StreamPort

Platform for multivariate data Analyses, sensor networks and pipelines and device condition monitoring and diagnostics.

Setup

The streamPort is an experimental project under development. Below, we instruct you on how to setup a development environment. Note that certain packages included with this release require Chrome or any chromium-based browser to enable smooth function. Install Chrome via https://www.google.com/chrome/.

On Windows

• Install Python version 3.12 or above;
• Verify if the correct version is installed using python --version (it should be above 3.12);
• If you cannot detect python, add the path to the environment variables following https://realpython.com/add-python-to-path/;
• Check and note the python installation path with (Get-Command python).Path;
• Update pip with python -m pip install --upgrade pip;
• Check if pip version is 24 or above with pip --version and verify that the python path is a parent of the pip lib folder;
• If not already installed, install virtualenv with pip install virtualenv;
• You can run pip list to check if the virtualenv is installed;
• Clone the repository locally;
• From the local repository folder, start a virtual environment using python -m venv env (you can change env to another name of your preference);
• Then activate the virtual environment with env/Scripts/activate.bat, where env should be the name of the virtual environment you defined;
• Once the virtual environment is activated, you can install the required libraries with pip install -r requirements.txt;
• For example workflows using Jupyter Notebooks, see the notebooks directory.
• For the Jupyter Notebooks, you can select the kernel from the virtual environment;
• Run the dev_core.ipynb for testing the setup;

Streamlit App

• Install Streamlit version 1.48.1 or above (included in requirements);
• Configure the page layout/design by editing the .streamlit/config.toml file;
• From the root directory, make all modules in the current path discoverable by setting PYTHONPATH:;

CMD

• set PYTHONPATH=.;
• Run app using streamlit run src/StreamPort/app/Home.py;

Build Library

• The build package is required to build the libraries. It can be installed with the command pip install build;
• The library can be built by first navigating to the root directory StreamPort and then running py -m build, which creates the dist directory containing the .whl and .tar.gz files for installation;

Package Installation

• The StreamPort package can be installed by first navigating to the dist directory using cd dist;
• Then, to install the package, run pip install streamport-0.0.1-py3-none-any.whl, or the .whl file that is created on build;
• To install and make source code editable, run from root directory pip install -e .;
• Now the StreamPort package can be imported using import StreamPort, and all its public classes can now be used using from StreamPort import *, where * includes device and machine_learning;
• Your first Device Analysis class object can be created using pc = StreamPort.device.analyses.PressureCurvesAnalyses(<files>) or ms = StreamPort.device.analyses.MassSpecAnalyses(<files>), where files is the file or list of files to be analyzed, and similarly for Machine Learning Analysis or Methods and so on (see notebooks directory for example usages);

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