python-client.md

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Python Client Library	/integrate/storage/python-client/

• TOC {:toc}

The Python client library is a Storage API client which you can use in your Python code. The current implementation supports all basic data manipulations:

• Importing data
• Exporting data
• Creating and deleting buckets and tables
• Creating and deleting workspaces

The client source code is available in our Github repository.

Installation

This library is available on Github, so we recommend that you use the pip package to install it:

pip3 install git+https://github.com/keboola/sapi-python-client.git

Usage

The client contains a Client class, which encapsulates all API endpoints and holds a storage token and URL. Each API endpoint is represented by its own class (Files, Buckets, Jobs, etc.), which can be used standalone if you only work with one endpoint. This means that the two following examples are equivalent:

{% highlight python %} from kbcstorage.client import Client

client = Client('https://connection.keboola.com', 'your-token') client.tables.detail('in.c-demo.some-table') {% endhighlight %}

{% highlight python %} from kbcstorage.tables import Tables

tables = Tables('https://connection.keboola.com', 'your-token') tables.detail('in.c-demo.some-table') {% endhighlight %}

Example --- Create Table and Import Data

To create a new table in Storage, use the create function of the Tables class. Provide the name of an existing bucket, the name of the new table and a CSV file with the table's contents.

To create the new-table table in the in.c-main bucket, use:

{% highlight python %} from kbcstorage.client import Client

client = Client('https://connection.keboola.com', 'your-token') client.tables.create(name='new-table', bucket_id='in.c-main', file_path='coords.csv', primary_key=['id']) {% endhighlight %}

The above command will import the contents of the coords.csv file into the newly created table. It will also mark the id column as the primary key.

Example --- Load to existing table, incrementally

To load data incrementally into an existing table, we can use the load method, where table_id is the ID of the table that you want to load into, and path is the path to your csv file containing the data:

{% highlight python %}

from kbcstorage.client import Client

client = Client('https://connection.keboola.com', 'your-token')

client.tables.load(table_id=table_id, file_path=path, is_incremental=True)

{% endhighlight %}

Example --- Export Data

To export data from the old-table table in the in.c-main bucket, use:

{% highlight python %} from kbcstorage.client import Client import csv

client = Client('https://connection.keboola.com', 'your-token') client.tables.export_to_file(table_id='in.c-main.new-table', path_name='.') with open('./new-table', mode='rt', encoding='utf-8') as in_file: lazy_lines = (line.replace('\0', '') for line in in_file) reader = csv.reader(lazy_lines, lineterminator='\n') for row in reader: print(row) {% endhighlight %}

The above command will export the table from Storage into the file new-table and read it using CSV Reader.

Other Examples

{% highlight python %}

create a client

client = Client('https://connection.keboola.com', 'your-token')

create a bucket

client.buckets.create(name='demo', stage='in')

list buckets

client.buckets.list()

list all tables

client.tables.list()

list all tables in a bucket

client.buckets.list_tables(bucket_id='in.c-demo')

delete a table

client.tables.delete(table_id='in.c-demo.some-table')

delete a bucket

client.buckets.delete(bucket_id='in.c-main', force=True)

{% endhighlight %}