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annotate gamelib/lab.py @ 45:1e8f7e694f0c

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Refactor missions and sciences a bit to reduce duplication.
author Jeremy Thurgood <firxen@gmail.com>
date Mon, 07 May 2012 20:44:27 +0200
parents efc4f90cfd63
children d3d277a42ac6
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1 # -*- test-case-name: gamelib.tests.test_lab -*-
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3 from random import random, choice
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4
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5 from gamelib import research, products
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6 from gamelib.game_base import get_subclasses
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8
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9 class Lab(object):
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10 BASIC_RESEARCH_SUCCESS_RATE = 0.05
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11 BASIC_RESEARCH_SUCCESS_MULTIPLIER = 2
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13 def __init__(self, init_data=None):
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14 self.science = []
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15 self.new_research = get_subclasses(research.ResearchArea)
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16 self.new_products = get_subclasses(products.Product)
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18 if init_data is not None:
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19 # Load stored state.
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20 self._load_data(init_data)
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21 else:
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22 # New game.
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23 self._choose_initial_science()
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24
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25 def _load_data(self, init_data):
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26 for name, points in init_data['science'].iteritems():
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27 science_type, cls = name.split('.')
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28 if science_type == 'product':
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29 science = getattr(products, cls)
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30 elif science_type == 'research':
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31 science = getattr(research, cls)
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32 else:
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33 raise ValueError("Unknown science type: %s" % (science_type,))
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34 self._gain_science(science(points))
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35
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36 def save_data(self):
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37 data = {'science': {}}
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38 for science in self.science:
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39 name = "%s.%s" % (science.SCIENCE_TYPE, type(science).__name__)
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40 data['science'][name] = science.points
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41 return data
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42
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43 def _choose_initial_science(self):
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44 # We always get all starting products.
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45 for product in self.new_products[:]:
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46 if product.STARTING_PRODUCT:
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47 self._gain_science(product())
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48
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49 # We get three random sciences with no prerequisites.
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50 new_science = []
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51 for _ in range(3):
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52 science = choice(self.find_new_research())()
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53 self._gain_science(science)
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54 new_science.append(science)
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55
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56 # Add a point to each of our sciences, and see if we get products.
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57 self.spend_points(new_science, 0)
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58
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59 def _gain_science(self, science):
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60 self.science.append(science)
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61 if isinstance(science, research.ResearchArea):
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62 self.new_research.remove(type(science))
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63 elif isinstance(science, products.Product):
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64 self.new_products.remove(type(science))
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65
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66 def spend_points(self, things, basic_research):
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67 breakthroughs = []
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68
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69 # First, allocate the points.
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70 for thing in things:
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71 assert thing in self.science
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72 assert thing.can_spend(self)
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73 thing.spend_point()
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74
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75 # Next, check for product breakthroughs and upgrades
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76 for thing in things:
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77 if isinstance(thing, research.ResearchArea):
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78 breakthroughs.extend(self.apply_area_research(thing))
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79
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80 # Finally, check for research breakthroughs.
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81 breakthroughs.extend(self.apply_basic_research(basic_research))
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82
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83 return breakthroughs
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84
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85 def _get_science(self, science_class):
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86 for science in self.science:
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87 if isinstance(science, science_class):
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88 return science
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89 return None
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90
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91 def meet_requirements(self, science_class, extra=0):
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92 total_points = 0
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93 base_points = 0
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94 for science, level in science_class.PREREQUISITES:
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95 my_science = self._get_science(science)
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96 if my_science is None:
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97 return False
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98 if my_science.points < level:
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99 return False
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100 base_points += level
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101 total_points += my_science.points
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102 return total_points - base_points >= extra
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103
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104 def find_new_products(self):
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105 available_products = []
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106 for product_class in self.new_products:
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107 if self.meet_requirements(product_class):
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108 available_products.append(product_class)
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109 return available_products
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110
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111 def find_new_research(self):
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112 available_research = []
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113 for research_class in self.new_research:
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114 if self.meet_requirements(research_class):
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115 available_research.append(research_class)
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116 return available_research
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117
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118 def apply_area_research(self, research):
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119 options = [product for product in self.find_new_products()
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120 if type(research) in [p[0] for p in product.PREREQUISITES]]
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121 breakthroughs = [product for product in options
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122 if random() < product.ACQUISITION_CHANCE]
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123 if breakthroughs:
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124 breakthrough = choice(breakthroughs)()
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125 self._gain_science(breakthrough)
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126 breakthroughs = [breakthrough]
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127 return breakthroughs
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128
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129 def apply_basic_research(self, basic_research):
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130 if basic_research <= 1:
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131 return []
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132
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133 options = self.find_new_research()
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134 success_chance = self.BASIC_RESEARCH_SUCCESS_RATE * (
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135 self.BASIC_RESEARCH_SUCCESS_MULTIPLIER ** basic_research)
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136 breakthroughs = [research for research in options
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137 if random() < success_chance]
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138 if breakthroughs:
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parents: 14
diff changeset
139 breakthrough = choice(breakthroughs)(1)
10d3db1f1e08 Set up initial research and rework breakthroughs.
Jeremy Thurgood <firxen@gmail.com>
parents: 14
diff changeset
140 self._gain_science(breakthrough)
10d3db1f1e08 Set up initial research and rework breakthroughs.
Jeremy Thurgood <firxen@gmail.com>
parents: 14
diff changeset
141 breakthroughs = [breakthrough]
10d3db1f1e08 Set up initial research and rework breakthroughs.
Jeremy Thurgood <firxen@gmail.com>
parents: 14
diff changeset
142 return breakthroughs