本文实例讲述了Python实现简单状态框架的方法。分享给大家供大家参考。具体分析如下:
这里使用Python实现一个简单的状态框架,代码需要在python3.2环境下运行
代码如下:
from time import sleep
from random import randint, shuffle
class StateMachine(object):
''' Usage: Create an instance of StateMachine, use set_starting_state(state) to give it an
initial state to work with, then call tick() on each second (or whatever your desired
time interval might be. '''
def set_starting_state(self, state):
''' The entry state for the state machine. '''
state.enter()
self.state = state
def tick(self):
''' Calls the current state's do_work() and checks for a transition '''
next_state = self.state.check_transitions()
if next_state is None:
# Stick with this state
self.state.do_work()
else:
# Next state found, transition to it
self.state.exit()
next_state.enter()
self.state = next_state
class BaseState(object):
''' Usage: Subclass BaseState and override the enter(), do_work(), and exit() methods.
enter() -- Setup for your state should occur here. This likely includes adding
transitions or initializing member variables.
do_work() -- Meat and potatoes of your state. There may be some logic here that will
cause a transition to trigger.
exit() -- Any cleanup or final actions should occur here. This is called just
before transition to the next state.
'''
def add_transition(self, condition, next_state):
''' Adds a new transition to the state. The "condition" param must contain a callable
object. When the "condition" evaluates to True, the "next_state" param is set as
the active state. '''
# Enforce transition validity
assert(callable(condition))
assert(hasattr(next_state, "enter"))
assert(callable(next_state.enter))
assert(hasattr(next_state, "do_work"))
assert(callable(next_state.do_work))
assert(hasattr(next_state, "exit"))
assert(callable(next_state.exit))
# Add transition
if not hasattr(self, "transitions"):
self.transitions = []
self.transitions.append((condition, next_state))
def check_transitions(self):
''' Returns the first State thats condition evaluates true (condition order is randomized) '''
if hasattr(self, "transitions"):
shuffle(self.transitions)
for transition in self.transitions:
condition, state = transition
if condition():
return state
def enter(self):
pass
def do_work(self):
pass
def exit(self):
pass
##################################################################################################
############################### EXAMPLE USAGE OF STATE MACHINE ###################################
##################################################################################################
class WalkingState(BaseState):
def enter(self):
print("WalkingState: enter()")
def condition(): return randint(1, 5) == 5
self.add_transition(condition, JoggingState())
self.add_transition(condition, RunningState())
def do_work(self):
print("Walking...")
def exit(self):
print("WalkingState: exit()")
class JoggingState(BaseState):
def enter(self):
print("JoggingState: enter()")
self.stamina = randint(5, 15)
def condition(): return self.stamina
self.add_transition(condition, WalkingState())
def do_work(self):
self.stamina -= 1
print("Jogging ({0})...".format(self.stamina))
def exit(self):
print("JoggingState: exit()")
class RunningState(BaseState):
def enter(self):
print("RunningState: enter()")
self.stamina = randint(5, 15)
def walk_condition(): return self.stamina
self.add_transition(walk_condition, WalkingState())
def trip_condition(): return randint(1, 10) == 10
self.add_transition(trip_condition, TrippingState())
def do_work(self):
self.stamina -= 2
print("Running ({0})...".format(self.stamina))
def exit(self):
print("RunningState: exit()")
class TrippingState(BaseState):
def enter(self):
print("TrippingState: enter()")
self.tripped = False
def condition(): return self.tripped
self.add_transition(condition, WalkingState())
def do_work(self):
print("Tripped!")
self.tripped = True
def exit(self):
print("TrippingState: exit()")
if __name__ == "__main__":
state = WalkingState()
state_machine = StateMachine()
state_machine.set_starting_state(state)
while True:
state_machine.tick()
sleep(1)
希望本文所述对大家的Python程序设计有所帮助。

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.

Python is suitable for rapid development and data processing, while C is suitable for high performance and underlying control. 1) Python is easy to use, with concise syntax, and is suitable for data science and web development. 2) C has high performance and accurate control, and is often used in gaming and system programming.

The time required to learn Python varies from person to person, mainly influenced by previous programming experience, learning motivation, learning resources and methods, and learning rhythm. Set realistic learning goals and learn best through practical projects.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Zend Studio 13.0.1
Powerful PHP integrated development environment

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

WebStorm Mac version
Useful JavaScript development tools