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Streamlit: Building an Email Dashboard

Blag aka Alvaro Tejada Galindo

Using Python and Streamlit with the help of Nylas, create an email dashboard to get insights on your inbox.

Streamlit: Building an Email Dashboard

Have you read our blog post, Shiny for Python: Building an Email Dashboard or watched our livestream Shiny for Python: Building an Email Dashboard but you’re looking for something else to build your dashboard using Python? How about an email dashboard using Streamlit?

We’re going to use Streamlit, a pure Python package that allows you to create data scripts into web apps in minutes.

What are we going to do today?

  • Is your system ready?
  • Installing additional packages
  • What are we going to build?
  • What does our dashboard look like?
  • Let’s start building

Is your system ready?

If you don’t have the Nylas Python SDK installed and your environment isn’t configured, I would recommend you to read the post How to Send Emails with the Nylas Python SDK where everything is clearly explained.

Installing additional packages

Having the Nylas Python SDK installed and configured is important, but it’s not all we need. We need to install some additional packages, especially Streamlit:

$ pip3 install streamlit # Streamlit
$ pip3 install matplotlib # Library for creating static, animated, and interactive visualizations
$ pip3 install pandas as pd # Python data analysis library

What are we going to build?

Before moving on with the blog, we should take a look at what we are going to build, which is pretty much, a dashboard. This dashboard will use the Nylas Python SDK ability to access our email account and read the first hundred emails from our inbox and the first hundred emails from our sent folder.

With this information, we’re going to get the names of the 3 top people that we email from, the names of the top 3 people who we send emails to and finally, we’re going to generate a word cloud, using all the words gathered from the subjects of the emails in our inbox, that is, what are the most important words that people email us about.

What does our dashboard look like?

Here we go:

Streamlit email dashboard

We have a slider, with two bar plots and a word cloud. 

Let’s start building

First, we need to a file called streamlit_email_dashboard.py and enter the following code:

# Load your env variables
from dotenv import load_dotenv
load_dotenv()

# Import your dependencies
from nylas import APIClient
import streamlit as st
from wordcloud import WordCloud
import os
import pandas as pd
import altair as alt
import matplotlib.pyplot as plt

# Initialize your Nylas API client
nylas = APIClient(
    os.environ.get("CLIENT_ID"),
    os.environ.get("CLIENT_SECRET"),
    os.environ.get("ACCESS_TOKEN")
)

# Auxiliar variables
from_messages = []
to_messages = []
text = ""

st.title('Email Dashboard')
num = st.slider('How many emails?', 1, 200, 50)

# Get emails from your inbox folder
f_messages = nylas.messages.where(in_='inbox', limit = num)
# Get emails from your sent folder
t_messages = nylas.messages.where(in_='sent', limit = num)

# Loop through your inbox emails
for msg in f_messages:
	# Get the name of the person emailing you
	if(msg["from_"][0]["name"] != ""):
		from_messages.append(msg["from_"][0]["name"].split()[0])
	# Concatate the subjects of all emails
	text = text + " " + msg["subject"]
# Turn the array into a data frame	
f_df = pd.DataFrame(from_messages, columns=['Names'])
# Aggregate values, get the top 3 and a name to the new column
top_3_from = f_df["Names"].value_counts().head(3).reset_index(name="count")
top_3_from.columns = ['person', 'count']

# Loop through your sent emails
for msg in t_messages:
	# Get the name of the person you're emailing	
	if(msg["to"][0]["name"] != ""):	
		to_messages.append(msg["to"][0]["name"].split()[0])
# Turn the array into a data frame		
t_df = pd.DataFrame(to_messages, columns=['Names'])
# Aggregate values, get the top 3 and a name to the new column
top_3_to = t_df["Names"].value_counts().head(3).reset_index(name="count")
top_3_to.columns = ['person', 'count']

# Using all the email subjects, generate a wordcloud
wordcloud = WordCloud(width=800, height=300).generate(text)

# Create columns layout
col1, col2 = st.columns(2)
with col1:
    # Create barchart from emails
    bar_chart = alt.Chart(top_3_from).mark_bar().encode(
    alt.X('person', title='person'),
    alt.Y('count', title='count'),
    color='person:N'
    ).properties(
        title='From: Emails'
    )
    # Display the barchart
    st.altair_chart(bar_chart, use_container_width=True)
with col2:
    # Create barchart to emails
    bar_chart = alt.Chart(top_3_to).mark_bar().encode(
    alt.X('person', title='person'),
    alt.Y('count', title='count'),
    color='person:N'
    ).properties(
        title='To: Emails'
    )
    # Display the barchart
    st.altair_chart(bar_chart, use_container_width=True)

# Display the generated image:
fig, ax = plt.subplots(figsize = (12, 8))
ax.imshow(wordcloud)
plt.axis("off")
st.pyplot(fig)

To run it, we can simply go to the terminal and type:

$ streamlit run streamlit_email_dashboard.py
Running our Streamlit email dashboard

Our application will be running on port 8510 of localhost, so we just need to wait until it opens itself or open our favourite browser and go to the following address:

http://localhost:8510

We had easily and elegantly developed our Email Dashboard using Python and Streamlit.

To learn more about our Email APIs, please go to our documentation Email API Overview.

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