Metadata-Version: 2.1
Name: oasislmf
Version: 1.2.7
Summary: Core loss modelling framework.
Home-page: https://github.com/OasisLMF/oasislmf
Author: Oasis LMF
Author-email: support@oasislmf.org
License: BSD 3-Clause
Description: <img src="https://oasislmf.org/packages/oasis_theme_package/themes/oasis_theme/assets/src/oasis-lmf-colour.png" alt="Oasis LMF logo" width="250"/>
        
        [![PyPI version](https://badge.fury.io/py/oasislmf.svg)](https://badge.fury.io/py/oasislmf)  [![Build](http://ci.oasislmfdev.org/buildStatus/icon?job=oasis_pypi)](http://ci.oasislmfdev.org/blue/organizations/jenkins/oasis_pypi/activity)
        
        # OasisLMF
        
        The `oasislmf` Python package, loosely called the *model development kit (MDK)* or the *MDK package*, provides a command line interface and reusable libraries for developing and running Oasis models end-to-end, locally or remotely via the Oasis API. For running models locally the CLI provides a `model` subcommand with the following main subcommands:
        
        * `model generate-keys`: generates Oasis keys files that model lookups would generate; these are essentially line items of (location ID, peril ID, coverage type ID, area peril ID, vulnerability ID) where peril ID and coverage type ID span the full set of perils and coverage types that the model supports
        * `model generate-oasis-files`: generates the Oasis input CSV files, from which ground up loss (GUL), direct insured losses (IL/FM) and/or reinsurance losses are generated; it requires the provision of source exposure and optionally source accounts and reinsurance info. and scope files (in OED or RMS format), canonical profiles and aggregation profiles that describe the financial terms in "canonical" versions of the source exposure and accounts files, and other model data related assets
        * `model generate-losses`: generates GUL, or GUL + IL, or GUL + IL + RI losses from pre-generated Oasis files
        * `model run`: runs the model from start to finish by generating losses (GUL, or GUL + IL, or GUL + IL + RI) from the source data, canonical and aggregation profiles, and model data.
        
        For remote model execution the `api` subcommand provides the following main subcommand:
        
        * `api run`: runs the model remotely (same as `model run`) but via the Oasis API
        
        The reusable libraries are organised into several sub-packages, the most relevant of which from a model developer or user's perspective are:
        
        * `api_client`
        * `model_preparation`
        * `model_execution`
        * `utils`
        
        ## Installation
        
        The latest released version of the package can be installed using `pip` (or `pip3` if using Python 3):
        
            pip install oasislmf
        
        Alternatively you can install the latest development version using:
        
            pip install git+{https,ssh}://git@github.com/OasisLMF/OasisLMF
        
        You can also install from a specific branch `<branch name>` using:
        
            pip install [-v] git+{https,ssh}://git@github.com/OasisLMF/OasisLMF.git@<branch name>#egg=oasislmf
        
        ## Dependencies
        
        ### System
        
        The package provides a built-in lookup framework (`oasislmf.keys.lookup`) which uses the Rtree Python package, which in turn requires the `libspatialindex` spatial indexing C library.
        
        https://libspatialindex.github.io/index.html
        
        The PiWind demonstration model uses the built-in lookup framework, therefore running PiWind or any model which uses the built-in lookup, requires that you install `libspatialindex`.
        
        #### GNU/Linux
        
        For GNU/Linux the following is a specific list of required system libraries
        
         * unixodbc unixodbc-dev
         * **Debian**: g++ compiler build-essential, libtool, zlib1g-dev autoconf on debian distros
         * **Red Hat**: 'Development Tools' and zlib-devel
        
        ### Python
        
        Package Python dependencies are controlled by `pip-tools`. To install the development dependencies first, install `pip-tools` using:
        
            pip install pip-tools
        
        and run:
        
            pip-sync
        
        To add new dependencies to the development requirements add the package name to `requirements.in` or
        to add a new dependency to the installed package add the package name to `requirements-package.in`.
        Version specifiers can be supplied to the packages but these should be kept as loose as possible so that
        all packages can be easily updated and there will be fewer conflict when installing.
        
        After adding packages to either `*.in` file:
        
            pip-compile && pip-sync
        
        should be ran ensuring the development dependencies are kept up to date.
        
        ## Testing
        
        To test the code style run:
        
            flake8
        
        To test against all supported python versions run:
        
            tox
        
        To test against your currently installed version of python run:
        
            py.test
        
        To run the full test suite run:
        
            ./runtests.sh
        
        ## Publishing
        
        Before publishing the latest version of the package make you sure increment the `__version__` value in `oasislmf/__init__.py`, and commit the change. You'll also need to install the `twine` Python package which `setuptools` uses for publishing packages on PyPI. If publishing wheels then you'll also need to install the `wheel` Python package.
        
        ### Using the `publish` subcommand in `setup.py`
        
        The distribution format can be either a source distribution or a platform-specific wheel. To publish the source distribution package run:
        
            python setup.py publish --sdist
        
        or to publish the platform specific wheel run:
        
            python setup.py publish --wheel
        
        ### Manually publishing, with a GPG signature
        
        The first step is to create the distribution package with the desired format: for the source distribution run:
        
            python setup.py sdist
        
        which will create a `.tar.gz` file in the `dist` subfolder, or for the platform specific wheel run:
        
            python setup.py bdist_wheel
        
        which will create `.whl` file in the `dist` subfolder. To attach a GPG signature using your default private key you can then run:
        
            gpg --detach-sign -a dist/<package file name>.{tar.gz,whl}
        
        This will create `.asc` signature file named `<package file name>.{tar.gz,whl}.asc` in `dist`. You can just publish the package with the signature using:
        
            twine upload dist/<package file name>.{tar.gz,whl} dist/<package file name>.{tar.gz,whl}.asc
            
        ## Documentation
        * <a href="https://github.com/OasisLMF/OasisLMF/issues">Issues</a>
        * <a href="https://github.com/OasisLMF/OasisLMF/releases">Releases</a>
        * <a href="https://oasislmf.github.io">General Oasis documentation</a>
        * <a href="https://oasislmf.github.io/docs/oasis_mdk.html">Model Development Kit (MDK)</a>
        * <a href="https://oasislmf.github.io/OasisLmf/modules.html">Modules</a>
        
        ## License
        The code in this project is licensed under BSD 3-clause license.
        
Keywords: oasis lmf loss modeling framework
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
