v3.8.4

CHANGELOG.md

@@ -490,3 +490,8 @@ CHANGELOG
 - docstrings updated.
 - new types added.
 - types in init updated.
+
+3.8.4 (13/06/2022)
+- Manifesto added.
+- special methods redefined.
+- PEP8 alignments.

_manifesto/ABOUT

@@ -0,0 +1 @@
+This is the manifesto folder of the package, providing guidelines for the public.

_manifesto/Manifesto.md

@@ -0,0 +1,15 @@
+![vandal-header](https://raw.githubusercontent.com/dkundih/vandal/master/_logistics/vandal.jpg)
+
+vandal Manifesto
+=====
+
+1. This library, once and for all, belongs to the vandal framework.
+
+2. Vandal framework consists of vandal, duality and logistics libraries and is open for new ideas.
+
+3. Vandal framework follows PEP8 recommendations, but not blindly and unconditionally.
+
+4. Everyone is allowed to contribute to the project and improve it under the conditions set by the LICENSE.
+
+David Kundih
+13.06.2022.

requirements.txt

@@ -1,5 +1,5 @@
 duality >= 4.7.2
-logistics >= 0.0.5
+logistics >= 0.0.6
 colorama
 pandas >= 1.2.3
 numpy >= 1.19.5

setup.py

@@ -54,7 +54,7 @@
   packages = find_packages(),
   install_requires = [
     'duality >= 4.7.2',
-    'logistics >= 0.0.5', 
+    'logistics >= 0.0.6', 
     'colorama',
     'pandas >= 1.2.3',
     'numpy >= 1.19.5',

vandal/__init__.py

@@ -94,7 +94,7 @@
 from logistics.plugins.types import *
 
 # available types.
-__types__ = [
+types = [
     VandalType,
     IntegerType,
     FloatType,
@@ -121,7 +121,7 @@
 ]
 
 # metaclass.
-__metaclass__ = [
+metaclass = [
     'Meta',
 ]
 

vandal/hub/toolkit.py

@@ -53,6 +53,7 @@ def random_value(mean, st_dev, **rounded):
                 random_value = round(random.gauss(mean, st_dev))
         else:
                 random_value = random.gauss(mean, st_dev)
+
         return random_value
 
 # gives random values of mean and standard deviation inputed for the amount of values defined in the pool size, if rounded = 'y', values will be rounded.
@@ -62,20 +63,23 @@ def random_pool(mean, st_dev, pool_size, **rounded):
                 random_pool = [round(random.gauss(mean, st_dev)) for y in range(pool_size)]
         else:
                 random_pool = [random.gauss(mean, st_dev) for y in range(pool_size)]
+
         return random_pool
 
 # splits the data using a split method character.
 def split_values(data, split_method):
         split_values = []
         for i in data:
                 split_values += [i.split(split_method)]
+
         return split_values
 
 # joins the data using a join metod character.
 def join_values(data, join_method):
         join_values = []
         for i in data:
                 join_values += [join_method.join(i)]
+
         return join_values
 
 # replaces a defined value with a desired value.
@@ -86,13 +90,15 @@ def replace_values(data, replaced_value, replacing_value):
         replace_values = []
         for i in replaced_values:
                 replace_values += [replacing_value.join(i)]
+
         return replace_values
 
 # manually sorts data depending on defined array of indexes.
 def list_sort(data, array):
         redefined_data = []
         for d in array:
                 redefined_data += [data[d]]
+
         return redefined_data
 
 # sorts the indicies in a list of values based on the index array defined as [x,x,x].
@@ -109,6 +115,7 @@ def index_sort(data, split_method, index_array):
                 if array_count == array_lenght:
                         break
                 array_count += 1
+
         return remixed_data
 
 # automatically splits all values in a list and sorts them based on the added trigger as lambda x: [x[i], x[i]] and joins them back together.
@@ -120,12 +127,14 @@ def auto_sort(data, split_method, trigger = lambda x: x[0]):
         auto_sort = sorted(split_values, key = trigger)
         for i in auto_sort:
                 merged_final += ['-'.join(i)]
+
         return merged_final
 
 # creates a random password with adjustable lenght (default: length = 8).
 def create_password(length = 8):
         import random
         particles = 'abcdefghijklmnoprstuxwyzqABCDEFGHIJKLMNOPRSTUXWYZQ0123456789'
+
         return ''.join(random.sample(particles, length))
 
 # handles the file extenstion upon import.

vandal/misc/_meta.py

@@ -13,7 +13,7 @@
 
 ]
 __license__ = 'Copyright © 2021-2022 David Kundih. All rights reserved. Licensed under the Apache License, Version 2.0 | For more details about the license and terms of use visit the official vandal documentation linked at https://github.com/dkundih/vandal and https://pypi.org/project/vandal'
-__version__ = '3.8.3'
+__version__ = '3.8.4'
 __documentation__ = 'https://github.com/dkundih/vandal | https://pypi.org/project/vandal'
 __contact__ = 'dakundih@unin.hr | kundihdavid@gmail.com'
 __donate__ = 'https://patreon.com/dkundih | https://buymeacoffee.com/dkundih'

vandal/objects/montecarlo.py

@@ -233,15 +233,13 @@ def get_risk(
         for num_sim in range(risk_sims):
             random_change = random.choice(percent_change)
             index_array = []
-
             index_array += [today_value * (1 + (random_change))]
             data[num_sim] = index_array
 
             for sim in data[num_sim]:
                 if sim < today_value:
                     smaller += [sim]
         NRisk = len(smaller) / num_sim * 100
-
         assert (NRisk < 100), '\nTime sequence and/or number of iterations are too low for the proper risk calculation.'
 
         return str(round(NRisk, 2)) + '%'
@@ -427,7 +425,6 @@ def MCapp():
                 listinput = input('Enter a value: ')
                 listinput = listinput.replace(",", ".")
                 listinput = float(listinput)
-
                 data.append(listinput)
             except:
                 print('')
@@ -449,7 +446,7 @@ def MCapp():
     # simulation parameters and execution.
     simulations = int(input('Enter number of simulations: ') or 100)
     period = int(input('Enter desired period: ') or 50)
-
+    
     MC = MonteCarlo(list_of_values = data, num_sims = simulations, time_seq = period)
     print('')
     executed = MC.execute(filtered = False)
@@ -460,21 +457,18 @@ def MCapp():
 
         if action == 'graph':
             print('')
-
             title = input('Title: ')
             x_axis = input('X axis title:')
             y_axis = input('Y axis title:')
-
             MC.graph(graph_title = title, x_title = x_axis, y_title = y_axis)
 
         if action == 'change':
             print(Fore.YELLOW + '\nSAVE OPTIONS', Fore.RESET)
             print('0 | csv')
             print('1 | xlsx')
             print('2 | json')
-
+            
             file_type = input('\nEnter the number or name of file type: ')
-
             output = MC.get_change()
 
             try:
@@ -500,9 +494,7 @@ def MCapp():
 
         if action == 'risk':
             sample = int(input('Number of iterations to measure risk on: ') or 5000)
-
             executed_risk = MC.get_risk(risk_sims = sample)
-
             print(Fore.YELLOW + '\nRisk for this option is' + Fore.RESET, executed_risk[:-1], Fore.YELLOW + '%.' + Fore.RESET)
 
         if action == 'hist' or action == 'histogram':