China 
Africa 
Explore chapters and articles related to this topic
Python API Modules for Machine Learning and Arduino
Published in Amartya Mukherjee, Nilanjan Dey, Smart Computing with Open Source Platforms, 2019
Amartya Mukherjee, Nilanjan Dey
Python package installer is called pip. In all Python versions, pip is available. Before using pip, first, we have to check the version of Python that is being currently used. This can be done using the following command:
Design and development of a web-based EPANET model catalogue and execution environment
Published in Annals of GIS, 2021
Tylor Bayer, Daniel P. Ames, Theodore G. Cleveland
Several of the same technologies used in the EPANET Model Repository were also implemented in the EPANET Model Viewer, however, being a more specialized application, it required the addition of more specialized tools. In addition to Tethys Platform, HydroShare, jQuery, and Bootstrap (as described in Section 3.2) key technologies used in the EPANET Model Repository include: EPANETTOOLS – Python wrapper for running EPANET models; Installed with pip; Requires a C compiler.SigmaJS – JavaScript graphics library for drawing networks of connected nodes.Plotly – High-level JavaScript graphing library; Used to create scientific plots and charts; Includes many tools for data viewing and manipulation.
Tutorial: The LuxPy Python Toolbox for Lighting and Color Science
Published in LEUKOS, 2020
Note that Anaconda from Continuum Analytics is a free and open-source distribution of Python for scientific computing that eases package management and deployment (it contains a large set packages specifically aimed at scientific computation). Enthought Canopy is another option. Once installed, activate the virtual environment (this step must be done each time you want to use any of the packages installed in the environment) by typing:Install pip—installer for packages listed on the Python Package Index (pypi.python.org)—to the py36 conda virtual environment to ensure that any packages installed with pip will be installed to the py36 environment and not globally:The LuxPy package can now be installed by typing:
Simpy Simulation of Patient Priority-Based Cloud Healthcare System
Published in IETE Journal of Research, 2022
Subhasish Mohapatra, Abhishek Roy
The DES framework is the enigmatic feature of Simpy library, performed by a Python generator function. It is used to simulate any theoretical model before its actual implementation. It synchronizes event interaction under a multi-agent platform and performs prototype model simulation under temporal scenarios. It not only showcases continuous simulation of resources but also identifies resource modeling. Subsequently, it checks upon node congestion, though it is a program-based simulation at the same time, it interacts in-depth with active components like Patient and Cloud Data Storage to channelize SERVICE REQUEST. It also actively participates in resource monitoring and sharing under real-life scenario. “Simpy” can be used in Python-based Open-Source platform by typing instructions, i.e. “PIP install Simpy” in Anaconda prompt. Simpy library contains discrete event functional parameters to assist simulation. As shown in Figure 1, multiple SERVICE REQUESTS are generated from patients who should be modeled and simulated using realistic parameters and behaviors. The generator is a term used in Simpy to handle various discrete events. To create any event, “Simpy” allocates a “yield” mechanism, and to suspend or hold any event, it uses timeout () method. To generate any process, Simpy creates an instance as per its environment process method. Here Simpy platform is used to sculpt a resource from its initiation to termination. It demonstrates a basic process interaction between the User (i.e. Patient, in this case) and Cloud Data Storage. Here one Cloud Data Storage is used to store essential information related to SERVICE REQUEST of the Patient, which is generated through the IoT-based terminal sensor devices [3].