Observed since 20 Oct, 17:30 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Collection of tasks for analyzing colony dynamics.
Collection of tasks for analyzing colony dynamics. Designed to be used both in Prefect workflows and as modular, useful pieces of code.
The collection can be installed using:
pip install abm-colony-collection
We recommend using Poetry to manage and install dependencies. To install into your Poetry project, use:
poetry add abm-colony-collection
All tasks in this collection are wrapped in a Prefect @task decorator, and can be used directly in a Prefect @flow.
Running tasks within a Prefect flow enables you to take advantage of features such as automatically retrying failed tasks, monitoring workflow states, running tasks concurrently, deploying and scheduling flows, and more.
from prefect import flow
from abm_colony_collection import <task_name>
@flow
def run_flow():
<task_name>()
if __name__ == "__main__":
run_flow()
See cell-abm-pipeline for examples of using tasks from different collections to build a pipeline for simulating and analyzing agent-based model data.
Not all use cases require a full workflow.
Tasks in this collection can be used without the Prefect @task decorator by simply importing directly from the module:
from abm_colony_collection.<task_name> import <task_name>
def main():
<task_name>()
if __name__ == "__main__":
main()
or using the .fn() method:
from abm_colony_collection import <task_name>
def main():
<task_name>.fn()
if __name__ == "__main__":
main()
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.5.0 | 25 Sept 2024 | 6 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 17:30 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:0f7bb0cbd8decf96fa4a0d799fd504a076ffc59bf41e7d599cd80cd277d9dd3c