A toolkit for accessing and working with data from the CRITT Translation Process Research Database (TPR-DB).
Project description
tprdb-utilities
A Python toolkit for downloading and reading data tables from the CRITT Translation Process Research Database (TPR-DB).
Two functions cover the full workflow:
| Function | What it does |
|---|---|
fetch_TPRDB_tables |
Downloads study tables from the CRITT API and saves them to a local directory structure |
read_TPRDB_tables |
Reads those tables (locally or on the CRITT server) into a single pandas.DataFrame |
Installation
# pip
pip install tprdb-utilities
# uv
uv add tprdb-utilities
# poetry
poetry add tprdb-utilities
Quick Start
1 — Download data (fetcher)
Public study (no credentials needed):
from tprdb_utilities import fetch_TPRDB_tables
fetch_TPRDB_tables(
path="/path/to/local/data",
StudyID="DG21",
extension=["kd", "ss"],
public=True,
)
Private study (requires your TPR-DB username and API token):
from tprdb_utilities import fetch_TPRDB_tables
fetch_TPRDB_tables(
path="/path/to/local/data",
StudyID="MYSTUDY",
extension=["kd"],
public=False,
username="myTPRDBusername", # case-sensitive, must match your account
token="my-api-token",
)
After downloading, the function always prints a summary like this:
=== fetch_TPRDB_tables Summary ===
StudyID : DG21
Clone dir: /path/to/local/data/tprdb-mothership-clone
User dir : TPRDB
Extension Status Time
--------- ---------- ------
kd Downloaded 1.23s
ss Downloaded 0.98s
To read these files with read_TPRDB_tables:
path = "/path/to/local/data/tprdb-mothership-clone"
user = "TPRDB"
studies = ["DG21"]
Copy those argument values directly into read_TPRDB_tables.
2 — Read data (reader)
From a local clone (mothership=False) — after running fetch_TPRDB_tables:
from tprdb_utilities import read_TPRDB_tables
df = read_TPRDB_tables(
studies=["DG21", "AR22"],
extension="kd",
mothership=False,
path="/path/to/local/data/tprdb-mothership-clone",
user="TPRDB",
)
Directly on the CRITT TPR-DB server (mothership=True):
from tprdb_utilities import read_TPRDB_tables
df = read_TPRDB_tables(
studies=["DG21", "AR22"],
extension="kd",
mothership=True, # path is set automatically; no path argument needed
)
Directory Structure
fetch_TPRDB_tables creates the following layout under path:
<path>/
└── tprdb-mothership-clone/
├── TPRDB/ ← public studies
│ └── <StudyID>/
│ └── Tables/
│ ├── session1.kd
│ └── ...
└── <username>/ ← private studies
└── <StudyID>/
└── Tables/
├── session1.kd
└── ...
read_TPRDB_tables with mothership=False expects this exact layout, so the
two functions are designed to work together seamlessly.
Supported Table Extensions
ss, sg, st, tt, kd, fd, au, pu, hof, pol
License
MIT — see LICENSE.
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