https://github.com/iniself/noba
Noba not only backtrader as a quantitative investment platform, but also visualized using bokeh, which can get richer plot effects. Additionally, Noba also provide 'Ioc Container', 'Event System', 'Database Abstraction Layer', 'Pipeline System' and more.
https://github.com/iniself/noba
backtrader bokeh investment-analysis quantitative-finance quantitative-investment quantitative-trading
Last synced: 5 months ago
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Noba not only backtrader as a quantitative investment platform, but also visualized using bokeh, which can get richer plot effects. Additionally, Noba also provide 'Ioc Container', 'Event System', 'Database Abstraction Layer', 'Pipeline System' and more.
- Host: GitHub
- URL: https://github.com/iniself/noba
- Owner: iniself
- License: gpl-3.0
- Created: 2022-04-10T14:57:52.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-04T01:25:12.000Z (over 2 years ago)
- Last Synced: 2025-04-24T00:39:07.341Z (6 months ago)
- Topics: backtrader, bokeh, investment-analysis, quantitative-finance, quantitative-investment, quantitative-trading
- Language: Python
- Homepage:
- Size: 919 KB
- Stars: 94
- Watchers: 2
- Forks: 22
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.EN.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# What is Noba
## Noba means not only backtrader :)
**You can visit noba documentation for more information: [EN(coming soon)](#) | [中文](https://aui.photos/noba-doc/zh/)**
The core of Noba is an `ioc container`, through which you can create `BB` service, which based on [Backtrader](https://www.backtrader.com/)*(one quantitative backtest system)* and [Bokeh](https://bokeh.org/) *(use bokeh as the backend, Backtrader can get richer plot effects)* *\* BB service would like to thank [backtrader_plotting](https://github.com/verybadsoldier/backtrader_plotting) and [btplotting](https://github.com/happydasch/btplotting) for providing the main code for using bokeh as the backend for the backtrader*
```python
from noba import core
bt = core.make('bb')
```
Of course, you can also create your own services based container. Combined with **Pipeline System** and **Event System** (which can be created directly through containers), noba can enable your quantitative projects to work in a more engineering methods
```python
from noba import core
pipline = core.make('pipeline')
cleaned_data = pipline.via("handle").send(raw_data).through([ChangeDataType, RepeatRowData, ExceptionData, MissingData]).then(lambda raw_data:raw_data)
```
```python
from noba import core
event = core.make('event')
db_event = event.hub(['read_database_complete'])
db_event.watch('read_database_complete', lambda data:..., always=True)
...
db_event.fire('read_database_complete')
```
More importantly, Noba can create database service objects (dber) through containers. This is a **Database Abstraction Layer**. Through configuration files(one json file) and unified one set of APIs, you can operate the most common databases
```python
from noba import core
dber = core.make('db')
stocks = db.table('daily').where('Open==3578.73').or_where('High==3652.46').set_index('Date').get_except('OpenInterest')
```
# Getting Started
* Python >= 3.6 is required.
* Suggest using conda to manage virtual environments
## Installation
```bash
pip install noba
# or
pip install git+https://github.com/iniself/noba
```
## Init noba project
```bash
mkdir your_noba_project
cd your_noba_project
noba init
```
## Preparation
Here you can do some project configuration and write your own service provider, and so on. Please refer to the **NOBA documentation** for details
## Write strategy
```bash
vim main.py
```
Only give **Live Mode** example, about **Normal Mode** and **Optstrategy Mode** pls refer to **NOBA documentation**
* Add to cerebro as an analyzer **(Live Mode)**:
```python
from noba import core
...
...
bt = core.make('bb')
cerebro = bt.Cerebro()
cerebro.addstrategy(MyStrategy)
cerebro.adddata(LiveDataStream()) # Note! Data is must Live Data
cerebro.addanalyzer(bt.analyzers.Live, force_plot_legend=True, autostart=True)
cerebro.run()
# cerebro.plot() # do not run this line unless your data is not real-time
```
* If you need to change the default port or share the plotting to public:
```python
cerebro.addanalyzer(bt.analyzers.Live, address="localhost", port=8889)
```
* Note! In Jupyter you can plut to a single browser tab with iplot=False:
```python
cerebro.plot(plot, iplot=False)
```
# Demos
# Contact us
Telegram Channel: [Aui_Say](https://t.me/aui_say)
Discord Server: [Aui and Friends](https://discord.gg/dhp8uzKSfR)
# Sponsoring
If you want to support the development of noba, consider to support this project.
* ETH: 0x0275779f70179748C6fCe1Fe5D7638DfA7e3F986