Use Dash to Build to Web Apps on Toggl Data
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas module, and the Dash framework, you can build Toggl-connected web applications for Toggl data. This article shows how to connect to Toggl with the CData Connector and use pandas and Dash to build a simple web app for visualizing Toggl data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Toggl data in Python. When you issue complex SQL queries from Toggl, the driver pushes supported SQL operations, like filters and aggregations, directly to Toggl and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Toggl Data
Connecting to Toggl 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.
Start by setting the Profile connection property to the location of the Toggl Profile on disk (e.g. C:\profiles\Toggl.apip). Next, set the ProfileSettings connection property to the connection string for Toggl (see below).
Toggl API Profile Settings
Obtain your API key from your Toggl account Profile Settings page, where it is listed under the API section.
After installing the CData Toggl Connector, follow the procedure below to install the other required modules and start accessing Toggl 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 Toggl 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.api as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Toggl Connector to create a connection for working with Toggl data.
cnxn = mod.connect("Profile=C:\profiles\Toggl.apip;ProfileSettings='APIKey=your_api_key';")
Execute SQL to Toggl
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, WorkspaceId FROM Clients WHERE IsArchived = 'false'", 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-apiedataplot' 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 Toggl data and configure the app layout.
trace = go.Bar(x=df.Id, y=df.WorkspaceId, 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='Toggl Clients 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 Toggl data.
python api-dash.py
Free Trial & More Information
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Toggl 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.api as mod
import plotly.graph_objs as go
cnxn = mod.connect("Profile=C:\profiles\Toggl.apip;ProfileSettings='APIKey=your_api_key';")
df = pd.read_sql("SELECT Id, WorkspaceId FROM Clients WHERE IsArchived = 'false'", cnxn)
app_name = 'dash-apidataplot'
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.WorkspaceId, 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='Toggl Clients Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)