cycquery 0.1.3

A tool to query EHR databases

cyclops-query

cyclops-query is a tool for querying relational databases using a simple Python API. It is specifically developed to query Electronic Health Record (EHR) databases. The tool is a wrapper around SQLAlchemy and can be used to write SQL-like queries in Python, including joins, conditions, groupby aggregation and many more.

🐣 Getting Started

Installing cyclops-query using pip

python3 -m pip install cycquery

Query postgresql database

from cycquery import DatasetQuerier
import cycquery.ops as qo


querier = DatasetQuerier(
    dbms="postgresql",
    port=5432,
    host="localhost",
    database="dbname",
    user="usename",
    password="password",
)
# List all tables.
querier.list_tables()

# Get some table.
table = querier.schema.sometable()
# Filter based on some condition (e.g. substring match).
table = table.ops(qo.ConditionSubstring("col1", "substr"))
# Run query to get data as a pandas dataframe.
df = table.run()

# Create a sequential list of operations to perform on the query.
ops = qo.Sequential(
	qo.ConditionIn("col2", [1, 2]),
	qo.DropNulls("col3"),
	qo.Distinct("col1")
)
table = table.ops(ops)
# Run query to get data as a pandas dataframe.
df = table.run()

🧑🏿‍💻 Developing

Using poetry

The development environment can be set up using poetry. Hence, make sure it is installed and then run:

python3 -m poetry install
source $(poetry env info --path)/bin/activate

In order to install dependencies for testing (codestyle, unit tests, integration tests), run:

python3 -m poetry install --with test

API documentation is built using Sphinx and can be locally built by:

python3 -m poetry install --with docs
cd docs
make html SPHINXOPTS="-D nbsphinx_allow_errors=True"

Contributing

Contributing to cyclops-query is welcomed. See Contributing for guidelines.

📚 Documentation

🎓 Citation

Reference to cite when you use cyclops-query in a project or a research paper:

@article {Krishnan2022.12.02.22283021,
	author = {Krishnan, Amrit and Subasri, Vallijah and McKeen, Kaden and Kore, Ali and Ogidi, Franklin and Alinoori, Mahshid and Lalani, Nadim and Dhalla, Azra and Verma, Amol and Razak, Fahad and Pandya, Deval and Dolatabadi, Elham},
	title = {CyclOps: Cyclical development towards operationalizing ML models for health},
	elocation-id = {2022.12.02.22283021},
	year = {2022},
	doi = {10.1101/2022.12.02.22283021},
	publisher = {Cold Spring Harbor Laboratory Press},
	URL = {https://www.medrxiv.org/content/early/2022/12/08/2022.12.02.22283021},
	journal = {medRxiv}
}