tprdbreader

A tiny helper that fetches Translation Process Research Database (TPR-DB) tables from Google Cloud Storage and returns them as Pandas DataFrames—no manual downloads, no local staging.

Why tprdbreader?

• One function, one line:
  readTPRDBtable_GCP(["ACS08", "AR20"], ext="kd")
• Streams directly into Pandas: handles multiple studies and large Tables without blowing up RAM.
• MIT-licensed & lightweight: only two runtime deps—pandas and google-cloud-storage.

Installation

pip install tprdbreader          # requires Python 3.6+

Quick-start

from tprdbreader import readTPRDBtable_GCP

# Pull all *.kd files (Keystroke Burst layer) from two studies
df = readTPRDBtable_GCP(
        studies=["ACS08", "AR20"],
        ext="kd",              # extension WITHOUT dot works too
        user="TPRDB",          # public user
        verbose=1)             # print per-study stats

print(df.head())

Example verbose output

ACS08  #sessions: 33   .kd:152  ...
AR20   #sessions: 29   .kd:131

API Reference

readTPRDBtable_GCP(studies, ext, user="TPRDB", verbose=0) -> pandas.DataFrame

Returns: a single concatenated pandas.DataFrame.
Columns depend on the specific Table you load (*.kd, *.au, *.ss …).

Internal path logic

For each study <S> the function builds
data/critt/tprdb/<user>/<S>/Tables/
and downloads every file whose name ends with .<ext>.

License

Released under the MIT License — see LICENSE for full text.

_{© 2025 Devisri Bandaru. Affiliated with the official TPRDB maintainers.}