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				+from sympy import * 
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				+from itertools import product, combinations 
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				+import plotly.graph_objects as go 
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				+import numpy as np 
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				+import math 
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				+ 
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				+ 
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				+class solver: 
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				+    corners = (-100, 100) 
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				+ 
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				+    data: list[str] 
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				+    equalations: list[Equality] 
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				+    sequance = None 
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				+    solutions: list 
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				+    points: list 
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				+    ndims: int 
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				+    __X = [*symbols('x1 x2 x3')] 
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				+ 
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				+    @staticmethod 
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				+    def toEq(data): 
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				+        data = data[:] 
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				+        for i,linEx in enumerate(data): 
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				+            data[i] = Eq(*[simplify(side) for side in linEx.split('=')]) 
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				+        return data 
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				+ 
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				+ 
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				+    def solve(self): 
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				+        result = [] 
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				+        for Eq in self.equalations: 
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				+            lin = [] 
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				+            for prod in product([-100, 100], repeat=self.ndims-1): 
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				+                subEq = Eq.copy() 
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				+                X = self.__X[:] 
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				+                high_sym = sorted(list(subEq.free_symbols), key=lambda x: x.name)[0] 
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				+                X.remove(high_sym) 
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				+                values = [(sym,corner) for sym, corner in zip(X, prod)] 
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				+                subEq = subEq.subs(values) 
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				+                solution = int(solve(subEq, high_sym)[0]) 
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				+                values.append((high_sym, solution)) 
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				+                lin.append(sorted(values, key=lambda x: x[0].name)) 
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				+            result.append([[dot[dim][1] for dot in lin] for dim in range(self.ndims)]) 
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				+        return result 
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				+ 
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				+ 
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				+    def right_dote(self, dote): 
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				+        flag = True 
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				+        for line in self.data: 
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				+            for sym, val in zip(self.__X, dote): line = line.replace(sym.name, str(val)) 
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				+            flag *= eval(line) 
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				+        return flag 
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				+ 
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				+ 
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				+    def get_dots(self): 
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				+        result = [] 
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				+        for Eqs in combinations(self.equalations, r=2): 
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				+            if Eqs[0] == Eqs[1]: continue 
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				+            solution = list(solve(Eqs, Eqs[0].free_symbols | Eqs[1].free_symbols, set=True))[1] 
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				+            if len(solution) == 0: continue 
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				+            dot = list(solve(Eqs, Eqs[0].free_symbols | Eqs[1].free_symbols, set=True)[1])[0] 
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				+            if self.right_dote(dot): result.append(dot) 
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				+        reference_point = result[0] 
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				+        sorted_coordinates = sorted(result, key=lambda point: math.atan2(point[1] - reference_point[1], point[0] - reference_point[0])) 
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				+        return [[float(val[dim]) for val in sorted_coordinates] for dim in range(self.ndims)] 
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				+ 
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				+ 
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				+    def show(self): 
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				+        fig = go.Figure() 
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				+        for line, names in zip(self.solutions, self.data): 
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				+            fig.add_trace(go.Scatter({dim:val for val, dim in zip(line, ('x','y','z'))}, name=str(names))) 
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				+        fig.add_trace(go.Scatter({dim:val for val, dim in zip(self.get_dots(), ('x','y','z'))}, mode='markers', fill='toself', fillpattern=dict(fillmode='replace', shape='x'))) 
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				+        fig.add_trace(go.Scatter(x=[0, self.gradient[0]], y=[0, self.gradient[1]], 
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				+                                 marker=dict(color='black', symbol='arrow', size=16, angleref="previous"), 
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				+                                 line = dict(width=4, dash='dot', color='black'))) 
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				+        touch = len(fig.data) 
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				+ 
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				+        for step in np.arange(0, self.count, self.step): 
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				+            k = ((self.gradient[1]-0) * (step-0) - (self.gradient[1]-0) * (0-0)) / ((self.gradient[1]-0)**2 + (self.gradient[0]-0)**2) 
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				+            x4 = step - k * (self.gradient[1]-0) 
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				+            y4 = 0 + k * (self.gradient[0]-0) 
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				+            y5 = y4+y4 
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				+            x5 = x4+(x4-step) 
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				+ 
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				+            fig.add_trace( 
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				+                go.Scatter(visible=False, line=dict(color='black', width=2), 
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				+                           x=[step, x4, x5], y=[0, y4, y5]) 
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				+            ) 
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				+        fig.data[touch].visible = True 
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				+ 
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				+        steps = [] 
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				+        for i in range(len(fig.data[touch:])): 
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				+            step = dict( 
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				+                method="update", 
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				+                args=[{"visible": [True]*touch + [False] * (len(fig.data)-touch)}, 
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				+                    {"title": "Slider switched to step: " + str(i)}],  # layout attribute 
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				+            ) 
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				+            step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible" 
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				+            steps.append(step) 
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				+ 
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				+        sliders = [dict( 
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				+            active=10, 
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				+            currentvalue={"prefix": "Frequency: "}, 
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				+            pad={"t": 50}, 
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				+            steps=steps 
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				+        )] 
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				+ 
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				+        fig.update_layout( 
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				+            sliders=sliders 
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				+        ) 
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				+ 
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				+        fig.update_xaxes(title_text='x1', gridwidth=1) 
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				+        fig.update_yaxes(title_text='x2', gridwidth=1) 
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				+        fig.show() 
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				+ 
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				+ 
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				+    def __init__(self, seq: str, data: list[str], ndims=2, step=0.01, count=10): 
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				+        self.data = data 
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				+        self.gradient = list(map(int,Poly(simplify(seq)).coeffs())) 
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				+        self.equalations = solver.toEq([lin.replace('>','').replace('<', '') for lin in data]) 
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				+        self.ndims = ndims 
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				+        self.__X = self.__X[:ndims] 
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				+        self.solutions = self.solve() 
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				+        self.count = count 
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				+        self.step = step 
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				+ 
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				+ 
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				+if __name__ == '__main__': 
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				+    # solver( seq='3*x1 + 4*x2', 
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				+    #         data=['4*x1 + x2 <= 8',  
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				+    #         'x1 >= 0',  
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				+    #         'x1 - x2 >= -3',  
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				+    #         'x2 >= 0'], ndims=2).show() 
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				+ 
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				+    # solver( seq='3*x1 + 2*x2', 
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				+    #         data=['2*x1 + 3*x2 <= 6',  
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				+    #         'x1 <= 2', 'x1 >= 0',  
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				+    #         '2*x1 - x2 >= 0',  
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				+    #         'x2 >= 0', 'x2 <= 1'], ndims=2).show() 
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				+ 
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				+    # solver( seq='x1 + 3*x2', 
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				+    #         data=['2*x1 + 3*x2 <= 24',  
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				+    #         'x1 >= 0',  
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				+    #         'x1 - x2 <= 7',  
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				+    #         'x2 >= 0', 'x2 <= 6'], ndims=2, step=0.1, count=25).show() 
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				+ 
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				+    # solver( seq='x1 - 1.1*x2 + 7.4', 
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				+    #         data=['x1 >= 0',  
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				+    #         'x2 >= 0',  
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				+    #         'x1 + x2 <= 10',  
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				+    #         '10 - x1 >= 0', '10 - x2 >= 0'], ndims=2, step=0.1, count=15).show() 
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				+ 
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				+     
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				+    pass 
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