<img src="https://oasislmf.org/packages/oasis_theme_package/themes/oasis_theme/assets/src/oasis-lmf-colour.png" alt="Oasis LMF logo" width="250"/>
[](https://github.com/OasisLMF/ktools/releases)
[](https://badge.fury.io/py/oasislmf)
[](https://colab.research.google.com/github/OasisLMF/OasisLMF/blob/main/fm_testing_tool/FmTesting.ipynb)
[](https://github.com/OasisLMF/OasisLMF/actions/workflows/unittest.yml)
[](https://github.com/OasisLMF/OasisLMF/actions/workflows/code-quality.yml)
[](https://github.com/OasisLMF/OasisLMF/actions/workflows/piwind-test.yml)
[](https://github.com/OasisLMF/OasisLMF/actions/workflows/piwind-mdk.yml)
# OasisLMF
The `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.
## Versioning and Updates
### Current Stable Versions (Actively Supported)
* `1.28.x` [stable/1.28.x](https://github.com/OasisLMF/OasisLMF/tree/stable/1.28.x) From 2023
* `2.3.x` [stable/2.3.x](https://github.com/OasisLMF/OasisLMF/tree/stable/2.3.x) From 2024
* `2.4.x` [stable/2.4.x](https://github.com/OasisLMF/OasisLMF/tree/stable/2.4.x) From 2025
### Release Schedule
Starting in 2023, we transitioned to a yearly release cycle for our stable versions. At the start of Each year, we release a new stable version with an increased **minor** version number `{major}.{minor}.{patch}`.
That version of oaisislmf is then 'frozen' into a branch matching the new version number, so for release `{major}.{minor}.0` the code base is copied to a branch matching the version `stable/{major}.{minor}.x`, there are where backported features and fixes are applied.
In general, we aim to maintain consistent output numbers within each stable version. (excluding bugs like output errors)
#### Monthly Stable Updates
Each month we provide updates to the last three stable version(s) which are viewed as 'actively maintaining'.
So bug fixes will be backport and applied, where possible, without being asked.
Older versions can be updated, but on an on request basis.
When a stable version has a monthly update release its **patch** version number is incremented, so from `{major}.{minor}.{n}` to `{major}.{minor}.{n + 1}`.
## Features
For running models locally the CLI provides a `model` subcommand with the following options:
* `model generate-exposure-pre-analysis`: generate new Exposure input using user custom code (ex: geo-coding, exposure enhancement, or dis-aggregation...)
* `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
* `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
* `model generate-losses`: generates losses (GUL, or GUL + IL, or GUL + IL + RIL) from a set of pre-existing Oasis files
* `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
The 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.
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
For generating deterministic losses an `exposure run` subcommand is available:
* `exposure run`: generates deterministic losses (GUL, or GUL + IL, or GUL + IL + RIL)
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`
## Minimum Python Requirements
Starting 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).
Also for this release (and all future releases) a **minimum of Python 3.8 is required**.
## Installation
The latest released version of the package, or a specific package version, can be installed using `pip`:
pip install oasislmf[==<version string>]
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
## Enable Bash completion
Bash 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.
Once oasislmf is installed you'll need to be activate the feature by sourcing a bash file. (only needs to be run once)
### Local
oasislmf admin enable-bash-complete
### Global
echo 'complete -C completer_oasislmf oasislmf' | sudo tee /usr/share/bash-completion/completions/oasislmf
## Dependencies
### System
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
Linux users can install the development version of `libspatialindex` from the command line using `apt`.
[sudo] apt install -y libspatialindex-dev
and OS X users can do the same via `brew`.
brew install spatialindex
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
* **Debian**: g++ compiler build-essential, libtool, zlib1g-dev autoconf on debian distros
sudo apt install g++ build-essential libtool zlib1g-dev autoconf
* **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.
### ods_tools
OasisLMF uses the ods_tools package to read exposure files and the setting files
The version compatible with each OasisLMF is manage in the requirement files.
below is the summary:
- OasisLMF 1.23.x or before => no ods_tools
- OasisLMF 1.26.x => use ods_tools 2.3.2
- OasisLMF 1.27.0 => use ods_tools 3.0.0 or later
- OasisLMF 1.27.1 => use ods_tools 3.0.0 or later
- OasisLMF 1.27.2 => use ods_tools 3.0.4 or later
### pandas
Pandas has released its major version number 2 breaking some of the compatibility with the 1st version
Therefore, for all version of OasisLMF <= 1.27.2, the latest supported version for pandas is 1.5.3
Support for pandas 2, starts from version 1.27.3
## 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
### Creating a bdist for another platform
To create a distribution for a non-host platform use the `--plat-name` flag:
python setup.py bdist_wheel --plat-name Linux_x86_64
or
python setup.py bdist_wheel --plat-name Darwin_x86_64
### 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.
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"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\"/>\n\n[](https://github.com/OasisLMF/ktools/releases)\n[](https://badge.fury.io/py/oasislmf)\n[](https://colab.research.google.com/github/OasisLMF/OasisLMF/blob/main/fm_testing_tool/FmTesting.ipynb)\n\n[](https://github.com/OasisLMF/OasisLMF/actions/workflows/unittest.yml)\n[](https://github.com/OasisLMF/OasisLMF/actions/workflows/code-quality.yml)\n[](https://github.com/OasisLMF/OasisLMF/actions/workflows/piwind-test.yml)\n[](https://github.com/OasisLMF/OasisLMF/actions/workflows/piwind-mdk.yml)\n\n\n\n# OasisLMF\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\n## Versioning and Updates\n\n### Current Stable Versions (Actively Supported)\n* `1.28.x` [stable/1.28.x](https://github.com/OasisLMF/OasisLMF/tree/stable/1.28.x) From 2023\n* `2.3.x` [stable/2.3.x](https://github.com/OasisLMF/OasisLMF/tree/stable/2.3.x) From 2024\n* `2.4.x` [stable/2.4.x](https://github.com/OasisLMF/OasisLMF/tree/stable/2.4.x) From 2025\n\n### Release Schedule\nStarting in 2023, we transitioned to a yearly release cycle for our stable versions. At the start of Each year, we release a new stable version with an increased **minor** version number `{major}.{minor}.{patch}`.\nThat version of oaisislmf is then 'frozen' into a branch matching the new version number, so for release `{major}.{minor}.0` the code base is copied to a branch matching the version `stable/{major}.{minor}.x`, there are where backported features and fixes are applied.\nIn general, we aim to maintain consistent output numbers within each stable version. (excluding bugs like output errors)\n\n\n#### Monthly Stable Updates\nEach month we provide updates to the last three stable version(s) which are viewed as 'actively maintaining'.\nSo bug fixes will be backport and applied, where possible, without being asked.\nOlder versions can be updated, but on an on request basis.\n\nWhen a stable version has a monthly update release its **patch** version number is incremented, so from `{major}.{minor}.{n}` to `{major}.{minor}.{n + 1}`.\n\n\n## Features\n\nFor running models locally the CLI provides a `model` subcommand with the following options:\n\n* `model generate-exposure-pre-analysis`: generate new Exposure input using user custom code (ex: geo-coding, exposure enhancement, or dis-aggregation...)\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 3.8 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[==<version string>]\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 `<branch name>` using:\n\n pip install [-v] git+{https,ssh}://git@github.com/OasisLMF/OasisLMF.git@<branch name>#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\n### ods_tools\nOasisLMF uses the ods_tools package to read exposure files and the setting files\nThe version compatible with each OasisLMF is manage in the requirement files.\nbelow is the summary:\n\n- OasisLMF 1.23.x or before => no ods_tools\n- OasisLMF 1.26.x => use ods_tools 2.3.2\n- OasisLMF 1.27.0 => use ods_tools 3.0.0 or later\n- OasisLMF 1.27.1 => use ods_tools 3.0.0 or later\n- OasisLMF 1.27.2 => use ods_tools 3.0.4 or later\n\n### pandas\nPandas has released its major version number 2 breaking some of the compatibility with the 1st version\nTherefore, for all version of OasisLMF <= 1.27.2, the latest supported version for pandas is 1.5.3\nSupport for pandas 2, starts from version 1.27.3\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/<package file name>.{tar.gz,whl}\n\nThis 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:\n\n twine upload dist/<package file name>.{tar.gz,whl} dist/<package file name>.{tar.gz,whl}.asc\n\n## Documentation\n* <a href=\"https://github.com/OasisLMF/OasisLMF/issues\">Issues</a>\n* <a href=\"https://github.com/OasisLMF/OasisLMF/releases\">Releases</a>\n* <a href=\"https://oasislmf.github.io\">General Oasis documentation</a>\n* <a href=\"https://oasislmf.github.io/docs/oasis_mdk.html\">Model Development Kit (MDK)</a>\n* <a href=\"https://oasislmf.github.io/OasisLmf/modules.html\">Modules</a>\n\n## License\nThe code in this project is licensed under BSD 3-clause license.\n\n\n",
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