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What is yarl?

Each part of a URL, which includes the scheme, user, password, host, port, path, query, and fragment, can be accessed via their designated properties. When a URL is manipulated, it creates a new URL object, and any strings passed into the constructor or modification functions are automatically encoded to achieve a standard format. Standard properties return values that are percent-decoded, while the raw_ variants are used when you need the encoded strings. For a version of the URL that is easier for humans to read, the .human_repr() method can be utilized. The yarl library offers binary wheels on PyPI for various operating systems, including Linux, Windows, and MacOS. If you need to install yarl on systems like Alpine Linux, which do not meet manylinux standards because they lack glibc, you will have to compile the library from the source using the provided tarball. This compilation requires that you have a C compiler and the appropriate Python headers installed on your system. It's crucial to note that the uncompiled, pure-Python version of yarl tends to be significantly slower than its compiled counterpart. However, users of PyPy will find that it generally uses a pure-Python implementation, meaning it does not suffer from these performance discrepancies. Consequently, PyPy users can rely on the library to deliver consistent behavior across different environments, ensuring a uniform experience no matter where it is run.

What is MPI for Python (mpi4py)?

In recent times, high-performance computing has become increasingly available to a larger pool of researchers in the scientific field than it ever has been before. The effective synergy of high-quality open-source software and reasonably priced hardware has played a crucial role in the widespread utilization of Beowulf class clusters and workstation clusters. Among the various approaches to parallel computation, message-passing has stood out as a notably efficient model. This approach is particularly advantageous for distributed memory systems and is heavily relied upon in today’s most challenging scientific and engineering tasks related to modeling, simulation, design, and signal processing. However, the environment for portable message-passing parallel programming used to be complicated, as developers had to navigate a multitude of incompatible choices. Fortunately, this scenario has vastly improved since the MPI Forum established its standard specification, which has simplified the development process considerably. Consequently, researchers are now able to dedicate more of their efforts to advancing their scientific research instead of dealing with the intricacies of programming. This shift not only enhances productivity but also fosters innovation across various disciplines.

Media

Media

Integrations Supported

Python
C
C++
Fortran
NumPy

Integrations Supported

Python
C
C++
Fortran
NumPy

API Availability

Has API

API Availability

Has API

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

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

Company Facts

Organization Name

Python Software Foundation

Company Location

United States

Company Website

pypi.org/project/yarl/

Company Facts

Organization Name

MPI for Python

Company Website

mpi4py.readthedocs.io/en/stable/

Categories and Features

Categories and Features

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