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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Conda serves as an open-source solution for managing packages, dependencies, and environments across various programming languages, including Python, R, Ruby, Lua, Scala, Java, JavaScript, C/C++, Fortran, and others. This versatile system operates seamlessly on multiple platforms such as Windows, macOS, Linux, and z/OS. With the ability to swiftly install, execute, and upgrade packages alongside their dependencies, Conda enhances productivity. It simplifies the process of creating, saving, loading, and switching between different environments on your device. Originally designed for Python applications, Conda's capabilities extend to packaging and distributing software for any programming language. Acting as an efficient package manager, it aids users in locating and installing the packages they require. If you find yourself needing a package that depends on an alternate Python version, there’s no need to switch to a different environment manager; Conda fulfills that role as well. You can effortlessly establish an entirely separate environment to accommodate that specific version of Python, while still utilizing your standard version in your default environment. This flexibility makes Conda an invaluable tool for developers working with diverse software requirements.

Description

MPCPy is a Python library designed to support the testing and execution of occupant-integrated model predictive control (MPC) within building systems. This tool emphasizes the application of data-driven, simplified physical or statistical models to forecast building performance and enhance control strategies. It comprises four primary modules that provide object classes for data importation, interaction with real or simulated systems, data-driven model estimation and validation, and optimization of control inputs. Although MPCPy serves as a platform for integration, it depends on various free, open-source third-party software for model execution, simulation, parameter estimation techniques, and optimization solvers. This encompasses Python libraries for scripting and data manipulation, along with more specialized software solutions tailored for distinct tasks. Notably, the modeling and optimization tasks related to physical systems are currently grounded in the specifications of the Modelica language, which enhances the flexibility and capability of the package. In essence, MPCPy enables users to leverage advanced modeling techniques through a versatile and collaborative environment.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Studio Lab Yes 
Arize Phoenix Yes 
CodeQwen Yes 
Coiled Yes 
Fortran Package Manager Yes 
JetBrains DataSpell Yes 
Nyala Yes 
Python No 
Reo.Dev Yes 
Seeker Yes 
Sonatype Nexus Repository Yes 
Spark NLP Yes 
Thunder Compute Yes 
Travis CI Yes 
Ubuntu No 
Ultralytics Yes 
garak Yes 

Integrations

Amazon SageMaker Studio Lab No 
Arize Phoenix No 
CodeQwen No 
Coiled No 
Fortran Package Manager No 
JetBrains DataSpell No 
Nyala No 
Python Yes 
Reo.Dev No 
Seeker No 
Sonatype Nexus Repository No 
Spark NLP No 
Thunder Compute No 
Travis CI No 
Ubuntu Yes 
Ultralytics No 
garak No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Conda

Website

docs.conda.io

Vendor Details

Company Name

MPCPy

Country

United States

Website

github.com/lbl-srg/MPCPy

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