learning Curve for Advanced Features
    While the basic interface is intuitive, mastering htop's advanced features and customizations may require additional learning and familiarity.
  • No Built-in Logging
    htop does not have functionality for logging or saving historical data, which can limit its usefulness for performance tracking over time without third-party tools.
  • Dependency on Terminal
    As a terminal-based application, htop requires a terminal to run, which might not be ideal for users who prefer GUI-based monitoring tools.
  • Lack of Detailed Metrics
    htop provides an overview of system performance but does not offer the granularity of metrics provided by specialized monitoring tools dedicated to in-depth analysis.

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.

Analysis of htop

Overall verdict

  • Yes, htop is considered a good tool. It improves upon the functionality of the standard top command by providing a more intuitive interface and additional features that enhance usability and efficiency in system monitoring.

Why this product is good

  • Htop is an interactive process viewer for Unix systems, offering an enhanced, user-friendly alternative to the traditional top command. It provides a visually appealing interface that allows users to easily monitor system processes, resource usage, and performance in real-time. Features like tree view for process hierarchies, customizable meters, and the ability to manage processes make it a popular tool among system administrators and power users.

Recommended for

  • System administrators
  • Linux and Unix users
  • IT professionals
  • Developers interested in system performance
  • Servers monitoring

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.

htop videos

+ Add

Htop Review Video

More videos:

  • Review - HTOP Hotel DO's and DONT's || REVIEW #2
  • Review - Htop - Terminal-Based Interactive Process Viewing Program

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

Category Popularity

0-100% (relative to htop and NumPy)

htop

NumPy

Command Line Tools
100 100%
Command Line Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Monitoring Tools
100 100%
Monitoring Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using htop and NumPy. For example, how are they different and which one is better?
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Reviews

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

htop Reviews

Best Linux Network Monitoring Tools for 2020
At this point in the list, weโ€™re starting to review less-complex programs to monitor small-network use with accuracy and reliability. Htop (the H stands for the designerโ€™s name, Hisham) doesnโ€™t contain graphical analysis software, but it provides a flexible monitoring program that can be installed on Linux as well as Unix-based systems. Htop might not be the most visually...
Source: www.dnsstuff.com

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

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.

htop mentions (0)

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

NumPy mentions (122)

View more

What are some alternatives?

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

Process Explorer - The top window always shows a list of the currently active processes, including the names of their owning accounts, whereas the information displayed in the bottom window depends on the mode that Process Explorer is in: if it is in handle mode you'lโ€ฆ

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

glances system monitoring - Glances is a cross-platform system monitoring tool written in Python. Written in Python, Glances will run on almost any plaftorm : GNU/Linux, FreeBSD, OS X and Windows.

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

SystemExplorer - Homepage of System Explorer. Freeware Tool for displaying and managing system internals

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

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