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aws / segment-analytics-python
Install & Compatibility
Where this runs
tested against v2.3.6 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.95 runs
installs and imports cleanly · install 0.0s · import 0.600s · 22.9MB
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 2.4s · import 0.532s · 23MB
21MB installed
● package 21MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
analytics
✓ import segment.analytics as analytics
✗ import analytics
The top-level 'analytics' module in `segment-analytics-python` should be imported as `segment.analytics` to avoid potential naming conflicts with other 'analytics' modules or local files.
Client
✓ from segment.analytics.client import Client
For advanced use cases like sending data to multiple Segment sources, you can initialize a new Client directly with a specific write_key.
This quickstart demonstrates how to initialize the Segment client, identify a user, track an event, record a page view, and associate a user with a group. It includes best practices for handling the `write_key` via environment variables and setting up error handling for development. Remember to replace `YOUR_SEGMENT_WRITE_KEY` or set the `SEGMENT_WRITE_KEY` environment variable.
import os
import segment.analytics as analytics
# It's recommended to set the write_key via an environment variable for security
WRITE_KEY = os.environ.get('SEGMENT_WRITE_KEY', 'YOUR_SEGMENT_WRITE_KEY')
if not WRITE_KEY or WRITE_KEY == 'YOUR_SEGMENT_WRITE_KEY':
print("WARNING: SEGMENT_WRITE_KEY environment variable not set or using placeholder. Analytics calls will not be sent.")
analytics.send = False # Disable sending if key is not set
else:
analytics.write_key = WRITE_KEY
print(f"Segment write_key set: {analytics.write_key[:4]}...{analytics.write_key[-4:]}")
# Configure for development (optional, but recommended to see errors)
analytics.debug = True
def on_error(error, items):
print(f"An error occurred with Segment: {error}. Items: {items}")
analytics.on_error = on_error
# Identify a user
analytics.identify('user-123', {
'name': 'John Doe',
'email': 'john.doe@example.com',
'plan': 'premium'
})
# Track an event
analytics.track('Sign Up Completed', {
'method': 'email',
'plan': 'premium'
})
# Page view (for server-side apps, typically not directly used for web page views)
analytics.page('App Home', {
'path': '/home',
'title': 'Homepage'
})
# Group (associate a user with a group, e.g., a company)
analytics.group('user-123', 'company-456', {
'name': 'Acme Corp',
'industry': 'Software'
})
# Flush any remaining events in the queue
analytics.flush()
print("Segment events sent (or queued if SEND_DISABLED is not set).")
Debug
Known issues
deprecatedThe `segment-analytics-python` library is in maintenance mode. This means it will only receive critical bug fixes and security updates, but no new features. Users should be aware that active development has ceased.fixContinue to use the library for existing integrations, but be aware of the lack of new features. For new projects or if advanced features are required, evaluate other Segment SDKs or consider the implications of a maintenance-only library.
affects: 2.x.x onwards
gotchaEvents are batched and sent asynchronously by default. In development or for scripts that exit quickly, you might not see events sent if `analytics.flush()` or `analytics.shutdown()` are not called, or if `analytics.send = False` is set for testing.fixAlways call `analytics.flush()` or `analytics.shutdown()` at the end of your application's lifecycle or script to ensure all queued events are sent. For development, set `analytics.debug = True` and an `on_error` handler to catch issues.
affects: All versions
breakingIf you were using an older version (1.x) of `analytics-python`, some configurations or imports might have changed in version 2.x. Specifically, the recommended import path is `import segment.analytics as analytics`. Pinning dependencies to `1.X` was recommended to avoid breaking changes in the past.fixReview the official Segment Python library documentation for detailed migration guides if coming from a 1.x version. Ensure imports are updated to `import segment.analytics as analytics` and verify method signatures if you encounter errors.
affects: Migration from 1.x to 2.x
gotchaIncorrectly setting the `write_key` or not setting it at all will result in analytics events not being sent to Segment. Hardcoding the `write_key` directly in code is also a security risk.fixAlways retrieve the Segment `write_key` from a secure environment variable (e.g., `SEGMENT_WRITE_KEY`) and ensure it's correctly assigned to `analytics.write_key`. Validate that the key is present before making analytics calls.
affects: All versions
Errors
Common errors & fixes
ModuleNotFoundError: No module named 'segment.analytics'
The segment-analytics-python library is not installed in the current Python environment or the import path is incorrect.
fixpip install segment-analytics-python
AssertionError: segment.analytics.write_key must be set
The Segment write_key was not configured before attempting to send analytics events, and debug mode is enabled.
fiximport segment.analytics
segment.analytics.write_key = 'YOUR_WRITE_KEY'
TypeError: expected a dictionary of properties to track
The 'properties' argument in a track call was not provided as a dictionary.
fixsegment.analytics.track('User Signed Up', {'plan': 'premium', 'source': 'website'}) ValueError: either user_id or anonymous_id must be provided.
An 'identify' call was made without providing either a 'user_id' or an 'anonymous_id'.
fixsegment.analytics.identify('user_123', {'email': 'test@example.com'}) Upgrade
Version history
2.3.6latest on PyPI · released Apr 7, 2026
Audit
Dependencies
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