littlebaker

littlebaker is your personal Python baker to create custom lists, dictionaries, matricies (lists of lists), numpy arrays, csv files, in-memory json blobs, and Pandas DataFrames.

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