version update 0.2.5

.gitignore

@@ -149,3 +149,4 @@ checklink/cookies.txt
 
 # Quarto
 .quarto
+.devenv-corebridge/

README.md

@@ -6,18 +6,20 @@
 This package provides functions and classes to run wodan style
 processing functions in the Stactics AICore environment.
 
-## Install
+## Installation
+
+Use
 
 ``` sh
 pip install corebridge
 ```
 
+to install corebrdige.
+
 ## How to use
 
 ### Introduction
 
-#### Wodan processing functions
-
 Wodan is a proprietary backend service that applies high performance,
 custom analytical processing to timeseries data in the Whysor data and
 dashboarding environment.
@@ -38,13 +40,17 @@ def multiply(data:np.ndarray, multiplier:float=1.0):
     
 ```
 
-#### AICore modules
+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 one defines a class, always named `Module` with a constructor
-`__init__` and a method `infer`.
+For AICore users define a class, always named `Module` with a
+constructor `__init__` and a method `infer`.
 
 This package defines a baseclass to quickly construct a custom `Module`
-class that uses a wodan processor function inside the AICore system:
+class that is able to use a wodan processor function inside the AICore
+system:
 
 ``` {python}
 import numpy as np
@@ -55,23 +61,32 @@ def multiply(data:np.ndarray, multiplier:float=1.0):
 
 class Module(corebridge.aicorebridge.AICoreModule):
     def __init__(self, save_dir, assets_dir, *args, **kwargs):
-        super().__init__(read, 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 and you could override `infer` for the same reason.
+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.
 
-``` python
-```
+## Development
+
+Setup a virtual environment, activate it and install the development
+package and dependencies with, on linux
+
+        pip install -e ‘.\[dev\]’
+
+or on Windows
 
-    2
+        pip install -e .\[dev\]
 
-## nbdev cycle
+### nbdev cycle
 
 - edit
 - nbdev_export
-- pip install -e ‘.\[dev\]’
 - nbdev_test
 - nbdev_clean
 - nbdev_readme

corebridge/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.4"
+__version__ = "0.2.5"

corebridge/core.py

@@ -95,15 +95,17 @@ def timeseries_dataframe_from_datadict(
 
     if orient == 'records':
         df = pd.DataFrame.from_records(data)
-        time_column = [C for C in df.columns if C.lower() in timecolumns][0]
+        time_column = [C for C in df.columns if C in timecolumns][0]
 
     elif orient == 'table':
         time_column = data['schema']['primaryKey'][0]
         df = pd.DataFrame.from_dict(data['data']).set_index(data['schema']['primaryKey'])
         df.index.name = 'time'
+    else:
+        time_column = [C for C in df.columns if C in timecolumns][0]
+
 
-    df.columns = [C.lower() for C in df.columns]
-    time_column = [C for C in df.columns if C in timecolumns][0]
+    df.columns = list(df.columns)
     df[time_column] = pd.to_datetime(df[time_column],utc=True,format='ISO8601')
     df.set_index(time_column, inplace=True)
     #df.index = pd.DatetimeIndex(df.index).round('ms')

settings.ini

@@ -5,7 +5,7 @@
 ### Python library ###
 repo = corebridge
 lib_name = %(repo)s
-version = 0.2.4
+version = 0.2.5
 min_python = 3.7
 license = apache2
 black_formatting = False
@@ -39,5 +39,5 @@ user = fenke
 
 ### Optional ###
 requirements = python-dateutil pytz numpy pandas scipy scikit-learn fastcore twine
-dev_requirements = python-dateutil pytz numpy pyarrow pandas scipy scikit-learn fastcore jupyter ipywidgets jupyterlab>4 jupyter_contrib_nbextensions jupyterlab-git jupyterlab-quarto nbdev aiohttp asyncpg apscheduler twine
+dev_requirements = python-dateutil pytz numpy pyarrow pandas scipy scikit-learn fastcore jupyter ipywidgets jupyterlab>4 jupyter_contrib_nbextensions jupyterlab-git jupyterlab-quarto nbdev aiohttp asyncpg apscheduler twine addroot
 # console_scripts =