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What is Growler?

Growler is a cutting-edge web framework built on asyncio, the asynchronous library introduced in PEP 3156 and included in the standard library starting with Python 3.4. It draws on the design principles of Connect and Express from the Node.js environment, employing a consolidated application object alongside a series of middleware to efficiently handle HTTP requests. This flexible middleware chain facilitates the straightforward creation of intricate applications while avoiding unnecessary complexity. With the support of the pip package manager, users can install only the optional dependencies they need, which aligns perfectly with Growler's commitment to a minimalist design that shuns superfluous installations. Additionally, the Growler community encourages developers to create and maintain supplementary packages that have been thoroughly tested for compatibility and stability with every release of Growler, ensuring that these extensions are easily accessible. By focusing on user autonomy, the framework emphasizes the inclusion of only the fundamental components required for optimal performance, thereby enhancing the overall development experience. This approach not only promotes efficiency but also fosters an ecosystem where developers can thrive and innovate.

What is Apache Mahout?

Apache Mahout is a powerful and flexible library designed for machine learning, focusing on data processing within distributed environments. It offers a wide variety of algorithms tailored for diverse applications, including classification, clustering, recommendation systems, and pattern mining. Built on the Apache Hadoop framework, Mahout effectively utilizes both MapReduce and Spark technologies to manage large datasets efficiently. This library acts as a distributed linear algebra framework and includes a mathematically expressive Scala DSL, which allows mathematicians, statisticians, and data scientists to develop custom algorithms rapidly. Although Apache Spark is primarily used as the default distributed back-end, Mahout also supports integration with various other distributed systems. Matrix operations are vital in many scientific and engineering disciplines, which include fields such as machine learning, computer vision, and data analytics. By leveraging the strengths of Hadoop and Spark, Apache Mahout is expertly optimized for large-scale data processing, positioning it as a key resource for contemporary data-driven applications. Additionally, its intuitive design and comprehensive documentation empower users to implement intricate algorithms with ease, fostering innovation in the realm of data science. Users consistently find that Mahout's features significantly enhance their ability to manipulate and analyze data effectively.

Media

Media

Integrations Supported

Apache Spark
Hadoop
Python

Integrations Supported

Apache Spark
Hadoop
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Growler

Company Website

github.com/pyGrowler/Growler

Company Facts

Organization Name

Apache Software Foundation

Company Location

United States

Company Website

mahout.apache.org

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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