semvec/pypi-packages huggingface dataset:
powerbi-push-datasets 0.1a5
Power BI Push Datasets Mgmt
License: MIT
Requires Python: >=3.6
Keywords: PowerBI,Push,Datasets,REST,API,Tabular,Model,ResultSets,StoredProcedure,TabularEditor,metadata,schema,table,workspace,pump,xcopy


powerbi_push_datasets - Power BI Push Datasets Mgmt

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The main class **PushDatasetsMgmt** encapsulates the Power BI REST operations on `Push Datasets <https://docs.microsoft.com/en-us/rest/api/power-bi/pushdatasets>`_
(which allows programmatic access for pushing data into PowerBI) into a few simple methods:

-   ``deploy_dataset`` : Create a pushable dataset (or update the metadata and schema for existing tables) in Power BI Service by a `Tabular Model <https://github.com/otykier/TabularEditor/wiki/Power-BI-Desktop-Integration>`__ (.bim file);
-   ``push_tables`` : Push all `ResultSets of a Stored Procedure <https://github.com/DataBooster/DbWebApi/wiki#http-response>`__ - data for multiple tables into a Power BI Push Dataset;
-   ``truncate_tables`` : Removes all rows from specified (or all) tables in a Power BI Push Dataset;

This module also provides two conversion tools for development-time:

-   ``convert_bim_to_push_dataset`` : Convert a `Tabular Model <https://github.com/otykier/TabularEditor/wiki/Power-BI-Desktop-Integration>`__ (.bim file) into a Push Dataset Model supported by Power BI Service;
-   ``derive_bim_from_resultsets`` : Generate a `Tabular Model <https://github.com/otykier/TabularEditor/wiki/Power-BI-Desktop-Integration>`__ (.bim file) based on `ResultSets of a Stored Procedure (ResultSets) <https://github.com/DataBooster/DbWebApi/wiki#http-response>`__ - data for multiple tables;

For detailed usage, see the practice sample code: https://github.com/DataBooster/PyWebApi/blob/master/Sample/UserApps/PowerBIPusher/db_to_pbi.py

and its product documentation: https://github.com/DataBooster/PyWebApi#powerbi-data-pusher

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| Homepage and documentation: https://github.com/DataBooster/PyWebApi
| Copyright (c) 2020 Abel Cheng
| License: MIT
typo-pypi 0.1.7
experimental approach for an empirical study for my thesis
License: MIT
Requires Python: >=3.6.0

### typo_pypi, experimental methods 

*insert a UML diagram for all classes*  
analizer: forms list from  package managers  
validater: checks typos for any squats or malicious code
server: handles http stuff  
algos: mostly levenshtein delete-insert typo generation

* should back theoretical claims in thesis work
* could be used for a possible API used by a standalone security pypi module 
* a yet pretty slow and naive implementation