The Python SDK
Important
This article relates to both journy.io's SDKs and Twilio Segment SDKs.
Check out also our journy.io developers documentation -- https://developers.journy.io/
Topics
journy.io’s Python library lets you record data from your platform, from your Python code.
All of journy.io’s server-side libraries are built for high-performance, so you can use them in your web server controller code. This library uses an internal queue to make identify
and track
calls non-blocking and fast. It also batches messages and flushes asynchronously to journy.io’s servers.
Getting started
Make sure you’re using a version of Python that’s 14 or higher.
Run the relevant command to add journy.io’s Python library module to your
package.json
.pip install segment-analytics-python
Initialize the
Analytics
constructor the module exposes with your journy.io SDK connector Write Key, like so:import segment.analytics as analytics analytics.write_key = "YOUR_WRITE_KEY" analytics.host = "https://analyze.journy.io/backend"
Be sure to replace YOUR_WRITE_KEY
with your actual Write Key which you can find in journy.io by navigating to: Connections > API/SDK Connector and selecting the source tab and going to the Python tab.
This creates an instance of Analytics
that you can use to send data to journy.io for your project. The default initialization settings are production-ready and queue 20 messages before sending any requests.
There is an option in journy.io to set a proxy ("Use proxy domain") so traffic flows through your own domain. In that case, host
will have another value, pointing to your own domain.
Basic tracking methods
The basic tracking methods below serve as the building blocks of your journy.io tracking. They include Identify, Group, Track, and Page.
These methods correspond with those used in the journy.io Spec. The documentation on this page explains how to use these methods in Python.
Identify
For any of the different methods described on this page, you can replace the properties and traits in the code samples with variables that represent the data collected.
identify
lets you tie a user to their actions and record traits about them. It includes a unique User ID and/or anonymous ID, and any optional traits you know about them.
journy.io recommends that you make an identify
call:
After a user first registers
After a user logs in
When a user updates their info (for example, they change or add a new address)
Example of an identify
call for an identified user Elon Musk:
analytics.identify(
user_id="abc123", # Elon Musk — unique Id from database
traits={
"firstname": "Elon",
"lastname": "Musk",
"email": "elon.musk@tesla.com",
"friends": 24 }
)
The call above identifies Elon by his unique User ID (the one you know him by in your database), and labels him with the firstname
, lastname
, email
, and friends
traits.
The identify
call has the following fields:
FIELD | DESCRIPTION |
| The ID for this user in your database. |
| A dict of traits you know about the user. Things like: |
| A dict containing any context about the request. To see the full reference of supported keys, check them out in the context reference |
| A |
| An anonymous session ID for this user. |
| A dictionary of destinations to enable or disable |
Identifying users happen incremental: You can identify users with a subset of traits
; and later make another identify call with another subset of traits
. The result of both identify calls will be the union of all traits
.
To delete a traits
, you have to add them to the identify
call with value null:
Find details on the identify method payload in journy.io’s Identify Spec.
Group
group
lets you associate an identified user with a group. A group could be a company, organization, account, project or team! It also lets you record custom traits about the group, like industry or number of employees.
journy.io recommends that you make a group
call:
After a user first registers, entering its company details.
After a user logs in. Make a group call for each account the user is part of.
When a user updates their info, make a group call for each account the user is part of.
Example group
call, adding user Elon Musk to account Tesla, as an 'admin':
The group
call has the following fields:
FIELD | DESCRIPTION |
| The ID for the user that is a part of the group. |
| The ID of the group. |
| A dict of traits you know about the group. For a company, they might be things like |
| A dict containing any context about the request. To see the full reference of supported keys, check them out in the context reference |
| A |
| An anonymous session ID for this user. |
| A dictionary of destinations to enable or disable |
To identify a group, without adding a user, you can use anonymousId
with the same value of the groupId
. It goes like this:
Group-calling accounts happen incremental: You can identify users with a subset of traits
; and later make another identify call with another subset of traits
. The result of both identify calls will be the union of all traits
.
To delete a traits
, you have to add them to the group
call with a null reference:
Find more details about group
, including the group
payload, in the journy.io Spec.
Track
track
lets you record the actions your users perform, optionally within the context of an account. Every action triggers what we call an “event”, which can also have associated event metadata.
You’ll want to track events that are indicators of success for your site, like Signed Up, Item Purchased or Article Bookmarked.
To get started, we recommend tracking just a few important events. You can always add more later!
Example identified track
call by a user Elon Musk:
B2B example identified track
call by a user Elon Musk in the context of account Tesla, back on Dec 12th 2015:
This example track
call tells us that Elon Musk triggered the Car Sold event with a revenue of $39999.99 and chose your hypothetical ‘200-day’ shipping, back on Dec 12th 2015.
track
event metadata ( properties
) can be anything you want to record. In this case, revenue and shipping method.
The track
call has the following fields:
FIELD | DESCRIPTION |
| The ID for this user in your database. |
| The name of the event you’re tracking. Use human-readable names like Song Played or Status Updated. |
| A dictionary of properties for the event. If the event was Product Added, it might have properties like |
| A dict containing any context about the request. To see the full reference of supported keys, check them out in the context reference |
| A |
| An anonymous session ID for this user. |
| A dictionary of destinations to enable or disable |
Find details on best practices in event naming as well as the track
method payload in the journy.io Spec.
Page
The page
method lets you record page views on your website, along with optional extra information about the page being viewed. It is also user to record screen views in your app/on your platform.
If you’re using our client-side set up in combination with the Python library, page calls are already tracked for you by default. However, if you want to record your own page views manually and aren’t using our client-side library, read on!
Example page
call, where a user Elon Musk visits the pricing page:
B2B example page
call, where a user Elon Musk visits the pricing page, when being in account Tesla, back on Dec 12th 2015:
The page
call has the following fields:
FIELD | DESCRIPTION |
| The ID for the user that is a part of the group. |
| The category of the page. Useful for things like ecommerce where many pages often live under a larger category. |
| The name of the page, for example Signup or Home. |
| The page properties. To see a reference of reserved page properties, see the spec here. |
| A dict containing any context about the request. To see the full reference of supported keys, check them out in the context reference |
| A |
| An anonymous session ID for this user. |
| A dictionary of destinations to enable or disable |
Find details on the page
payload in the journy.io Spec.
Additional configuration in development mode
In development, Segment recommends that you enable the following settings to help spot problems:
analytics.debug
to log debugging information to the Python loggeran
on_error
handler to print the response you receive from Segment’s API.
If you don’t want to send information to Segment during testing, add the following code to your test: