Saravanan666/pypi-org huggingface dataset:
Package: model-viewer
TemporalViewerTemporalViewer enables the exploration of temporal distribution of the model outputs in Jupyter Notebooks.DemoIn Jupyter Notebook:importModelViewerimportjson# Open JSON filesf_steps=open('/Users/soniacq/PTG/TemporalViewer/ModelViewer/data/reasoning_check_status.json')f_objects=open('/Users/soniacq/PTG/TemporalViewer/ModelViewer/data/detic_image.json')f_actions=open('/Users/soniacq/PTG/TemporalViewer/ModelViewer/data/egovlp_action_steps.json')f_metadata=open('/Users/soniacq/PTG/TemporalViewer/ModelViewer/data/ngc_0293_13_additional_metadata_v1.json')main_camera_path='/Users/soniacq/PTG/TemporalViewer/ModelViewer/data/ngc_0293_13-main.mp4'# Takes file objects and returns JSON object as dictionariesdata_steps=json.load(f_steps)data_objects=json.load(f_objects)data_actions=json.load(f_actions)data_metadata=json.load(f_metadata)# create a sessionsession_info={'reasoningJSONFile':data_steps,'boundingBoxJSONFile':data_objects,'egovlpActionJSONFile':data_actions,'recordingMetadata':data_metadata,'recordingName':'ngc_0293_13','mainCameraPath':main_camera_path}ModelViewer.plot_datasets_summary(session_info)InstallOption 1: install via pip:pip install model-viewer
Package: modelw-env-manager
Model W — Env ManagerThe goal of the env manager is to help managing the loading of environment
variables and Django settings (although this is not Django-dependent).Typical use is:frommodel_w.env_managerimportEnvManagerwithEnvManager()asenv:SOME_VALUE=env.get('SOME_VALUE',is_yaml=True,default=False)Documentation✨Documentation is there✨
Package: modelwithlog
KF Django Model with LogModel with log for djangoInstallationWith requirements.txtAdd the following line in yourrequirements.txtfile:modelwithlogWith PIP$pipinstallmodelwithlogGetting StartedAllow to create a model with log, adding a log field to the model. This create a log message with the formated datetime and a messageFormat example:
[2019-03-15 03:00:02] My messageOnly must define logger in your modelFor example:

import logging

logger = logging.getLogger(__name__)


class MyModel(ModelWithLog):

    logger = logger

    class Meta:
        verbose_name = _('MyModel')
        verbose_name_plural = _('MyModels')

    my_field = models.<Tipe>
    ....Also, this model allows to define the logger level for that log. This are the differents levels loggersINFOSet log level to InfoDEBUGSet log level to debugWARNINGSet log level to warningERRORSet log level to errorCRITICALSet log level to criticalHow to use itOnly call your level error with yo message errorFor example:
mymodel.info("MY ERROR")