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Create Python applications that use pandas and Dash to build Phoenix-connected web apps.
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Phoenix, the pandas module, and the Dash framework, you can build Phoenix-connected web applications for Phoenix data. This article shows how to connect to Phoenix with the CData Connector and use pandas and Dash to build a simple web app for visualizing Phoenix data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Phoenix data in Python. When you issue complex SQL queries from Phoenix, the driver pushes supported SQL operations, like filters and aggregations, directly to Phoenix and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Phoenix Data
Connecting to Phoenix 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.
Connect to Apache Phoenix via the Phoenix Query Server. Set the Server and Port (if different from the default port) properties to connect to Apache Phoenix. The Server property will typically be the host name or IP address of the server hosting Apache Phoenix.
Authenticating to Apache Phoenix
By default, no authentication will be used (plain). If authentication is configured for your server, set AuthScheme to NEGOTIATE and set the User and Password properties (if necessary) to authenticate through Kerberos.
After installing the CData Phoenix Connector, follow the procedure below to install the other required modules and start accessing Phoenix through Python objects.
Install Required Modules
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
Visualize Phoenix Data in Python
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.apachephoenix as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Phoenix Connector to create a connection for working with Phoenix data.
cnxn = mod.connect("Server=localhost;Port=8765;")
Execute SQL to Phoenix
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 Id, Column1 FROM MyTable WHERE Id = '123456'", cnxn)
Configure the Web App
With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.
app_name = 'dash-apachephoenixedataplot' external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.title = 'CData + Dash'
Configure the Layout
The next step is to create a bar graph based on our Phoenix data and configure the app layout.
trace = go.Bar(x=df.Id, y=df.Column1, name='Id') 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='Phoenix MyTable Data', barmode='stack') }) ], className="container")
Set the App to Run
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 Phoenix data.
python apachephoenix-dash.py
Free Trial & More Information
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Full Source Code
import os import dash import dash_core_components as dcc import dash_html_components as html import pandas as pd import cdata.apachephoenix as mod import plotly.graph_objs as go cnxn = mod.connect("Server=localhost;Port=8765;") df = pd.read_sql("SELECT Id, Column1 FROM MyTable WHERE Id = '123456'", cnxn) app_name = 'dash-apachephoenixdataplot' 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.Id, y=df.Column1, name='Id') 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='Phoenix MyTable Data', barmode='stack') }) ], className="container") if __name__ == '__main__': app.run_server(debug=True)