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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for IBM Cloud Object Storage, the pandas module, and the Dash framework, you can build IBM Cloud Object Storage-connected web applications for IBM Cloud Object Storage data. This article shows how to connect to IBM Cloud Object Storage with the CData Connector and use pandas and Dash to build a simple web app for visualizing IBM Cloud Object Storage data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live IBM Cloud Object Storage data in Python. When you issue complex SQL queries from IBM Cloud Object Storage, the driver pushes supported SQL operations, like filters and aggregations, directly to IBM Cloud Object Storage and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to IBM Cloud Object Storage data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.
If you do not already have Cloud Object Storage in your IBM Cloud account, follow the procedure below to install an instance of SQL Query in your account:
There are certain connection properties you need to set before you can connect. You can obtain these as follows:
To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:
If you have multiple accounts, specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:
You can now set the following to connect to data:
When you connect, the connector completes the OAuth process.
After installing the CData IBM Cloud Object Storage Connector, follow the procedure below to install the other required modules and start accessing IBM Cloud Object Storage through Python objects.
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.
First, be sure to import the modules (including the CData Connector) with the following:
import os import dash import dash_core_components as dcc import dash_html_components as html import pandas as pd import cdata.ibmcloudobjectstorage as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData IBM Cloud Object Storage Connector to create a connection for working with IBM Cloud Object Storage data.
cnxn = mod.connect("ApiKey=myApiKey;CloudObjectStorageCRN=MyInstanceCRN;Region=myRegion;OAuthClientId=MyOAuthClientId;OAuthClientSecret=myOAuthClientSecret;")
Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.
df = pd.read_sql("SELECT Key, Etag FROM Objects WHERE Bucket = 'someBucket'", cnxn)
With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.
app_name = 'dash-ibmcloudobjectstorageedataplot' external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.title = 'CData + Dash'
The next step is to create a bar graph based on our IBM Cloud Object Storage data and configure the app layout.
trace = go.Bar(x=df.Key, y=df.Etag, name='Key')
app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout':
go.Layout(title='IBM Cloud Object Storage Objects Data', barmode='stack')
})
], className="container")
With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.
if __name__ == '__main__': app.run_server(debug=True)
Now, use Python to run the web app and a browser to view the IBM Cloud Object Storage data.
python ibmcloudobjectstorage-dash.py👁 IBM Cloud Object Storage data in a Dash web app (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for IBM Cloud Object Storage to start building Python apps with connectivity to IBM Cloud Object Storage data. Reach out to our Support Team if you have any questions.
import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.ibmcloudobjectstorage as mod
import plotly.graph_objs as go
cnxn = mod.connect("ApiKey=myApiKey;CloudObjectStorageCRN=MyInstanceCRN;Region=myRegion;OAuthClientId=MyOAuthClientId;OAuthClientSecret=myOAuthClientSecret;")
df = pd.read_sql("SELECT Key, Etag FROM Objects WHERE Bucket = 'someBucket'", cnxn)
app_name = 'dash-ibmcloudobjectstoragedataplot'
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Key, y=df.Etag, name='Key')
app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout':
go.Layout(title='IBM Cloud Object Storage Objects Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)
Download a Community License of the IBM Cloud Object Storage Connector to get started:
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👁 IBM Cloud Object Storage IconPython Connector Libraries for IBM Cloud Object Storage Data Connectivity. Integrate IBM Cloud Object Storage with popular Python tools like Pandas, SQLAlchemy, Dash & petl.