Use Dash to Build to Web Apps on FTP Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for FTP, the pandas module, and the Dash framework, you can build FTP-connected web applications for FTP data. This article shows how to connect to FTP with the CData Connector and use pandas and Dash to build a simple web app for visualizing FTP data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live FTP data in Python. When you issue complex SQL queries from FTP, the driver pushes supported SQL operations, like filters and aggregations, directly to FTP and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to FTP Data

Connecting to FTP 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.

To connect to FTP or SFTP servers, specify at least RemoteHost and FileProtocol. Specify the port with RemotePort.

Set User and Password to perform Basic authentication. Set SSHAuthMode to use SSH authentication. See the Getting Started section of the data provider help documentation for more information on authenticating via SSH.

Set SSLMode and SSLServerCert to secure connections with SSL.

The data provider lists the tables based on the available folders in your FTP server. Set the following connection properties to control the relational view of the file system:

• RemotePath: Set this to the current working directory.
• TableDepth: Set this to control the depth of folders to list as views.
• FileRetrievalDepth: Set this to retrieve and list files recursively from the root table.

Stored Procedures are available to download files, upload files, and send protocol commands. See the Data Model chapter of the FTP data provider documentation for more information.

After installing the CData FTP Connector, follow the procedure below to install the other required modules and start accessing FTP 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 FTP 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.ftp as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData FTP Connector to create a connection for working with FTP data.

cnxn = mod.connect("RemoteHost=MyFTPServer;")

Execute SQL to FTP

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 Filesize, Filename FROM MyDirectory WHERE FilePath = '/documents/doc.txt'", 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-ftpedataplot'

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 FTP data and configure the app layout.

trace = go.Bar(x=df.Filesize, y=df.Filename, name='Filesize')

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='FTP MyDirectory 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 FTP data.

python ftp-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for FTP to start building Python apps with connectivity to FTP data. Reach out to our Support Team if you have any questions.

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.ftp as mod
import plotly.graph_objs as go

cnxn = mod.connect("RemoteHost=MyFTPServer;")

df = pd.read_sql("SELECT Filesize, Filename FROM MyDirectory WHERE FilePath = '/documents/doc.txt'", cnxn)
app_name = 'dash-ftpdataplot'

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.Filesize, y=df.Filename, name='Filesize')

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='FTP MyDirectory Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)