DBRepo Python Library
Official client library for DBRepo, a database repository to support research based on requests, pydantic and pika.
Installing
$ python -m pip install dbrepo
This package supports Python 3.11+.
Quickstart
Get public data from a table as pandas DataFrame:
from dbrepo.RestClient import RestClient
client = RestClient(endpoint="https://test.dbrepo.tuwien.ac.at")
# Get a small data slice of just three rows
df = client.get_table_data(database_id="e0d82287-9099-4077-8f69-3c19fc3bc145",
table_id="71f8c746-ea26-4651-b3f2-ce46830f1af4",
page=0, size=3)
print(df)
# x_coord component unit ... value stationid meantype
# 0 16.52617 Feinstaub (PM10) µg/m³ ... 21.0 01:0001 HMW
# 1 16.52617 Feinstaub (PM10) µg/m³ ... 23.0 01:0001 HMW
# 2 16.52617 Feinstaub (PM10) µg/m³ ... 26.0 01:0001 HMW
#
# [3 rows x 12 columns]
Create table and import DataFrame into a table:
import pandas as pd
from dbrepo.RestClient import RestClient
client = RestClient(endpoint="https://test.dbrepo.tuwien.ac.at", username="foo",
password="bar")
df = pd.DataFrame(data={'x_coord': 16.52617, 'component': 'Feinstaub (PM10)',
'unit': 'µg/m³', ...})
df = df.set_index(['x_coord'])
client.create_table(database_id="e0d82287-9099-4077-8f69-3c19fc3bc145",
name="Sensor", is_public=True, is_schema_public=True,
dataframe=df)
... or just create the table schema by setting create_table(..., withData=False).
In both cases it is important to set the index to existing columns that uniquely identify a row. You can specify multiple columns:
...
df = df.set_index(['some_column', 'some_other_column'])
Supported Features & Best-Practices
- Manage user account (docs)
- Manage databases (docs)
- Manage database access & visibility (docs)
- Import dataset (docs)
- Create persistent identifiers (docs)
- Execute queries (docs)
- Get data from tables/views/subsets
Configure
All credentials can optionally be set/overridden with environment variables. This is especially useful when sharing
Jupyter Notebooks by creating an invisible .env file and loading it:
REST_API_ENDPOINT="https://dbrepo1.ec.tuwien.ac.at"
REST_API_USERNAME="foo"
REST_API_PASSWORD="bar"
REST_API_SECURE="True"
AMQP_API_HOST="https://dbrepo1.ec.tuwien.ac.at"
AMQP_API_PORT="5672"
AMQP_API_USERNAME="foo"
AMQP_API_PASSWORD="bar"
AMQP_API_VIRTUAL_HOST="dbrepo"
You can disable logging by setting the log level to e.g. INFO:
from dbrepo.RestClient import RestClient
import logging
logging.getLogger().setLevel(logging.INFO)
...
client = RestClient(...)
Roadmap
- Searching
Contact
- Prof. Andreas RauberTU Wien
- DI. Martin WeiseTU Wien
3 maintainers
Release files for dbrepo 1.13.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dbrepo-1.13.8.tar.gz | 103.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dbrepo-1.13.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 188.5 kB
Release files / dbrepo-1.13.8.tar.gz
| Download URL | dbrepo-1.13.8.tar.gz |
|---|---|
| Size | 103.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
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|
Release files / dbrepo-1.13.8-py3-none-any.whl
| Download URL | dbrepo-1.13.8-py3-none-any.whl |
|---|---|
| Size | 85.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.9
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