'Item_Weight',

'Item_Fat_Content',

'Item_Visibility',

'Item_Type',

'Item_MRP',

'Outlet_Identifier',

'Outlet_Establishment_Year',

'Outlet_Size',

'Outlet_Location_Type',

'Outlet_Type',

'Item_Outlet_Sales'

"Item_Identifier": "string",

"Item_Weight": "float",

"Item_Fat_Content": "string",

"Item_Visibility": "float",

"Item_Type": "string",

"Item_MRP": "float",

"Outlet_Identifier": "string",

"Outlet_Establishment_Year": "int",

"Outlet_Size": "string",

"Outlet_Location_Type": "string",

"Outlet_Type": "string",

"Item_Outlet_Sales": "float",

def validate(self, document):

text = document.text

if not text:

raise ValidationError(

message='Please fill the value. Press TAB for completion',

def validate(self, document):

text = document.text

if text and not text.isdigit():

i = 0

# Get index of fist non numeric character.

# We want to move the cursor here.

for i, c in enumerate(text):

if not c.isdigit():

break

raise ValidationError(

message='This input contains non-numeric characters',

def validate(self, document):

text = document.text

try:

float(text)

validity = True

except ValueError:

validity = False

if not validity:

i = 0

for i, c in enumerate(text):

has_one_dot = False

if c == '.' and not has_one_dot:

has_one_dot = True

elif not c.isdigit():

break

raise ValidationError(

message='This input contains non-numeric characters',

Token.Toolbar: '#ffffff bg:#333333',

Token.Feature: '#FFFFFF',

Token.DType: '#D95040',

Token.Colon: '#FFFFFF',

Token.Default: '#828282',

dtype = dtypes[feature]

ft = feature.replace("_", " ")

validators = {

'string': StringValidator,

'float': FloatValidator,

'int': NumberValidator,

}

parser = {

'string': str,

'float': float,

'int': int,

}

dict_completer = None

if dtype == 'string':

dict_completer = WordCompleter(content)

selected_validator = validators[dtype]

selected_parser = parser[dtype]

default_value = None

if dtype == 'string':

default_value = content[0]

elif dtype == 'int' or dtype == 'float':

default_value = (content["max"] - content["min"] / 2) + content["min"]

default_value = str(int(default_value))

def get_bottom_toolbar_tokens(cli):

selected_toolbar_text = "Whoa?! Please restart"

if dtype == 'string':

selected_toolbar_text = 'Press TAB for completion.'

elif dtype == 'int' or dtype == 'float':

selected_toolbar_text = 'Our data said that maximum is {} and minimum is {}'.format(

content["max"], content["min"])

return [(Token.Toolbar,

selected_toolbar_text)]

def get_prompt_tokens(cli):

return [

(Token.Feature, "{} ".format(ft)),

(Token.DType, "| {}".format(dtype)),

(Token.Colon, ': '),

(Token.Default, "({}) ".format(default_value)),

]

query[feature] = selected_parser(

prompt(

get_prompt_tokens=get_prompt_tokens,

validator=selected_validator(),

default=default_value,

get_bottom_toolbar_tokens=get_bottom_toolbar_tokens,

completer=dict_completer,

mouse_support=True,