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Lansweeper VS NumPy

Compare Lansweeper VS NumPy and see what are their differences

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Lansweeper logo Lansweeper

Lansweeper discovers Windows, Linux and Mac machines in your network.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Lansweeper Landing page
    Landing page //
    2023-08-02
  • NumPy Landing page
    Landing page //
    2023-05-13

Lansweeper

Website
lansweeper.com
Pricing URL
Official Lansweeper Pricing
$ Details
-
Release Date
2004 January
Startup details
Country
Belgium
State
Oost-Vlaanderen
City
Grembergen
Employees
100 - 249
Edit details

NumPy

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

Lansweeper features and specs

  • Comprehensive IT Asset Management
    Lansweeper provides detailed insights into various assets including hardware, software, and user data, which helps in complete IT asset tracking and management.
  • Agentless Scanning
    Lansweeper offers agentless scanning capabilities, eliminating the need to install software agents on every device, which simplifies deployment and reduces management overhead.
  • Customization and Scalability
    The platform is highly customizable and scalable, accommodating the needs of both small and large enterprises by allowing tailored reporting and flexible asset management options.
  • Integration Capabilities
    Lansweeper integrates well with other IT management tools and platforms, such as service desks, network monitoring tools, and cybersecurity solutions, which enhances its utility in a wider IT ecosystem.
  • User-Friendly Interface
    The software features an intuitive and user-friendly interface, which makes navigation, reporting, and management tasks straightforward, even for users with limited technical expertise.

Possible disadvantages of Lansweeper

  • Cost
    While Lansweeper offers a rich set of features, it can be expensive, particularly for smaller organizations or startups with limited budgets for IT tools.
  • Learning Curve
    Despite its user-friendly interface, the depth and breadth of features can result in a steep learning curve for new users, requiring time and training to fully utilize the platform’s capabilities.
  • Resource Intensive
    Lansweeper can be resource-intensive, necessitating adequate server resources and potentially competing with other applications for bandwidth and processing power, which could be an issue in resource-limited environments.
  • Limited Real-time Monitoring
    The platform's focus is more on asset management rather than real-time monitoring, which might not suffice for organizations needing instant alerts and continuous observation of IT assets.
  • Complex Configuration
    Initial setup and configuration of Lansweeper can be complex, requiring a thorough understanding of your network and meticulous planning to ensure it is tailored to your organization’s specific needs.

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.

Lansweeper videos

+ Add

IT Network Inventory | Agentless Network Discovery

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 Lansweeper and NumPy)

Lansweeper

NumPy

IT Asset Management
100 100%
IT Asset Management
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 Lansweeper 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 Lansweeper and NumPy

Lansweeper Reviews

11 NetBox Alternatives
Lansweeper is a website that manages all of your IT requirements manage IT assets and have full control over your IT. With the help of its great features, you can build your own centralized IT assets inventory and it will provide you full visibility of your IT estate. Lansweeper can handle all the assets and environments without installing any software on them and discovers...
Source: www.justalternativeto.com
9 Best Angry IP Scanner Alternatives Reviewed 2021 (Free & Paid)
Lansweeper clearly stands out from other network device scanners as it extends its capabilities into inventory management and machine maintenance. If you’re looking for a hybrid network scanner and inventory manager, Lansweeper is a great tool to use and is compatible in any Windows environment. You can use Landsweeper completely free, tracking up to 100 assets. The...
Source: www.comparitech.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 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.

Lansweeper mentions (0)

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

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 / 3 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 / 7 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

What are some alternatives?

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

Asset Panda - The cloud is playing a very important role for companies who utilize asset management software to track their assets or inventory. See how Asset Panda is leading the field thanks to their cloud-based tracking platform.

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

ALVAO IT Asset Management - ALVAO ITAM software helps you manage a wide range of assets, such as hardware, software, data, and people - it is up to you what you want to track.

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

FreeMeter - Monitor network bandwidth (C#.NET 2k/XP+). Desktop and Systray graph.

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

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