pytsp flake8 part 1 before CI introduction

setup.cfg

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length=100
+ignore=E402,E266,F841

source/algorithms/base_algorithm.py

@@ -16,7 +16,7 @@ def update_data(self):
         self.distances = self.compute_distances()
 
     def hav(self, angle):
-        return sin(angle/2)**2
+        return sin(angle / 2)**2
 
     def haversine_distance(self, cityA, cityB):
         coords = (*self.coords[cityA], *self.coords[cityB])
@@ -27,7 +27,7 @@ def haversine_distance(self, cityA, cityB):
         a = self.hav(delta_lat) + cos(lat_cityA) * cos(lat_cityB) * self.hav(delta_lon)
         c = 2 * asin(sqrt(a))
         # approximate radius of the Earth: 6371 km
-        return c*6371
+        return c * 6371
 
     def compute_distances(self):
         self.distances = defaultdict(dict)
@@ -50,7 +50,7 @@ def generate_solution(self):
     def compute_length(self, solution):
         total_length = 0
         for i in range(len(solution)):
-            length = self.distances[solution[i]][solution[(i+1) % len(solution)]]
+            length = self.distances[solution[i]][solution[(i + 1) % len(solution)]]
             total_length += length
         return total_length
 

source/algorithms/genetic_algorithm.py

@@ -1,5 +1,5 @@
-from .local_optimization import *
-from random import randint, random, randrange, sample, shuffle
+from .local_optimization import LocalOptmizationHeuristics
+from random import randint, random, randrange, sample
 
 
 class GeneticAlgorithm(LocalOptmizationHeuristics):
@@ -9,14 +9,14 @@ class GeneticAlgorithm(LocalOptmizationHeuristics):
         'OC': 'order_crossover',
         'MPC': 'maximal_preservative_crossover',
         'PMC': 'partially_mapped_crossover'
-        }
+    }
 
     mutations = {
         'Mutation method': 'swap_mutation',
         'Swap': 'swap_mutation',
         'Insertion': 'insertion_mutation',
         'Displacement': 'displacement_mutation'
-        }
+    }
 
     def __init__(self):
         super().__init__()
@@ -63,9 +63,9 @@ def order_crossover(self, i1, i2):
         return ni1, ni2
 
     def maximal_preservative_crossover(self, i1, i2):
-        c = len(i1)//2
+        c = len(i1) // 2
         r = randrange(self.size + 1)
-        s1, s2 = (i1*2)[r:r+c], (i2*2)[r:r+c]
+        s1, s2 = (i1 * 2)[r:r + c], (i2 * 2)[r:r + c]
         for x in s1:
             i2.remove(x)
         for x in s2:
@@ -89,7 +89,7 @@ def partial_mapping(self, i1, i2, ni1, ni2, a, b):
 
     def partially_mapped_crossover(self, i1, i2):
         a, b = self.crossover_cut()
-        ni1, ni2 = [0]*self.size, [0]*self.size
+        ni1, ni2 = [0] * self.size, [0] * self.size
         ni1[a:b], ni2[a:b] = i1[a:b], i2[a:b]
         self.partial_mapping(i1, i2, ni1, ni2, a, b)
         self.partial_mapping(i2, i1, ni2, ni1, a, b)
@@ -116,7 +116,7 @@ def cycle(self, generation, **data):
         for par in zip(generation[::2], generation[1::2]):
             ng.extend(getattr(self, crossover)(*par) if random() < cr else par)
         # mutation step
-        ng = [getattr(self, mutation)(i) for i in ng]
+        ng = [getattr(self, mutation)(i) if random() < mr else i for i in ng]
         # order the generation according to the fitness value
         ng = sorted(ng, key=self.compute_length)
         return ng, self.format_solution(ng[0]), self.compute_length(ng[0])

source/algorithms/linear_programming.py

@@ -1,8 +1,8 @@
-from .base_algorithm import *
+from .base_algorithm import BaseAlgorithm
 from itertools import chain, combinations
 try:
-    from cvxopt import matrix, glpk, solvers
-    from numpy import concatenate, eye, float, full, ones, vstack, zeros
+    from cvxopt import matrix, glpk
+    from numpy import float, full
 except ImportError:
     import warnings
     warnings.warn('cvxopt/numpy import failed: linear programming will not work')
@@ -27,8 +27,8 @@ def edges_to_tour(self, edges):
         return tour[:-1]
 
     def ILP_solver(self):
-        n, sx = len(self.distances), len(self.distances)*(len(self.distances) - 1)//2
-        c = [float(self.distances[i+1][j+1]) for i in range(n) for j in range(i + 1, n)]
+        n, sx = len(self.distances), len(self.distances) * (len(self.distances) - 1) // 2
+        c = [float(self.distances[i + 1][j + 1]) for i in range(n) for j in range(i + 1, n)]
         G, h, A, b = [], [], [], full(n, 2, dtype=float)
         for st in chain.from_iterable(combinations(range(n), r) for r in range(2, n)):
             G += [[float(i in st and j in st) for i in range(n) for j in range(i + 1, n)]]
@@ -37,9 +37,9 @@ def ILP_solver(self):
             A.append([float(k in (i, j)) for i in range(n) for j in range(i + 1, n)])
         A, G, b, c, h = map(matrix, (A, G, b, c, h))
         _, x = glpk.ilp(c, G.T, h, A.T, b, B=set(range(sx)))
-        reverse_mapping = [(i+1, j+1) for i in range(n) for j in range(i + 1, n)]
+        reverse_mapping = [(i + 1, j + 1) for i in range(n) for j in range(i + 1, n)]
         tour = self.edges_to_tour([reverse_mapping[k] for k in range(sx) if x[k]])
         intermediate_steps = [[]]
         for point in self.format_solution(tour):
             intermediate_steps.append(intermediate_steps[-1] + [point])
-        return intermediate_steps[2:], [self.compute_length(tour)]*n
+        return intermediate_steps[2:], [self.compute_length(tour)] * n

source/database.py

@@ -10,15 +10,15 @@
     connect_args={'check_same_thread': False},
     convert_unicode=True,
     echo=True
-    )
+)
 
 db.session = scoped_session(
     sessionmaker(
         autocommit=False,
         autoflush=False,
         bind=engine
-        )
     )
+)
 
 Base = declarative_base()
 Base.query = db.session.query_property()

source/flask_app.py

@@ -2,19 +2,18 @@
 from threading import Lock
 from flask import Blueprint, Flask, jsonify, render_template, request, session
 from flask_socketio import emit, SocketIO
-from json import dumps, load
+from json import load
 from os.path import abspath, dirname, join, pardir
 from sqlalchemy import exc as sql_exception
-from sys import dont_write_bytecode, path
 from werkzeug.utils import secure_filename
 from xlrd import open_workbook
-from xlrd.biffh import XLRDError
+import sys
 
-dont_write_bytecode = True
+sys.dont_write_bytecode = True
 path_app = dirname(abspath(__file__))
 path_parent = abspath(join(path_app, pardir))
-if path_app not in path:
-    path.append(path_app)
+if path_app not in sys.path:
+    sys.path.append(path_app)
 
 from algorithms.pytsp import pyTSP
 from database import db, create_database
@@ -53,15 +52,15 @@ def index():
         city.id: OrderedDict([
             (property, getattr(city, property))
             for property in City.properties
-            ])
+        ])
         for city in City.query.all()
-        }
+    }
     return render_template(
         'index.html',
         view=view,
         cities=cities,
         async_mode=socketio.async_mode
-        )
+    )
 
 
 @bp.route('/<algorithm>', methods=['POST'])
@@ -123,5 +122,6 @@ def genetic_algorithm(data):
         session['best'] = length
         emit('draw', ([best], [length]))
 
+
 if __name__ == '__main__':
     socketio.run(app)