diff --git a/mesa_frames/abstract/datacollector.py b/mesa_frames/abstract/datacollector.py new file mode 100644 index 00000000..cf23831e --- /dev/null +++ b/mesa_frames/abstract/datacollector.py @@ -0,0 +1,210 @@ +""" +Abstract base classes for data collection components in mesa-frames. + +This module defines the core abstractions for data collection in mesa-frames. +It provides a standardized interface for collecting model- and agent-level +data during simulation runs, supporting flexible triggers, custom statistics, +and optional external storage. + +Classes: + AbstractDataCollector: + An abstract base class defining the structure and core logic for + all data collector implementations. It supports flexible reporting + of model and agent attributes, conditional data collection using + triggers, and pluggable backends for storage. + +These classes are designed to be subclassed by concrete implementations that +handle the specifics of data collection and storage such as in-memory, CSV, +or database-backed collectors, potentially using Polars for high-performance +tabular operations. + +Usage: + These classes should not be instantiated directly. Instead, they should be + subclassed to create concrete DataCollector: + + from mesa_frames.abstract.datacollector import AbstractDataCollector + + class DataCollector(AbstractDataCollector): + def collect(self): + # Implementation using Polars DataFrame to collect model and agent data + ... + + def conditional_collect(self): + # Implementation using Polars DataFrame to collect model and agent data if trigger returns True + ... + + def data(self): + # Returns the data currently in memory + ... + + def flush(self): + # Persists collected data if configured and optionally deletes data from memory + ... + +For more detailed information on each class, refer to their individual docstrings. +""" + +from abc import ABC, abstractmethod +from typing import Dict, Optional, Union, Any, Literal, List +from collections.abc import Callable +from mesa_frames import ModelDF +import polars as pl + + +class AbstractDataCollector(ABC): + """ + Abstract Base Class for Mesa-Frames DataCollector. + + This class defines methods for collecting data from both model and agents. + Sub classes must implement logic for the methods + """ + + _model: ModelDF + _model_reporters: dict[str, Callable] | None + _agent_reporters: dict[str, str | Callable] | None + _trigger: Callable[..., bool] + _reset_memory = bool + _storage_uri: Literal["memory:", "csv:", "postgresql:"] + _frames: list[pl.DataFrame] + + def __init__( + self, + model: ModelDF, + model_reporters: dict[str, Callable] | None = None, + agent_reporters: dict[str, str | Callable] | None = None, + trigger: Callable[[Any], bool] | None = None, + reset_memory: bool = True, + storage: Literal["memory:", "csv:", "postgresql:"] = "memory:", + ): + """ + Initialize a Datacollector. + + Parameters + ---------- + model : ModelDF + The model object from which data is collected. + model_reporters : dict[str, Callable] | None + Functions to collect data at the model level. + agent_reporters : dict[str, str | Callable] | None + Attributes or functions to collect data at the agent level. + trigger : Callable[[Any], bool] | None + A function(model) -> bool that determines whether to collect data. + reset_memory : bool + Whether to reset in-memory data after flushing. Default is True. + storage : Literal["memory:", "csv:", "postgresql:"] + Storage backend URI (e.g. 'memory:', 'csv:', 'postgresql:'). + """ + self._model = model + self._model_reporters = model_reporters or {} + self._agent_reporters = agent_reporters or {} + self._trigger = trigger or (lambda model: False) + self._reset_memory = reset_memory + self._storage_uri = storage or "memory:" + self._frames = [] + + def collect(self) -> None: + """ + Trigger Data collection. + + This method calls _collect() to perform actual data collection. + + Example + ------- + >>> datacollector.collect() + """ + self._collect() + + def conditional_collect(self) -> None: + """ + Trigger data collection if condition is met. + + This method caslls _collect() to perform actual data collection + + Example + ------- + >>> datacollector.conditional_collect() + """ + if self._should_collect(): + self._collect() + + def _should_collect(self) -> bool: + """ + Evaluate whether data should be collected at current step. + + Returns + ------- + bool + True if the configured trigger condition is met, False otherwise. + """ + return self._trigger(self._model) + + @abstractmethod + def _collect(self): + """ + Perform the actual data collection logic. + + This method must be im + """ + pass + + @property + @abstractmethod + def data(self) -> Any: + """ + Returns collected data currently in memory as a dataframe. + + Example: + ------- + >>> df = datacollector.data + >>> print(df) + """ + pass + + def flush(self) -> None: + """ + Persist all collected data to configured backend. + + After flushing data optionally clears in-memory + data buffer if `reset_memory` is True (default behavior). + + use this method to save collected data. + + + Example + ------- + >>> datacollector.flush() + >>> # Data is saved externally and in-memory buffers are cleared if configured + """ + self._flush() + if self._reset_memory: + self._reset() + + def _reset(self): + """ + Clear all collected data currently stored in memory. + + Use this to free memory or start fresh without affecting persisted data. + + """ + self._frames = [] + + @abstractmethod + def _flush(self) -> None: + """ + Implement persistence of collected data to external storage. + + This method must be implemented by subclasses to handle + backend-specific data saving operations. + """ + pass + + @property + def seed(self) -> int: + """ + Function to get the model seed. + + Example: + -------- + >>> seed = datacollector.seed + """ + return self._model._seed diff --git a/uv.lock b/uv.lock index 68345793..416d802c 100644 --- a/uv.lock +++ b/uv.lock @@ -1,4 +1,5 @@ version = 1 +revision = 1 requires-python = ">=3.11" resolution-markers = [ "python_full_version >= '3.12'", @@ -569,35 +570,35 @@ wheels = [ [[package]] name = "fonttools" -version = "4.58.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = 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