# corebridge
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
This package provides functions and classes to run wodan style
processing functions in the Stactics AICore environment.
## Installation
Use
``` sh
pip install corebridge
```
to install corebrdige.
## How to use
### Introduction
Wodan is a proprietary backend service that applies high performance,
custom analytical processing to timeseries data in the Whysor data and
dashboarding environment.
Each wodan module defines one function that operates as the entry point.
The parameter annotations in this function definition are used to format
data and retrieve parameters from the originating call to the wodan api.
This function is called with data retrieved according to a specification
and with additional parameters as annotated.
A simple function might look like:
``` {python}
import numpy as np
def multiply(data:np.ndarray, multiplier:float=1.0):
return data * multiplier
```
Wodan binds this function to a service endpoint and takes care of
fetching data and parameters and converting the result for the caller.
### AICore modules
For AICore users define a class, always named `CustomModule` with a
constructor `__init__` and a method `infer`.
This package defines a baseclass to quickly construct a `CustomModule`
class that is able to use a wodan processor function inside the AICore
system:
``` {python}
import numpy as np
import corebridge
def multiply(data:np.ndarray, multiplier:float=1.0):
return data * multiplier
class CustomModule(corebridge.aicorebridge.AICoreModule):
def __init__(self, save_dir, assets_dir, *args, **kwargs):
super().__init__(multiply, save_dir, assets_dir, *args, **kwargs)
```
That’s it. Well, you can add parameters to `__init__` that can be used
as hyperparameters in the web-interface and you could override `infer`
for the same reason. The baseclass takes care of converting call
parameters and data to the function specification and, calls the
function and converts the result for the caller, similar to the original
Wodan service.
## Development
### NBDev
This library is developed with [NBDev](https://nbdev.fast.ai/) - a
literate programming toolkit that supports developing code using jupyter
notebooks and mix code with documentation.
Literate programming is a methodology - introduced in 1984 by Donald
Knuth - that combines a programming language with a documentation
language. In this approach, a program is explained in a human language
(such as English) alongside code snippets. The literate source file is
then processed by a preprocessor to produce both source code and
formatted documentation.
This paradigm enhances program robustness, portability, and
maintainability, making it a valuable tool in scientific computing and
data science[^1]
### Quarto
Documentation is prepared from the notebook with
[Quarto](https://quarto.org/). Quarto too combines code with
documentation but it does not extract source code into modules like
nbdev.
### Installation
#### Quarto
Quarto uses Pandoc and, for pdf format, LaTeX. These must be available
on your system.
Install [Quarto](https://quarto.org/docs/get-started/) as you see fit,
there is a [VSCode
extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto)
which handles this.
#### NBDev
NBDev is available as PyPi package and is installed with
pip install nbdev
or if you are using conda
conda install -c fastai -y nbdev
If so desired you can let NBDev install Quarto with
nbdev_install_quarto
But this ask for the system admin password.
### Local editing & testing
Setup a virtual environment, activate it and install the development
package and dependencies with, on linux
pip install -e ‘.[dev]’
or on Windows
pip install -e .[dev]
#### Jupyter
The above pip install should also install jupyter but to use it the
kernel needs to be installed with:
python -m ipykernel install --user --name=corebridge.venv
### nbdev cycle
- edit
- nbdev_prepare
The latter performs - nbdev_export - nbdev_test - nbdev_clean -
nbdev_readme
Then commit and to upload to Pypi with `nbdev_pypi`
[^1]: [Wikipedia on ‘Literate
Programming’](https://en.wikipedia.org/wiki/Literate_programming)
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