Metadata-Version: 2.1
Name: PyProtolinc
Version: 0.1.4
Summary: Projection Tool for Life Insurance Cash Flows
Home-page: https://github.com/mseehafer/PyProtolinc
Author: Martin Seehafer
License: MIT
Keywords: actuarial,projection,life,insurance
Requires-Python: >=3.6
Provides-Extra: DOC
License-File: LICENSE


About PyProtolinc
=======================================================================

An Extensible Projection Tool for Life Insurance Cash Flows.
-------------------------------------------------------------
This package allows to project future cash flows for portfolios of life insurance 
policies. It comes with a number of built-in standard products but can also be used
to project custom products by the user. 


Documentation
^^^^^^^^^^^^^^^^

For extended documentation cf. https://pyprotolinc.readthedocs.io/en/latest/index.html.


Project Objectives
----------------------

The key objective for *PyProtolinc* is to model cash flows for a variety of simple life and health insurance
products, going forward also beyond stylized textbook examples.

The tool should provide a command line interface which can be used with configuration files as well as an extensible
programming API which provides flexibility to adapt to own purposes.

Calculations should be laid out to deal with portfolios of insureds in a batch style and an attempt shall be made
that forecast projections for reasonably large portfolios (of, say, a few 10s or 100s of thousands of policies)
can be made in an acceptable amount of time (seconds or up to a few minutes rather than hours).


Basic Usage
----------------

Installation
^^^^^^^^^^^^^^^^


To install from PyPI run::

  pip install pyprotolinc

Alternatively, or for delevoplement clone (or download) the repository from https://github.com/mseehafer/PyProtolinc.git and
run::

  pip install -e .

from the root directory of the repository.

Quickstart
^^^^^^^^^^^^^^^^

Usage is illustrated in detail by the prepared use cases in the *examples* folder. To try those out *cd* into the respective
subfolder and run the tool from the command line::

  pyprotolinc run

This will pick up the configuration file (*config.yml*) in the working directory (which points to the portfolio file
in the subdirectory *portfolio*) and initiate a projection run. Once completed the (aggregate) results of the computation
are written into a CSV file in the subfolder *results*. To view these copy the Excel file *results_viewer_generic_template.xlsx*
from the examples folder into the working folder, rename it to *results_viewer_generic.xlsx*
and import the data from the CSV file. Now one can start playing around by changing the configuration. Note that the examples
are commented in the documentation, cf. https://pyprotolinc.readthedocs.io/en/latest/examples/intro.html .



Copyright (c) 2022 Martin Seehafer

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
