Glossary¶
- Anaconda
Python distrubution that makes installing packages like numpy easier for Windows. Includes over 700 packages. For a smaller, more minimal approach, see Miniconda. For more information, see https://www.anaconda.com/.
- Anaconda Prompt
Modified Windows prompt to be used with the Anaconda python distrubution. Reconfigures python paths to point to packages installed via conda
- conda
From https://www.conda.io/docs/:
Conda is an open source package management system and environment management system that runs on Windows, macOS, and Lunix. Conda quickly installs, runs, and updates packages and their dependncies
- CI
Continuous integration. Software we utilize to check that pull requests don’t break the code.
- git
Distributed version control system. Allows us to test and implement new features with ease. For more information, see https://git-scm.com.
- Jupyter notebook
Powerful web application used in this project, for examples and tutorials containing real python code. From https://jupyter.org:
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
- lint
Bits of potentially erroneous code. Can be identified by a linter
- linter
Program that analyzes source code to check for errors, bugs, stylistic issues, and other potential hangups.
- matplotlib
Primary python package for plotting data. Highly customizable and extensible. More information at https://matplotlib.org
- Miniconda
Minimal installer for conda. From https://conda.io:
Miniconda is a small, bootstrap version of Anaconda that only includes conda, Python, the packages they depend on, and a small number of useful packages
- numpy
Widely-used python package that allows multidimensional arrays and linear algebra routines. More information at https://www.numpy.org
- pip
Recommended tool for installing Python packages. More at https://pypi.org/project/pip/
- PyPI
Python package index. Where packages that can easily be fetched and installed via pip can be found. https://pypi.org
- pytest
Fully featured python test runner. More at https://pytest.org/en/latest/
- scipy
Widely-used python package that contains more mathematical support and data structures, such as sparse matrices. Not required for this package, but allows the sparsity of some matrices to be exploited. More information at https://docs.scipy.org/doc/scipy/reference/
- SERPENT
Monte Carlo particle transport code developed at VTT Technical Research Centre of Finland, Ltd [serpent]. Produces output files that can be parsed by this project. More information, including distribution and licensing of
SERPENT
can be found at http://montecarlo.vtt.fi.- twine
Python package for interacting with and uploading packages to PyPI
- yaml
Human-readable format used for configuration files in this project. For more information, see https://pyyaml.org/wiki/PyYAMLDocumentation