Metadata-Version: 2.1
Name: littlebaker
Version: 0.0.1
Summary: Package to auto-generate lists, dictionaries, arrays, matricies (list-of-lists), json, csv files, and Pandas Dataframes
Home-page: https://github.com/MiConnell/littlebaker
Author: Michael Connell
Author-email: connellmp@gmail.com
License: UNKNOWN
Description: # littlebaker
        
        ![littlebaker](https://user-images.githubusercontent.com/14168559/92421136-ebca1a80-f12b-11ea-8f90-c69ade7a659c.png)
        
        littlebaker is your personal Python baker to create custom lists, dictionaries, matricies (lists of lists), [numpy arrays](https://numpy.org/doc/stable/reference/generated/numpy.array.html), csv files, in-memory json blobs, and [Pandas DataFrames](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html).
        
        All it takes is
        
            from littlebaker import littlebaker
        
            baker_list = littlebaker.make.a_list() # returns list
            baker_dict = littlebaker.make.a_dict() # returns dictionary
            baker_matrix = littlebaker.make.a_matrix() # returns a list-of-lists
            baker_array = littlebaker.make.an_array() # returns numpy array
            baker_json = littlebaker.make.some_json() # returns json
            baker_csv = littlebaker.make.a_csv() # creates a csv file
            baker_df = littlebaker.make.a_df() # returns Pandas DataFrame
        
        ## Installation
        
        simply install littlebaker via pip `pip install littelbaker`
        
        ## Examples and Usage
        
        ### littlebaker.make.a_list(length, data_type)
        
            length=
                any integer greater than 0, specifies list length, defaults to 101
            data_type=
                specifies the type of values in the returned list, defaults to `int`. Valid options are
                    int: returns a list of integers
                    float: returns a list of floats
                    char: returns a list of single str characters
                    date: returns a list of dates
                    str: returns a list of random strings
        
        ### littlebaker.make.a_dict(length, value_type)
        
            length=
                any integer greater than 0, specifies dictionary length, defaults to 101
            value_type=
                specifies the type returned in the value of the dictionary's key:value pair, defaults to char.
                valid options are:
                    int: returns a dictionary with keys of integers and values of integers
                    float: returns a dictionary with keys of integers and values of floats
                    char: returns a dictionary with keys of integers and values of single str characters
                    date: returns a dictionary with keys of integers and values of dates
                    str: returns a dictionary with keys of integers and values of random strings
        
        ### littlebaker.make.a_matrix(num_lists, list_length, value_type)
        
            num_lists=
                positive integer, specifies the number of lists within the returned matrix, defaults to 5
            list_length=
                positive integer, specifies the lentgh of the inner lists, defaults to 5
            value_type=
                specity the type returned in the inner lists, defaults to all
                int: returns inner lists of integers
                float: returns inner lists of floats
                char: returns inner lists of single str characters
                date: returns inner lists of dates
                str: returns inner lists of random strings
                all: returns inner lists of all of the above options. With this option, `num_lists` must be 5
        
        ### littlebaker.make.an_array(matrix)
        
            matrix=
                matrix to use to create the array, defaults to the default values in `littlebaker.make.a_matrix()`
                must be of type `List[list]`
        
        ### littlebaker.make.some_json(value_length)
        
            value_length=
                positive integer, specifies the length of the values returned in the resulting json, defaults to 5
        
        ### littlebaker.make.a_df(n)
        
            n=
                positive integer for the number of rows desired in the DataFrame, defaults to 100
        
        ### littlebaker.make.a_csv(path, filename, rows, df, index)
        
            path=
                filepath to desired save location, defaults to the current `.py` file's directory
            filename=
                desired name of file, defaults to `littlebaker.csv`
            rows=
                positive integer to specity number of rows desired in the csv file, defaults to 100
            df=
                Pandas DataFrame to be written to csv, defaults to `littlebaker.make.a_df()`
            index=
                boolean to specify if an index is desired in the resulting csv
        
        **littlebaker can also generate dates for you with `littlebaker.date_generator()`**
        
        ## date_generator(num_dates, start_year, end_year, as_list)
        
            num_dates=
                positive integer to specify the number of dates desired to be returned, defaults to 1
            start_year=
                positive integer for the beginning year of the random date(s) to be returned, defaults 1950
            end_year=
                positive integer for the end year of the random date(s) to be returned, defaults to the current year
            as_list=
                boolean to specify if the date(s) returned should be in list form or as individual newline separated dates, defaults to False
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
