#π Import mesa.time could not be resolved
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@torn maple
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Import "mesa.time" could not be resolved Pylance(reportMissingImports) error, tried to reinstall, clean install, change os and I still get this error
Error when trying to run: ModuleNotFoundError: No module named 'mesa.time'
see if this helps https://discord.com/channels/267624335836053506/1310372249072570429
I was unable to accomplish anything with that, couldn t understand
well the important idea is that you probably have many installations of python on your machine, whether you know it or not
and in order for the import to work, you have to install your package into the same version of python that's trying to import it.
did you try the hack where you add the three or four lines of code to the top of your program? That pretty much always works.
Will do that rn
because it ensures that the two versions match, even if you aren't clear on which is which.
Even after inserting those lines and it downloading stuff I still get the same output error: No module named "mesa.time"
perhaps you've installed the library properly, but are confused about which modules it provides
if it's this library, then I don't see a module named "time"
although I do see "space" π
It is that one, but I am required to use .time by my requirements from a project
π€·
that, I cannot help you with
Python 3.13.1 (v3.13.1:06714517797, Dec 3 2024, 14:00:22) [Clang 15.0.0 (clang-1500.3.9.4)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
2025-01-18T17:14:55+0000 INFO .pythonrc <module> Hello from /private/var/folders/b0/_p0c_57s5n90cy4njdgd8vhw0000gq/T/x/.venv/bin/python and /Users/not-workme/.pythonrc
2025-01-18T17:14:55+0000 INFO .pythonrc <module> cwd is /private/var/folders/b0/_p0c_57s5n90cy4njdgd8vhw0000gq/T/x
>>> import mesa
>>> import mesa.time
Traceback (most recent call last):
File "<python-input-1>", line 1, in <module>
import mesa.time
ModuleNotFoundError: No module named 'mesa.time'
>>>
``` is what I see
you'll have to ask whoever created those requirements
I have even tried replacing mesa.time with other things and rewrite the code but I got errors at launch that I was unable to resolve or understand
π€·
there's no way I can possibly help
I've never heard of this library until just now, it clearly doesn't provide a module named "time", so ... π€·
(I even tried doing pip install "mesa[all]", which installs more stuff; but that didn't provide mesa.time either)
Yea, makes sense. Is there anyway I could share you with the other code that I have and send you the errors? Maybe you can get the hang of anything inside there
I don't see the point honestly
I literally cannot imagine how this could work. I am reasonably sure your prof or TA or whoever gave you this assignment is confused.
They left out a step, or something.
Maybe your uni has their own package repository, which you're expected to use instead of pypy, and their version of "mesa" does provide mesa.time.
but that's slightly crazy.
The other one doesn t use .time, I only get some errors that I don t understand. I might just not use that and get around it
Indeed
This is the new code(without mesa.time) and the errors:
File "e:\faculta\Proiect Python\main.py", line 116, in <module>
model = EvacuationModel(num_agents=5000, width=50, height=50, exits=exits)
File "e:\faculta\Proiect Python\main.py", line 77, in init
agent = EvacuationAgent(i, self, speed, panic_threshold, is_injured)
File "e:\faculta\Proiect Python\main.py", line 13, in init
Agent.init(self, unique_id, model)
~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Merien\AppData\Local\Programs\Python\Python313\Lib\site-packages\mesa\agent.py", line 64, in init _
super().init(*args, **kwargs)
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
TypeError: object.init() takes exactly one argument (the instance to initialize)
you don't call __init__() explicitly
or at least you should do super().__init__(unique_id, model) then
(my previous comment was due to a misreading of the stack trace)
just make sure that the superclass initializer takes the arguments you expect it to
After editing the code I still get the same errors. In this code that is almost doing the same thing I get the same errors that I can t get over and have been stuck on for hours now: https://paste.pythondiscord.com/DEEQ
I just can t get around it with anything I search
I have got over those erros and only get these now: File "e:\faculta\Proiect Python\main.py", line 76, in <module>
model = OpinionModel(num_agents, influencer_fraction)
File "e:\faculta\Proiect Python\main.py", line 47, in init
self.grid.place_agent(agent, i)
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "C:\Users\Merien\AppData\Local\Programs\Python\Python313\Lib\site-packages\mesa\space.py", line 87, in wrapper if agent.pos is not None:
^^^^^^^^^
AttributeError: 'OpinionAgent' object has no attribute 'pos'
is that class supposed to inherit from a mesa class?
or why does mesa code think the instance should have a property named pos?
I am not even sure anymore, I m not the best at phyton and I m trying to fix this code
this might be relevant: https://github.com/projectmesa/mesa/pull/2476
you would have to do pip install "mesa<3.1" to get a version that still has mesa.time, but it was already deprecated at that time, just not removed yet
@torn maple π
but you should probably not use it anymore as the project writes that it has been deprecated for a while and now has even been entirely removed from the project
so i would say it's a bad requirement from whom ever gave you this assignment
I have not used it anymore, I tried to switch the code up and ended up with something new that I can t get my head around due to errors. The code has no problems anymore but I have errors.I can share the new code here
they should update their curriculum
import random
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
from mesa.space import NetworkGrid
from mesa.datacollection import DataCollector
class OpinionAgent:
def __init__(self, unique_id, model, influence, opinion):
self.unique_id = unique_id
self.model = model
self.influence = influence # Influence weight (0 to 1)
self.opinion = opinion # Current opinion (-1 to 1)
self.next_opinion = opinion # Placeholder for the next opinion
self.pos = None # Position attribute required for compatibility with NetworkGrid
def step(self):
neighbors = self.model.grid.get_neighbors(self.pos, include_center=False)
neighbor_opinions = [self.model.agent_dict[neighbor].opinion for neighbor in neighbors]
if neighbor_opinions:
peer_influence = np.mean(neighbor_opinions)
self.next_opinion = (1 - self.influence) * self.opinion + self.influence * peer_influence
else:
self.next_opinion = self.opinion
# Add randomness (independent opinion change)
if random.random() < 0.05: # 5% chance of random opinion adjustment
self.next_opinion += random.uniform(-0.1, 0.1)
self.next_opinion = np.clip(self.next_opinion, -1, 1)
def advance(self):
self.opinion = self.next_opinion
class OpinionModel:
def __init__(self, num_agents, influencer_fraction):
self.num_agents = num_agents
self.influencer_fraction = influencer_fraction
self.grid = NetworkGrid(nx.scale_free_graph(num_agents)) # Scale-free network
self.agent_dict = {} # Use a custom attribute for agent storage
for i in range(num_agents):
is_influencer = random.random() < influencer_fraction
influence = 0.9 if is_influencer else random.uniform(0.1, 0.5)
opinion = random.uniform(-1, 1)
agent = OpinionAgent(i, self, influence, opinion)
agent.pos = i # Set the position of the agent
self.agent_dict[i] = agent
self.grid.place_agent(agent, i)
self.datacollector = DataCollector(
model_reporters={"Average Opinion": self.compute_average_opinion},
agent_reporters={"Opinion": "opinion"}
)
@staticmethod
def compute_average_opinion(model):
opinions = [agent.opinion for agent in model.agent_dict.values()]
return np.mean(opinions)
def step(self):
# Update each agent's step logic
for agent in self.agent_dict.values():
agent.step()
# Advance all agents to the next state
for agent in self.agent_dict.values():
agent.advance()
# Collect data at the end of the step
self.datacollector.collect(self)
# Run the model
num_agents = 5000
influencer_fraction = 0.05 # 5% influencers
steps = 1000
model = OpinionModel(num_agents, influencer_fraction)
for _ in range(steps):
model.step()
# Collect results
data = model.datacollector.get_model_vars_dataframe()
agent_data = model.datacollector.get_agent_vars_dataframe()
# Visualization
plt.figure(figsize=(10, 6))
plt.plot(data.index, data["Average Opinion"], label="Average Opinion")
plt.title("Average Opinion Over Time")
plt.xlabel("Time Steps")
plt.ylabel("Average Opinion")
plt.legend()
plt.show()
# Histogram of final opinions
final_opinions = agent_data.xs(steps - 1, level="Step")["Opinion"]
plt.figure(figsize=(10, 6))
plt.hist(final_opinions, bins=20, edgecolor="black")
plt.title("Distribution of Final Opinions")
plt.xlabel("Opinion")
plt.ylabel("Frequency")
plt.show()
i would say this is a new problem and that you might get more help with it if you close this topic and open a new one with a new name and problem description that fits the new problem better
Alright, thank you so much!
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