Metadata-Version: 2.1
Name: baarutil
Version: 1.0.0
Summary: Utility functions for BAAR developers
Home-page: https://github.com/Allied-Media/baarutil
Author: Zhaoyu Xu, Souvik Roy
Author-email: zhaoyu.xu@alliedmedia.com, souvik.roy@alliedmedia.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/Allied-Media/baarutil/issues
Description: **This Custom Library is specifically created for the developers/useres who use BAAR. Which is a product of Allied Media Inc. (www.alliedmedia.com)**
        
        Author:
        ~~~~~~~
        Souvik Roy	[sroy-2019]
        Zhaoyu (Thomas) Xu	[xuzhaoyu]
        
        Dependencies:
        ~~~~~~~~~~~~~
        pandas==1.0.3 or above
        numpy==1.18.4 or above
        
        
        Additional Info:
        ~~~~~~~~~~~~~~~~
        The string structure that follows is a streamline structure that the developers/users follow throughout an automation workflow designed in BAAR:
        "Column_1__=__abc__$$__Column_2__=__def__::__Column_1__=__hello__$$__Column_2__=__world"
        
        
        Available functions and the examples are listed below:
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        1.	read_convert(string), Output Data Type: list of dictionary
        Attributes:
        	i.	string:	Input String, Data Type = String
        Input:	"Column_1__=__abc__$$__Column_2__=__def__::__Column_1__=__hello__$$__Column_2__=__world"
        Output:	[{"Column_1":"abc", "Column_2":"def"}, {"Column_1":"hello", "Column_2":"world"}]
        
        2.	write_convert(input_list), Output Data Type: string
        Attributes:
        	i.	input_list:	List that contains the Dictionaries of Data, Data Type = List
        Input:	[{"Column_1":"abc", "Column_2":"def"}, {"Column_1":"hello", "Column_2":"world"}]
        Output:	"Column_1__=__abc__$$__Column_2__=__def__::__Column_1__=__hello__$$__Column_2__=__world"
        
        3.	string_to_df(string, rename_cols, drop_dupes), Output Data Type: pandas DataFrame
        Attributes:
        	i.	string:	Input String, Data Type = String
        	ii.	rename_cols:	Dictionary that contains old column names and new column names mapping, Data Type = Dictionary, Default Value = {}
        	iii.drop_dupes:	Drop duplicate rows from the final dataframe, Data Type = Bool, Default Value = False
        Input:	"Column_1__=__abc__$$__Column_2__=__def__::__Column_1__=__hello__$$__Column_2__=__world"
        Output:
        	|	Column_1	|	Column_2
        ---------------------------------
          0	|	abc			|	def
          1	|	hello		|	world
        
        4.	df_to_string(input_df, rename_cols, drop_dupes), Output Data Type: string
        Attributes:
        	i.	input_df:	Input DataFrame, Data Type = pandas DataFrame
        	ii.	rename_cols:	Dictionary that contains old column names and new column names mapping, Data Type = Dictionary, Default Value = {}
        	iii.drop_dupes:	Drop duplicate rows from the final dataframe, Data Type = Bool, Default Value = False
        Input:
        	|	Column_1	|	Column_2
        ---------------------------------
          0	|	abc			|	def
          1	|	hello		|	world
        Output:	"Column_1__=__abc__$$__Column_2__=__def__::__Column_1__=__hello__$$__Column_2__=__world"
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6.8
Description-Content-Type: text/markdown
