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, 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