SkyWalking-Python: The Python Agent for Apache SkyWalking, which provides the native tracing abilities for Python project.
SkyWalking: an APM(application performance monitor) system, especially designed for microservices, cloud native and container-based (Docker, Kubernetes, Mesos) architectures.
The Python agent module is published to Pypi, from where you can use pip
to install:
# Install the latest version, using the default gRPC protocol to report data to OAP
pip install "apache-skywalking"
# Install the latest version, using the http protocol to report data to OAP
pip install "apache-skywalking[http]"
# Install the latest version, using the kafka protocol to report data to OAP
pip install "apache-skywalking[kafka]"
# Install a specific version x.y.z
# pip install apache-skywalking==x.y.z
pip install apache-skywalking==0.1.0 # For example, install version 0.1.0 no matter what the latest version is
Refer to the FAQ.
SkyWalking Python SDK requires SkyWalking 8.0+ and Python 3.5+.
If you want to try out the latest features that are not released yet, please refer to the guide to build from sources.
By default, SkyWalking Python agent uses gRPC protocol to report data to SkyWalking backend,
in SkyWalking backend, the port of gRPC protocol is 11800
, and the port of HTTP protocol is 12800
,
you should configure collector_address
(or environment variable SW_AGENT_COLLECTOR_BACKEND_SERVICES
)
according to the protocol you want.
For example, if you want to use gRPC protocol to report data, configure collector_address
(or environment variable SW_AGENT_COLLECTOR_BACKEND_SERVICES
) to <oap-ip-or-host>:11800
,
such as 127.0.0.1:11800
:
from skywalking import agent, config
config.init(collector_address='127.0.0.1:11800', service_name='your awesome service')
agent.start()
However, if you want to use HTTP protocol to report data, configure collector_address
(or environment variable SW_AGENT_COLLECTOR_BACKEND_SERVICES
) to <oap-ip-or-host>:12800
,
such as 127.0.0.1:12800
:
Remember you should install
skywalking-python
with extra requireshttp
,pip install "apache-skywalking[http]
.
from skywalking import agent, config
config.init(collector_address='127.0.0.1:12800', service_name='your awesome service')
agent.start()
Finally, if you want to use Kafka protocol to report data, configure kafka_bootstrap_servers
(or environment variable SW_KAFKA_REPORTER_BOOTSTRAP_SERVERS
) to kafka-brokers
,
such as 127.0.0.1:9200
:
Remember you should install
skywalking-python
with extra requireskafka
,pip install "apache-skywalking[kafka]
.
from skywalking import agent, config
config.init(kafka_bootstrap_servers='127.0.0.1:9200', service_name='your awesome service')
agent.start()
Alternatively, you can also pass the configurations via environment variables (such as SW_AGENT_NAME
, SW_AGENT_COLLECTOR_BACKEND_SERVICES
, etc.) so that you don't need to call config.init
.
All supported environment variables can be found here
The Python agent is capable of reporting collected logs to the backend(SkyWalking OAP), enabling Log & Trace Correlation.
Please refer to the Log Reporter Doc for a detailed guide.
There are some built-in plugins (such as http.server
, Flask
, Django
etc.) that support automatic instrumentation of Python libraries, the complete lists can be found here
Apart from the libraries that can be instrumented automatically, we also provide some APIs to enable manual instrumentation.
The code snippet below shows how to create entry span, exit span and local span.
from skywalking import Component
from skywalking.trace.context import SpanContext, get_context
from skywalking.trace.tags import Tag
context: SpanContext = get_context() # get a tracing context
# create an entry span, by using `with` statement,
# the span automatically starts/stops when entering/exiting the context
with context.new_entry_span(op='https://github.com/apache') as span:
span.component = Component.Flask
# the span automatically stops when exiting the `with` context
class TagSinger(Tag):
key = 'Singer'
with context.new_exit_span(op='https://github.com/apache', peer='localhost:8080', component=Component.Flask) as span:
span.tag(TagSinger('Nakajima'))
with context.new_local_span(op='https://github.com/apache') as span:
span.tag(TagSinger('Nakajima'))
from time import sleep
from skywalking import Component
from skywalking.decorators import trace, runnable
from skywalking.trace.context import SpanContext, get_context
@trace() # the operation name is the method name('some_other_method') by default
def some_other_method():
sleep(1)
@trace(op='awesome') # customize the operation name to 'awesome'
def some_method():
some_other_method()
@trace(op='async_functions_are_also_supported')
async def async_func():
return 'asynchronous'
@trace()
async def async_func2():
return await async_func()
@runnable() # cross thread propagation
def some_method():
some_other_method()
from threading import Thread
t = Thread(target=some_method)
t.start()
context: SpanContext = get_context()
with context.new_entry_span(op=str('https://github.com/apache/skywalking')) as span:
span.component = Component.Flask
some_method()
- Submit an issue by using [Python] as title prefix.
- Mail list: dev@skywalking.apache.org. Mail to
dev-subscribe@skywalking.apache.org
, follow the reply to subscribe the mail list. - Join
skywalking
channel at Apache Slack. If the link is not working, find the latest one at Apache INFRA WIKI. - Twitter, ASFSkyWalking
Before submitting a pull request or push a commit, please read our contributing and developer guide.
Check the FAQ page or add the FAQs there.
Apache 2.0