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📌 Reply Statistics

This guide will use the SignalWire Python SDK to get a list of owned DIDs, and compare inbound and outbound messages to provide statistics on reply rate.

The resulting stats.

What do I need to run this?

You will only need the SignalWire Python SDK, and your SignalWire API credentials. If you aren't sure where to find your credentials, check out this guide on naviating your space.

How do I run this code?

Check out our Recipe

🦉 Open Recipe: Get reply statistics for SMS

Run Natively

Run the file in your python environment of choice.

Code Walkthrough

The only file for this snippet will be an file.

Into our application


First we will import our SignalWire python SDK to handle our requests to SignalWire.

from import Client as signalwire_client

Now we can use our SignalWire credentials to create a client

client = signalwire_client(SIGNALWIRE_PROJECT_KEY, SIGNALWIRE_TOKEN, signalwire_space_url=SIGNALWIRE_SPACE)

Setting up our lists and dictionary variables for later use.

replydict will take each message with the message SID as the key, and the message from_ and body as a list of values.

uniqureplies will be our filtered "good" replies list

ournumbers will pull numbers from our project. this could be replaced with a list of phone numbers from a campaign to create a more granular overview of an account with multiple campaigns.

badsmsbody is our list of "bad" words, these could be opt-out phrases, or any other replies you do not want to consider useful to count in your statistics

badsmsnumbers is a list of the phone numbers who have sent "bad" replies.

sentmsgcount will count the the outbound messages sent from ournumbers

sentmsgscount = 0

List ournumbers

Now that we are done with our setup we can begin by populating our list of phone numbers.

response = client.incoming_phone_numbers.list()
for sid in response:

List messages

Then we can call a list of all messages. You could filter these messages by passing arguments to client.messages.list().

For each message we get from this call, we will check if the message is from one of ournumbers
and increment sentmsgscount

Then we will check the message body and append bad messages to our badsmsnumbers list.

Then, if the message is not from ournumbers, and is to ournumbers. We ensure that the message is not "bad", and is a unique entry to our uniquereplies list.
Additionally we will add all replies regardless of if they are unique to our replydict.

response = client.messages.list()
for message in response:
if message.from_ in ournumbers:
sentmsgscount = sentmsgscount+1
if message.body in badsmsbody and message.from_ not in ournumbers:
if message.from_ not in ournumbers and in ournumbers:
if message.body not in badsmsbody and message.from_ not in uniquereplies:
replydict[message.sid] = [message.from_,message.body]

Data formatting

Finally, we will do some calculations, and format our data so it can be printed to the console.

replycount = len(replydict)
uniquecount = len(uniquereplies)
badcount = len(badsmsnumbers)
replypercent = (replycount/sentmsgscount)*100
sentmsgscount = str(sentmsgscount)

print ("You sent "+str(sentmsgscount)+ " messages")
print("You recieved " + str(replycount) + " Replies")
print(str(uniquecount) + " Unique User Replied")
print(str(badcount)+ " Stop or other bad replies")
print("Your reply rate is " + str(replypercent)+ "%")

An example of output would be printed to the console like so:

You sent 60 messages
You recieved 11 Replies
1 Unique User Replied
0 Stop or other bad replies
Your reply rate is 18.333333333333332%


This guide provides a basic application to gather statistics on sms replies using the SignalWire python SDK. While this is a basic implementation it can be a powerful tool to implement into more in-depth reporting systems for your SignalWire usage.


Python SignalWire SDK

Sign Up Here

If you would like to test this example out, you can create a SignalWire account and space here.

Please feel free to reach out to us on our Community Slack or create a Support ticket if you need guidance!