cpgdata 0.6.0

Cell painting gallery data handling and validation

Cell painting gallery data handling and validation

Getting started

Install cpgdata package

pip install cpgdata

Sync pre-generated index files

cpg index sync -o "path to save index files"

Example of using the index for filtering files to download from the Cell painting gallery

from pathlib import Path
from pprint import pprint

import polars as pl
from cpgdata.utils import download_s3_files, parallel

index_dir = Path("path to dir containing index files")
index_files = [file for file in index_dir.glob("*.parquet")]
df = pl.scan_parquet(index_files)

df = (
    df
    .filter(pl.col("dataset_id").eq("cpg0016-jump"))
    .filter(pl.col("source_id").eq("source_4"))
    .filter(pl.col("leaf_node").str.contains("Cells.csv"))
    .select(pl.col("key"))
    .collect()
)

# print first 10 results
pprint(df.to_dicts()[0:10])

# Download filtered files
download_keys = list(df.to_dict()["key"])
parallel(download_keys, download_s3_files, ["cellpainting-gallery", Path("path to save downloaded files")], jobs=20)