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"description": "![\"Oasis](\"https://oasislmf.org/packages/oasis_theme_package/themes/oasis_theme/assets/src/oasis-lmf-colour.png\")
\n\n[](https://github.com/OasisLMF/ktools/releases) [](https://badge.fury.io/py/oasislmf) [](https://ci.oasislmfdev.org/job/oasis_oasislmf/job/master/)\n\n# OasisLMF\n\nThe `oasislmf` Python package, loosely called the *model development kit (MDK)* or the *MDK package*, provides a command line toolkit for developing, testing and running Oasis models end-to-end locally, or remotely via the Oasis API. It can generate ground-up losses (GUL), direct/insured losses (IL) and reinsurance losses (RIL). It can also generate deterministic losses at all these levels.\n\n## Features\n\nFor running models locally the CLI provides a `model` subcommand with the following options:\n\n* `model generate-keys`: generates Oasis keys files from model lookups; 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; if the lookup is for a complex/custom model the keys file will have the same format except that area peril ID and vulnerability ID are replaced by a model data JSON string\n* `model 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 files\n* `model generate-losses`: generates losses (GUL, or GUL + IL, or GUL + IL + RIL) from a set of pre-existing Oasis files\n* `model 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 related to lookup instantiation and keys file generation\n\nThe optional `--summarise-exposure` flag can be issued with `model generate-oasis-files` and `model run` to generate a summary of Total Insured Values (TIVs) grouped by coverage type and peril. This produces the `exposure_summary_report.json` file.\n\nFor remote model execution the `api` subcommand provides the following main subcommand:\n\n* `api run`: runs the model remotely (same as `model run`) but via the Oasis API\n\nFor generating deterministic losses an `exposure run` subcommand is available:\n\n* `exposure run`: generates deterministic losses (GUL, or GUL + IL, or GUL + IL + RIL)\n\nThe reusable libraries are organised into several sub-packages, the most relevant of which from a model developer or user's perspective are:\n\n* `api_client`\n* `model_preparation`\n* `model_execution`\n* `utils`\n\n## Minimum Python Requirements\n\nStarting from 1st January 2019, Pandas will no longer be supporting Python 2. As Pandas is a key dependency of the MDK we are **dropping Python 2 (2.7) support** as of this release (1.3.4). The last version which still supports Python 2.7 is version `1.3.3` (published 12/03/2019).\n\nAlso for this release (and all future releases) a **minimum of Python 3.6 is required**.\n\n\n## Installation\n\nThe latest released version of the package, or a specific package version, can be installed using `pip`:\n\n pip install oasislmf[==]\n\nAlternatively you can install the latest development version using:\n\n pip install git+{https,ssh}://git@github.com/OasisLMF/OasisLMF\n\nYou can also install from a specific branch `` using:\n\n pip install [-v] git+{https,ssh}://git@github.com/OasisLMF/OasisLMF.git@#egg=oasislmf\n\n## Enable Bash completion\n\nBash completion is a functionality which bash helps users type their commands by presenting possible options when users press the tab key while typing a command.\n\nOnce oasislmf is installed you'll need to be activate the feature by sourcing a bash file. (only needs to be run once)\n\n### Local \n\n oasislmf admin enable-bash-complete\n\n### Global \n\n echo 'complete -C completer_oasislmf oasislmf' | sudo tee /usr/share/bash-completion/completions/oasislmf\n\n\n## Dependencies\n\n### System\n\nThe 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.\n\nhttps://libspatialindex.github.io/index.html\n\nLinux users can install the development version of `libspatialindex` from the command line using `apt`.\n\n [sudo] apt install -y libspatialindex-dev\n\nand OS X users can do the same via `brew`.\n\n brew install spatialindex\n\nThe 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`.\n\n#### GNU/Linux\n\nFor GNU/Linux the following is a specific list of required system libraries\n\n * **Debian**: g++ compiler build-essential, libtool, zlib1g-dev autoconf on debian distros\n\n sudo apt install g++ build-essential libtool zlib1g-dev autoconf\n\n\n * **Red Hat**: 'Development Tools' and zlib-devel\n\n### Python\n\nPackage Python dependencies are controlled by `pip-tools`. To install the development dependencies first, install `pip-tools` using:\n\n pip install pip-tools\n\nand run:\n\n pip-sync\n\nTo add new dependencies to the development requirements add the package name to `requirements.in` or\nto add a new dependency to the installed package add the package name to `requirements-package.in`.\nVersion specifiers can be supplied to the packages but these should be kept as loose as possible so that\nall packages can be easily updated and there will be fewer conflict when installing.\n\nAfter adding packages to either `*.in` file:\n\n pip-compile && pip-sync\n\nshould be ran ensuring the development dependencies are kept up to date.\n\n## Testing\n\nTo test the code style run:\n\n flake8\n\nTo test against all supported python versions run:\n\n tox\n\nTo test against your currently installed version of python run:\n\n py.test\n\nTo run the full test suite run:\n\n ./runtests.sh\n\n## Publishing\n\nBefore 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.\n\n### Using the `publish` subcommand in `setup.py`\n\nThe distribution format can be either a source distribution or a platform-specific wheel. To publish the source distribution package run:\n\n python setup.py publish --sdist\n\nor to publish the platform specific wheel run:\n\n python setup.py publish --wheel\n\n### Creating a bdist for another platform \n\nTo create a distribution for a non-host platform use the `--plat-name` flag:\n\n python setup.py bdist_wheel --plat-name Linux_x86_64\n\n or\n\n python setup.py bdist_wheel --plat-name Darwin_x86_64\n\n\n### Manually publishing, with a GPG signature\n\nThe first step is to create the distribution package with the desired format: for the source distribution run:\n\n python setup.py sdist\n\nwhich will create a `.tar.gz` file in the `dist` subfolder, or for the platform specific wheel run:\n\n python setup.py bdist_wheel\n\nwhich will create `.whl` file in the `dist` subfolder. To attach a GPG signature using your default private key you can then run:\n\n gpg --detach-sign -a dist/.{tar.gz,whl}\n\nThis will create `.asc` signature file named `.{tar.gz,whl}.asc` in `dist`. You can just publish the package with the signature using:\n\n twine upload dist/.{tar.gz,whl} dist/.{tar.gz,whl}.asc\n \n## Documentation\n* Issues\n* Releases\n* General Oasis documentation\n* Model Development Kit (MDK)\n* Modules\n\n## License\nThe code in this project is licensed under BSD 3-clause license.",
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