A library to read Translation Process Research Database (TPR-DB) tables from Google Cloud Storage.
Project description
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—
pandasandgoogle-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
| Argument | Type | Description |
|---|---|---|
studies |
list[str] |
List of study IDs (folder names) such as ["ACS08", "AR20"]. |
ext |
str |
File extension without the leading dot, e.g. "kd", "au", "ss". |
user |
str |
Default "TPRDB". |
verbose |
int |
0 = silent, any non-zero prints per-study stats. |
Returns: a single concatenated
pandas.DataFrame.
Columns depend on the specific BTSS layer 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. """)
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