# 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>
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"description": "# DBRepo Python Library\n\nOfficial client library for [DBRepo](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.4.3/), a database\nrepository to support research based\non [requests](https://pypi.org/project/requests/), [pydantic](https://pypi.org/project/pydantic/) \nand [pika](https://pypi.org/project/pika/).\n\n## Installing\n\n```console\n$ python -m pip install dbrepo\n```\n\nThis package supports Python 3.11+.\n\n## Quickstart\n\nGet public data from a table as pandas `DataFrame`:\n\n```python\nfrom dbrepo.RestClient import RestClient\n\nclient = RestClient(endpoint=\"https://test.dbrepo.tuwien.ac.at\")\n# Get a small data slice of just three rows\ndf = client.get_table_data(database_id=\"e0d82287-9099-4077-8f69-3c19fc3bc145\",\n table_id=\"71f8c746-ea26-4651-b3f2-ce46830f1af4\",\n page=0, size=3)\nprint(df)\n# x_coord component unit ... value stationid meantype\n# 0 16.52617 Feinstaub (PM10) \u00b5g/m\u00b3 ... 21.0 01:0001 HMW\n# 1 16.52617 Feinstaub (PM10) \u00b5g/m\u00b3 ... 23.0 01:0001 HMW\n# 2 16.52617 Feinstaub (PM10) \u00b5g/m\u00b3 ... 26.0 01:0001 HMW\n#\n# [3 rows x 12 columns]\n```\n\nCreate table and import `DataFrame` into a table:\n\n```python\nimport pandas as pd\nfrom dbrepo.RestClient import RestClient\n\nclient = RestClient(endpoint=\"https://test.dbrepo.tuwien.ac.at\", username=\"foo\",\n password=\"bar\")\ndf = pd.DataFrame(data={'x_coord': 16.52617, 'component': 'Feinstaub (PM10)',\n 'unit': '\u00b5g/m\u00b3', ...})\ndf = df.set_index(['x_coord'])\nclient.create_table(database_id=\"e0d82287-9099-4077-8f69-3c19fc3bc145\",\n name=\"Sensor\", is_public=True, is_schema_public=True,\n dataframe=df)\n```\n\n... or just create the table schema by setting `create_table(..., withData=False)`.\n\nIn both cases it is important to set the index to existing columns that uniquely\nidentify a row. You can specify multiple columns:\n\n```python\n...\ndf = df.set_index(['some_column', 'some_other_column'])\n```\n\n## Supported Features & Best-Practices\n\n- Manage user\n account ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#create-user-account))\n- Manage\n databases ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/usage-overview/#create-database))\n- Manage database access &\n visibility ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#create-database))\n- Import\n dataset ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#import-dataset))\n- Create persistent\n identifiers ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#assign-database-pid))\n- Execute\n queries ([docs](https://www.ifs.tuwien.ac.at/infrastructures/dbrepo/1.6/api/#export-subset))\n- Get data from tables/views/subsets\n\n## Configure\n\nAll credentials can optionally be set/overridden with environment variables. This is especially useful when sharing \nJupyter Notebooks by creating an invisible `.env` file and loading it:\n\n```\nREST_API_ENDPOINT=\"https://dbrepo1.ec.tuwien.ac.at\"\nREST_API_USERNAME=\"foo\"\nREST_API_PASSWORD=\"bar\"\nREST_API_SECURE=\"True\"\nAMQP_API_HOST=\"https://dbrepo1.ec.tuwien.ac.at\"\nAMQP_API_PORT=\"5672\"\nAMQP_API_USERNAME=\"foo\"\nAMQP_API_PASSWORD=\"bar\"\nAMQP_API_VIRTUAL_HOST=\"dbrepo\"\n```\n\nYou can disable logging by setting the log level to e.g. `INFO`:\n\n```python\nfrom dbrepo.RestClient import RestClient\nimport logging\nlogging.getLogger().setLevel(logging.INFO)\n...\nclient = RestClient(...)\n```\n\n## Roadmap\n\n- Searching\n\n## Contact\n\n* Prof. [Andreas Rauber](https://tiss.tuwien.ac.at/person/39608.html)<sup>TU Wien</sup>\n* DI. [Martin Weise](https://tiss.tuwien.ac.at/person/287722.html)<sup>TU Wien</sup>\n",
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