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What is broot?

The ROOT data analysis framework is a prominent tool in High Energy Physics (HEP) that utilizes its own specialized file format (.root) for data storage. It boasts seamless integration with C++ programs, and for those who prefer Python, it offers an interface known as pyROOT. Unfortunately, pyROOT faces challenges with compatibility for Python 3.4, which has led to the development of a new library called broot. This streamlined library is designed to convert data contained in Python's numpy ndarrays into ROOT files, organizing data by creating a branch for each array. The primary goal of this library is to provide a consistent method for exporting numpy data structures to ROOT files efficiently. Additionally, broot is crafted to be both portable and compatible across Python 2 and 3, as well as with ROOT versions 5 and 6, requiring no modifications to the existing ROOT components—only a standard installation is sufficient. Users will appreciate the straightforward installation process, as they can either compile the library once or install it conveniently as a Python package, making it an attractive option for data analysis tasks. This user-friendly approach is likely to encourage an increasing number of researchers to incorporate ROOT into their data analysis routines. Overall, the accessibility and functionality of broot enhance the versatility of using ROOT in various research settings.

What is NumPy?

Quick and versatile, the principles of vectorization, indexing, and broadcasting in NumPy have established themselves as the standard for modern array computations. This robust library offers a comprehensive suite of mathematical functions, random number generation tools, linear algebra operations, Fourier transformations, and much more. NumPy's compatibility with a wide range of hardware and computing platforms allows it to work effortlessly with distributed systems, GPU libraries, and sparse array structures. At its foundation, NumPy is constructed with highly optimized C code, enabling users to benefit from the speed typical of compiled languages while still enjoying the flexibility provided by Python. The intuitive syntax of NumPy enhances its user-friendliness and efficiency for programmers of all levels and expertise. By merging the computational power of languages such as C and Fortran with Python’s approachability, NumPy streamlines complex processes, leading to solutions that are both clear and elegant. As a result, this library equips users to confidently and easily address a diverse array of numerical challenges, making it an essential tool in the world of data science and numerical analysis. Furthermore, the active community around NumPy continuously contributes to its development, ensuring that it remains relevant and powerful in the face of evolving computational needs.

What is CUPS-PDF?

CUPS-PDF is available under the GPL license and can be utilized across various operating systems or compiled directly from its source code. This software is designed to facilitate the creation of PDF documents within a network by providing a PDF printer that operates from a central file server. As CUPS-PDF modifies file ownership, it necessitates root access to function correctly. To ensure that CUPS-PDF can operate with the required root privileges, it is crucial to assign the ownership of the cups-pdf backend to 'root' while setting the backend's file permissions to 0700, which restricts access solely to the root user. Furthermore, CUPS-PDF performs best on a comprehensive UNIX filesystem, so it is vital to verify that any working directories linked to CUPS-PDF located on NFS-mounted volumes are appropriately mounted. Properly configuring these settings and permissions is essential for the effective operation of CUPS-PDF in networked setups. Therefore, attention to these details can significantly enhance the stability and reliability of PDF document creation in diverse environments.

Media

Media

Media

Integrations Supported

Avanzai
CentOS
Codédex
Cython
Dash
Flower
FreeBSD
Gentoo
JAX
NVIDIA FLARE
PaizaCloud
Slackware
Spyder
Train in Data
Unify AI
Yamak.ai
Yandex Data Proc
h5py
imageio
openSUSE Leap

Integrations Supported

Avanzai
CentOS
Codédex
Cython
Dash
Flower
FreeBSD
Gentoo
JAX
NVIDIA FLARE
PaizaCloud
Slackware
Spyder
Train in Data
Unify AI
Yamak.ai
Yandex Data Proc
h5py
imageio
openSUSE Leap

Integrations Supported

Avanzai
CentOS
Codédex
Cython
Dash
Flower
FreeBSD
Gentoo
JAX
NVIDIA FLARE
PaizaCloud
Slackware
Spyder
Train in Data
Unify AI
Yamak.ai
Yandex Data Proc
h5py
imageio
openSUSE Leap

API Availability

Has API

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

broot

Company Website

pypi.org/project/broot/

Company Facts

Organization Name

NumPy

Company Website

numpy.org

Company Facts

Organization Name

CUPS-PDF

Company Website

www.cups-pdf.de/

Categories and Features

Categories and Features

Categories and Features

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