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bms-tree-modules-0.2.1
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مشاهده بیشترتوضیحات
The package contains the generic building blocks for the period-based Banking Management Simulation Games developed by the Institue of Banking & Finance (University of Zurich, Switerland).
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | bms-tree-modules-0.2.1 |
| نام | bms-tree-modules |
| نسخه کتابخانه | 0.2.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Moritz Eck |
| ایمیل نویسنده | moritz.eck@gmail.com |
| آدرس صفحه اصلی | https://gitlab.uzh.ch/uzh-bf/sim/banking-game-2020 |
| آدرس اینترنتی | https://pypi.org/project/bms-tree-modules/ |
| مجوز | MIT |
# bms-tree-modules
The package contains the generic building blocks for the period-based Banking Management Simulation Games developed by the Institue of Banking & Finance (University of Zurich, Switerland).
The package delivers the game building blocks: Node, Tree, Team, Config, Curves, Module.
These classes can be used to implement a simulation without having to setup the complete tree data structure logic from scratch.
The implementation can extend the class `Module` which takes JSON as input and allows to create a tree data structure recursively from it.
All manipulations of the tree should be implemented in the actual implementation/simulation class.
This package has been created as part of the Banking Management Simulation Game (BMS20) project at the Institue of Banking & Finance and Institute of Informatics (University of Zurich).
## Requirements
- Python 3.8
- pip
- pipenv
## Using the Library (in a Simulation)
### Installation
Run `pipenv install bms-tree-modules` or `pip install bms-tree-modules` to install the package.
### How to create a new simulation?
Create a new file in which you're going to implement the logic of the simulation.
```python
from bms-tree-modules.module import Module
class SimulationClassName(Module):
def __init__(self, period_input):
super().__init__(period_input)
with open("/path/to/json_input.json", "r") as file:
# read file and load json string as dict
period_input = json.loads(file.read())
# create new simulation
sim = SimulationClassName(period_input)
```
### JSON input format requriements
The Module class requires the `period_input` to be JSON and in the following format.
All parts described separately below need to be in the same input file.
#### Curve Configuration
```json
{
"curve_assignments": [
{
// key how the curve shall be retrievable in your code
"curve_slot_key": "KEY_USED_INTERNALLY_TO_RETRIEVE_THE_CURVE",
"curve_assigned": {
// The coefficients of the sensitivity curve
// The curve will be create as a lambda function
"coefficients": [0.12, 7.5, 200.0],
}
},
```
#### Team Input
For every team taking part in the period-based simulation, the `teams` array needs to contain a separate entry.
```json
"teams": [
{
"team_id": 0,
"decisions": [
// the decisions the teams made
{ "key": "LOANS_MARK_UP_RATING_A", "value": 0.01 },
],
"tree_input": {
"name": "root",
"value": 0,
"description": "Team0_RoundInput_PeriodTimestamp?",
"children": [
{
"name": "BS",
"description": "The Balance Sheet",
"value": 0,
"children": [
{
```
##### Team Object
Every team object consists of:
- team_id: int
- decisions: List of Decision Objects
- tree_input: Node Object (root node)
##### Decision Object
Every decision objects consists of:
- key: string
- value: float
The keys must be the same across all teams and each team must contain all keys that exist.
##### Node Object
Every object inside the `tree_input` is a Node object which needs to contain the following:
- name: string
- value: float
- description: string
- children: List of other child nodes (or empty)
#### Leaf Node Configuration Values
For at least all leaf-nodes (nodes which don't have childern i.e. an empty children array), a node configuration object needs to be provided.
##### What is an effect?
An effect is a factor which influences how the value of a leaf-node is changed from state `t0` to state `t1` (i.e. the change from one period to the next).
A leaf-node can have many different effects.
The results of all effects are summed and added/subtracted from the leaf-nodes input value -> new value.
Each effect can have multiple configuration values -> these values are the same for all teams.
An example of a configuration value is the `CURVE` mapping which tells the simulation which sensitivity curve to use during the computation of the new effect value.
Others are, `MIN` (lower-limit), `MAX` (upper-limit), `WEIGHT` (contribution factor) which need to be considered when computing the effects value.
```json
"config": [
{
"name": "BS_ACT_LOANS_RATING_A",
"description": "Description of the configuration values",
"effects": [
{
"name": "SERVICE_QUALITY",
"values": [
{
"key": "MIN",
"value": 0.0
},
{
"key": "MAX",
"value": 0.1
},
{
"key": "WEIGHT",
"value": 0.5
},
{
"key": "CURVE",
"value": "SERVICE_QUALITY_ASSET_SIDE"
}
]
}
]
},
```
## Developing the Library
For developers wanting to extend this work, the following parts might give some insights.
### Installation Instructions
Run `pipenv install --dev` to install all dependencies
Run `pipenv shell` to enter the virtualenv created by pipenv for this project.
PS: if the installation doesn't work use `--pre` since some packages might only be in pre-release state.
### How to build a new release?
Make sure you're inside the previously created pipenv.
#### Create the build (package)
Run `python3 setup.py sdist bdist_wheel` which creates a `dist/` and `build` folder.
#### Upload the package
Run `python3 -m twine upload dist/*` to upload to the PyPi repository.
In order for the upload to work, you need to create an API token to access PyPi.
Use `__token__` for username and `pypi-...` as password.
PS: the credentails can also be stored inside a `$HOME/.pypirc` file.
```
[pypi]
username = __token__
password = pypi-...
```
#### Official Documentation
For more information have a look at the offical documentation: https://packaging.python.org/tutorials/packaging-projects/
## Changelog
The following sections documents the changes across the different versions.
#### 📦 v0.2.1
✨ New Feature
- add: helper field to Decision _(allows to hide internal helper decisions when returning state to dict)_
#### 📦 v0.2.0
✨ New Feature & Breaking Change
- Decisions are no longer key:value pairs
- New Class Decisions & Decision _(replaces decisions \<dict> in Team with List[Decision])_
#### 📦 v0.1.4
✨ New Feature
- add decisions to Team `to_dict()` function _(to be able to pass it back in ResponseDTO)_
#### 📦 v0.1.3
🐛 Bug Fix
- a team can be retrieved by its team_id _(not the index in the teams list)_
#### 📦 v0.1.2
- update README & package description
#### 📦 v0.1.1
- initial package creation
نیازمندی
| مقدار | نام |
|---|---|
| - | typing |
| - | pylama |
| - | black |
| - | flake8 |
| - | pytest |
| - | pytest-watch |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl bms-tree-modules-0.2.1:
pip install bms-tree-modules-0.2.1.whl
نصب پکیج tar.gz bms-tree-modules-0.2.1:
pip install bms-tree-modules-0.2.1.tar.gz