dbrepo 1.13.3
DBRepo Python Library
Requires Python: >=3.11
Keywords: DBRepo, Database Repository

# DBRepo Python Library

Official client library for [DBRepo](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.4.3/), a database
repository to support research based
on [requests](https://pypi.org/project/requests/), [pydantic](https://pypi.org/project/pydantic/) 
and [pika](https://pypi.org/project/pika/).

## Installing

```console
$ python -m pip install dbrepo
```

This package supports Python 3.11+.

## Quickstart

Get public data from a table as pandas `DataFrame`:

```python
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:

```python
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:

```python
...
df = df.set_index(['some_column', 'some_other_column'])
```

## Supported Features & Best-Practices

- Manage user
  account ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#create-user-account))
- Manage
  databases ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/usage-overview/#create-database))
- Manage database access &
  visibility ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#create-database))
- Import
  dataset ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#import-dataset))
- Create persistent
  identifiers ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#assign-database-pid))
- Execute
  queries ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#export-subset))
- 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`:

```python
from dbrepo.RestClient import RestClient
import logging
logging.getLogger().setLevel(logging.INFO)
...
client = RestClient(...)
```

## Roadmap

- Searching

## Contact

* Prof. [Andreas Rauber](https://tiss.tuwien.ac.at/person/39608.html)<sup>TU Wien</sup>
* DI. [Martin Weise](https://tiss.tuwien.ac.at/person/287722.html)<sup>TU Wien</sup>