#πŸ”’ Import mesa.time could not be resolved

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dawn cedarBOT
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@torn maple

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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

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Error when trying to run: ModuleNotFoundError: No module named 'mesa.time'

static quarry
torn maple
static quarry
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well the important idea is that you probably have many installations of python on your machine, whether you know it or not

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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.

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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.

torn maple
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Will do that rn

static quarry
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because it ensures that the two versions match, even if you aren't clear on which is which.

torn maple
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Even after inserting those lines and it downloading stuff I still get the same output error: No module named "mesa.time"

static quarry
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perhaps you've installed the library properly, but are confused about which modules it provides

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although I do see "space" πŸ™‚

torn maple
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It is that one, but I am required to use .time by my requirements from a project

static quarry
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🀷

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that, I cannot help you with

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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
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you'll have to ask whoever created those requirements

torn maple
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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

static quarry
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🀷

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there's no way I can possibly help

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I've never heard of this library until just now, it clearly doesn't provide a module named "time", so ... 🀷

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(I even tried doing pip install "mesa[all]", which installs more stuff; but that didn't provide mesa.time either)

torn maple
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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

static quarry
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I don't see the point honestly

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I literally cannot imagine how this could work. I am reasonably sure your prof or TA or whoever gave you this assignment is confused.

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They left out a step, or something.

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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.

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but that's slightly crazy.

torn maple
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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

torn maple
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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)

https://paste.pythondiscord.com/YFKQ

north gale
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you don't call __init__() explicitly

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or at least you should do super().__init__(unique_id, model) then

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(my previous comment was due to a misreading of the stack trace)

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just make sure that the superclass initializer takes the arguments you expect it to

torn maple
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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

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I just can t get around it with anything I search

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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'

https://paste.pythondiscord.com/2JTA

north gale
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is that class supposed to inherit from a mesa class?

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or why does mesa code think the instance should have a property named pos?

torn maple
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I am not even sure anymore, I m not the best at phyton and I m trying to fix this code

latent osprey
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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

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@torn maple πŸ‘†

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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

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so i would say it's a bad requirement from whom ever gave you this assignment

torn maple
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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

latent osprey
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they should update their curriculum

torn maple
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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()
latent osprey
dawn cedarBOT
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