The oasislmf
Python package, loosely called the model development kit (MDK) or the MDK package, provides a command line interface and reusable libraries primarly for developing and running Oasis models end-to-end locally, or remotely via the Oasis API, for the purpose of generating group-up losses (GUL), direct/insured losses (IL) and reinsurance losses (RIL). The package also provides end users with a way to generate deterministic losses at all levels, GUL, IL or RIL.
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 supportsmodel generate-oasis-files
: generates the Oasis input CSV files for losses (GUL, GUL + IL, or GUL + IL + RIL); it requires the provision of source exposure and optionally source accounts and reinsurance info. and scope files (in OED format), as well as assets for instantiating model lookups and generating keys filesmodel generate-losses
: generates losses (GUL, or GUL + IL, or GUL + IL + RIL) from a set of pre-existing Oasis filesmodel run
: runs the model from start to finish by generating losses (GUL, or GUL + IL, or GUL + IL + RIL) from the source exposure, and optionally source accounts and reinsurance info. and scope files (in OED or RMS format), as well as assets for instantiating model lookups and generating keys files
For remote model execution the api
subcommand provides the following main subcommand:
api run
: runs the model remotely (same asmodel run
) but via the Oasis API
For generating deterministic losses (GUL, or GUL + IL, or GUL + IL + RIL) the CLI provides an exposure run
subcommand.
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
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
The package provides a built-in lookup framework (oasislmf.model_preparation.lookup.OasisLookup
) 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
.
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
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.
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
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.
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
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
The code in this project is licensed under BSD 3-clause license.