The AWS X-Ray SDK for Python (the SDK) enables Python developers to record and emit information from within their applications to the AWS X-Ray service.
Project description
AWS X-Ray SDK for Python
Installing
The AWS X-Ray SDK for Python is compatible with Python 2.7, 3.4, 3.5, and 3.6.
Install the SDK using the following command (the SDK’s non-testing dependencies will be installed).
pip install aws-xray-sdk
To install the SDK’s testing dependencies, use the following command.
pip install tox
Getting Help
Use the following community resources for getting help with the SDK. We use the GitHub issues for tracking bugs and feature requests.
Ask a question in the AWS X-Ray Forum.
Open a support ticket with AWS Support.
If you think you may have found a bug, open an issue.
Opening Issues
If you encounter a bug with the AWS X-Ray SDK for Python, we want to hear about it. Before opening a new issue, search the existing issues to see if others are also experiencing the issue. Include the version of the AWS X-Ray SDK for Python, Python language, and botocore/boto3 if applicable. In addition, include the repro case when appropriate.
The GitHub issues are intended for bug reports and feature requests. For help and questions about using the AWS SDK for Python, use the resources listed in the Getting Help section. Keeping the list of open issues lean helps us respond in a timely manner.
Documentation
The developer guide provides in-depth guidance about using the AWS X-Ray service. The API Reference provides guidance for using the SDK and module-level documentation.
Quick Start
Configuration
from aws_xray_sdk.core import xray_recorder
xray_recorder.configure(
sampling=False,
context_missing='LOG_ERROR',
plugins=('EC2Plugin', 'ECSPlugin', 'ElasticBeanstalkPlugin'),
daemon_address='127.0.0.1:3000',
dynamic_naming='*mysite.com*'
)
Start a custom segment/subsegment
from aws_xray_sdk.core import xray_recorder
# Start a segment
segment = xray_recorder.begin_segment('segment_name')
# Start a subsegment
subsegment = xray_recorder.begin_subsegment('subsegment_name')
# Add metadata or annotation here if necessary
segment.put_metadata('key', dict, 'namespace')
subsegment.put_annotation('key', 'value')
xray_recorder.end_subsegment()
# Close the segment
xray_recorder.end_segment()
Capture
from aws_xray_sdk.core import xray_recorder
@xray_recorder.capture('subsegment_name')
def myfunc():
# Do something here
myfunc()
from aws_xray_sdk.core import xray_recorder
@xray_recorder.capture_async('subsegment_name')
async def myfunc():
# Do something here
async def main():
await myfunc()
Adding annotations/metadata using recorder
from aws_xray_sdk.core import xray_recorder
# Start a segment if no segment exist
segment1 = xray_recorder.begin_segment('segment_name')
# This will add the key value pair to segment1 as it is active
xray_recorder.put_annotation('key', 'value')
# Start a subsegment so it becomes the active trace entity
subsegment1 = xray_recorder.begin_subsegment('subsegment_name')
# This will add the key value pair to subsegment1 as it is active
xray_recorder.put_metadata('key', 'value')
if xray_recorder.is_sampled():
# some expensitve annotations/metadata generation code here
val = compute_annotation_val()
metadata = compute_metadata_body()
xray_recorder.put_annotation('mykey', val)
xray_recorder.put_metadata('mykey', metadata)
Trace AWS Lambda functions
from aws_xray_sdk.core import xray_recorder
def lambda_handler(event, context):
# ... some code
subsegment = xray_recorder.begin_subsegment('subsegment_name')
# Code to record
# Add metadata or annotation here, if necessary
subsegment.put_metadata('key', dict, 'namespace')
subsegment.put_annotation('key', 'value')
xray_recorder.end_subsegment()
# ... some other code
Trace ThreadPoolExecutor
import concurrent.futures
import requests
from aws_xray_sdk.core import xray_recorder
from aws_xray_sdk.core import patch
patch(('requests',))
URLS = ['http://www.amazon.com/',
'http://aws.amazon.com/',
'http://example.com/',
'http://www.bilibili.com/',
'http://invalid-domain.com/']
def load_url(url, trace_entity):
# Set the parent X-Ray entity for the worker thread.
xray_recorder.set_trace_entity(trace_entity)
# Subsegment captured from the following HTTP GET will be
# a child of parent entity passed from the main thread.
resp = requests.get(url)
# prevent thread pollution
xray_recorder.clear_trace_entities()
return resp
# Get the current active segment or subsegment from the main thread.
current_entity = xray_recorder.get_trace_entity()
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
# Pass the active entity from main thread to worker threads.
future_to_url = {executor.submit(load_url, url, current_entity): url for url in URLS}
for future in concurrent.futures.as_completed(future_to_url):
url = future_to_url[future]
try:
data = future.result()
except Exception:
pass
Patch third-party libraries
from aws_xray_sdk.core import patch
libs_to_patch = ('boto3', 'mysql', 'requests')
patch(libs_to_patch)
Add Django middleware
In django settings.py, use the following.
INSTALLED_APPS = [
# ... other apps
'aws_xray_sdk.ext.django',
]
MIDDLEWARE = [
'aws_xray_sdk.ext.django.middleware.XRayMiddleware',
# ... other middlewares
]
Add Flask middleware
from aws_xray_sdk.core import xray_recorder
from aws_xray_sdk.ext.flask.middleware import XRayMiddleware
app = Flask(__name__)
xray_recorder.configure(service='fallback_name', dynamic_naming='*mysite.com*')
XRayMiddleware(app, xray_recorder)
Working with aiohttp
Adding aiohttp middleware. Support aiohttp >= 2.3.
from aiohttp import web
from aws_xray_sdk.ext.aiohttp.middleware import middleware
from aws_xray_sdk.core import xray_recorder
from aws_xray_sdk.core.async_context import AsyncContext
xray_recorder.configure(service='fallback_name', context=AsyncContext())
app = web.Application(middlewares=[middleware])
app.router.add_get("/", handler)
web.run_app(app)
Tracing aiohttp client. Support aiohttp >=3.
from aws_xray_sdk.ext.aiohttp.client import aws_xray_trace_config
async def foo():
trace_config = aws_xray_trace_config()
async with ClientSession(loop=loop, trace_configs=[trace_config]) as session:
async with session.get(url) as resp
await resp.read()
Use SQLAlchemy ORM
The SQLAlchemy integration requires you to override the Session and Query Classes for SQL Alchemy
SQLAlchemy integration uses subsegments so you need to have a segment started before you make a query.
from aws_xray_sdk.core import xray_recorder
from aws_xray_sdk.ext.sqlalchemy.query import XRaySessionMaker
xray_recorder.begin_segment('SQLAlchemyTest')
Session = XRaySessionMaker(bind=engine)
session = Session()
xray_recorder.end_segment()
app = Flask(__name__)
xray_recorder.configure(service='fallback_name', dynamic_naming='*mysite.com*')
XRayMiddleware(app, xray_recorder)
Add Flask-SQLAlchemy
from aws_xray_sdk.core import xray_recorder
from aws_xray_sdk.ext.flask.middleware import XRayMiddleware
from aws_xray_sdk.ext.flask_sqlalchemy.query import XRayFlaskSqlAlchemy
app = Flask(__name__)
app.config["SQLALCHEMY_DATABASE_URI"] = "sqlite:///:memory:"
XRayMiddleware(app, xray_recorder)
db = XRayFlaskSqlAlchemy(app)
License
The AWS X-Ray SDK for Python is licensed under the Apache 2.0 License. See LICENSE and NOTICE.txt for more information.
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