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# ============================================================
# CITATION.cff (How to cite this project)
# ============================================================
# REQ.UNIVERSAL: Professional open projects SHOULD include this file.
# WHY: Support correct citation and attribution.
# ALT: Internal or private repositories may omit citation metadata.
# CUSTOM: Update author, repository, license, and keyword fields as needed.
# USAGE: See https://citation-file-format.github.io/ for details.
cff-version: "1.2.0"
type: software
title: "datafun-streaming: Shared Utilities for Streaming Data Analytics"
version: "0.7.0"
date-released: "2026-05-09"
authors:
- family-names: Case
given-names: Denise M.
orcid: "https://orcid.org/0000-0001-6165-7389"
affiliation: "Northwest Missouri State University, School of Computer Science and Information Systems, Maryville, MO, USA"
repository-code: "https://github.com/denisecase/datafun-streaming"
url: "https://github.com/denisecase/datafun-streaming"
license: MIT
abstract: >
Reusable Python library providing shared utilities for streaming data analytics
projects. Includes Kafka producer, consumer, and admin helpers built on
confluent-kafka; DuckDB storage utilities with schema inference and safe
parameterized queries; data validation types and field-level validators;
CSV and JSON file I/O helpers; incremental running statistics; and Plotly
chart utilities for live data visualization. Designed for use across
graduate-level streaming data analytics modules and projects.
keywords:
# identity
- streaming-data
- kafka
- duckdb
- data-validation
- data-analytics
- reusable-library
- graduate-education
# practices
- professional-python
- src-layout
- ci-cd
- github-actions
- reproducible-workflows
- software-quality
- professional-practice
# tools and ecosystem
- python
- confluent-kafka
- duckdb
- plotly
- git
- github
- open-source
- uv
- ruff
- pre-commit
- pyright
- hatchling
- zensical
- pypi
message: "If using this work, please cite it as described in this file."