Python实现分布式调用追踪:Span与Trace核心原理及代码解析

沿途有光
沿途有光
发布时间:2026-10-14| 4人浏览过
原创

本文介绍分布式追踪中的核心概念,包括Trace(追踪)、Span(跨度)及Span Context(跨度上下文)。通过Python代码示例,展示如何利用上下文管理器实现简单的调用追踪功能,记录服务间请求的时间、ID及父子关系,并提及后续结合Redis进行结果存储与分析的计划。

分布式追踪核心概念解析

在分布式系统中进行追踪时,主要涉及以下核心概念:

  • 追踪(Trace):指由多个分布式的微服务协同完成的一个完整事务。一个完整的追踪包含了为该事务提供支持的各个服务请求。
  • 跨度(Span):代表事务中的一个具体工作流单元。每个Span包含时间戳、日志以及标签信息。Span之间存在父子关系,或者主从(Followup)关系。
  • 跨度上下文(Span Context):这是支撑分布式追踪的关键机制,它允许在调用的服务之间传递状态。上下文内容通常包括:从上游服务传递到下游服务的时间、追踪ID(Trace ID)、Span ID以及其他需要从上游传递到下游的额外信息。

Python调用追踪代码实现

基于上述概念,我实现了一种简单的调用追踪方案。


import uuid
import os
import time
l = []
class Recorder(object):
  def __init__(self,servername,root_span = None):
    if root_span == None:
      self.__span = Span(servername)
    else:
      self.__span = Span(servername,root_span)
  #上下文管理器
  def __enter__(self):
    return self.__span

  # 退出方法中,用来实现善后处理工作
  def __exit__(self, exc_type, exc_val, exc_tb):
    self.__span.record()
    self.__span.record_save(self.__span.span)
class Span(object):
  def __init__(self,servername,root_span = None):
    self.servername = servername
    self.span = self.newspan()
    if root_span != None:
      root_span.dic['child_span'] = self.span
      self.span["root_span_flag"] = False
  def newspan(self):
    self.dic = {
      "spanid": uuid.uuid4().int,
      "servername": self.servername,
      "location": "",
      "ip": "",
      "durationtime": 0,
      "starttime": time.time(),
      "endtime":0,
      "tag": "",
      "log": "",
      "root_span_flag":True,
      "child_span": ""
    }
    return self.dic

  def record_save(self, span):
    currenttracer = {"id": span["spanid"], "data": span}
    print(currenttracer)
    l.append(currenttracer)

  def record(self):
    self.span["servername"] = self.servername
    self.span["location"] = os.getcwd() + "." + self.servername
    self.span["endtime"] = time.time()
    self.span["durationtime"] = self.span["endtime"] - self.span["starttime"]

  def setspantag(self,tag):
    self.span["tag"] = tag

  def setspanlog(self,log):
    self.span["log"] = log

# 连续调用
with Recorder('server1') as span:
  time.sleep(1)
  span.setspantag("test")
  #调用server1方法
  print("server1")
  with Recorder('server2',span) as span1:
    time.sleep(2)
    # 调用server2方法
    print("server2")
    with Recorder('server3',span1) as span2:
      time.sleep(0.5)
      # 调用server3方法
      print("server3")
#单独调用记录
with Recorder('server4') as span_test1:
  time.sleep(1.5)
  print("server4")

with Recorder('server5') as span_test2:
  time.sleep(2)
  print("server5")

代码运行结果展示

运行结果如下:


server1
server2
server3
{'id': 224716339449765695394515303164364012192, 'data': {'spanid': 224716339449765695394515303164364012192, 'servername': 'server3', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server3', 'ip': '', 'durationtime': 0.5004403591156006, 'starttime': 1598947338.0551107, 'endtime': 1598947338.555551, 'tag': '', 'log': '', 'root_span_flag': False, 'child_span': None}}
{'id': 254736847532758359233387151739984206570, 'data': {'spanid': 254736847532758359233387151739984206570, 'servername': 'server2', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server2', 'ip': '', 'durationtime': 2.501264810562134, 'starttime': 1598947336.0542862, 'endtime': 1598947338.555551, 'tag': '', 'log': '', 'root_span_flag': False, 'child_span': {'spanid': 224716339449765695394515303164364012192, 'servername': 'server3', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server3', 'ip': '', 'durationtime': 0.5004403591156006, 'starttime': 1598947338.0551107, 'endtime': 1598947338.555551, 'tag': '', 'log': '', 'root_span_flag': False, 'child_span': None}}}
{'id': 91028031631192607088457781914309166266, 'data': {'spanid': 91028031631192607088457781914309166266, 'servername': 'server1', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server1', 'ip': '', 'durationtime': 3.5021069049835205, 'starttime': 1598947335.0534441, 'endtime': 1598947338.555551, 'tag': 'test', 'log': '', 'root_span_flag': True, 'child_span': {'spanid': 254736847532758359233387151739984206570, 'servername': 'server2', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server2', 'ip': '', 'durationtime': 2.501264810562134, 'starttime': 1598947336.0542862, 'endtime': 1598947338.555551, 'tag': '', 'log': '', 'root_span_flag': False, 'child_span': {'spanid': 224716339449765695394515303164364012192, 'servername': 'server3', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server3', 'ip': '', 'durationtime': 0.5004403591156006, 'starttime': 1598947338.0551107, 'endtime': 1598947338.555551, 'tag': '', 'log': '', 'root_span_flag': False, 'child_span': None}}}}
server4
{'id': 103171729522922437998918618387133480096, 'data': {'spanid': 103171729522922437998918618387133480096, 'servername': 'server4', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server4', 'ip': '', 'durationtime': 1.5001769065856934, 'starttime': 1598947338.555551, 'endtime': 1598947340.055728, 'tag': '', 'log': '', 'root_span_flag': True, 'child_span': None}}
server5
{'id': 320091321623887285825256878422834254741, 'data': {'spanid': 320091321623887285825256878422834254741, 'servername': 'server5', 'location': 'D:\\python_protest\\protest\\trace\\trace_main.server5', 'ip': '', 'durationtime': 2.0005736351013184, 'starttime': 1598947340.055728, 'endtime': 1598947342.0563016, 'tag': '', 'log': '', 'root_span_flag': True, 'child_span': None}}

后续优化与展望

关于后续工作,计划使用Redis存储追踪结果,并进行相应的输出分析。

问题修复说明

修复了无法追踪同级调用的问题。


import uuid
import os
import time


l = []
class Recorder(object):
  def __init__(self,servername,root_span = None):
    if root_span == None:
      self.__span = Span(servername)
    else:
      self.__span = Span(servername,root_span)

  #上下文管理器
  def __enter__(self):
    return self.__span

  # 退出方法中,用来实现善后处理工作
  def __exit__(self, exc_type, exc_val, exc_tb):
    self.__span.record()
    self.__span.record_save(self.__span.span)


class Span(object):
  def __init__(self,servername,root_span = None):
    self.servername = servername
    self.span = self.newspan()
    if root_span != None:
      root_span.dic['child_span'].append(self.span)
      self.span["root_span_flag"] = False

  def newspan(self):
    self.dic = {
      "spanid": uuid.uuid4().int,
      "servername": self.servername,
      "location": "",
      "ip": "",
      "durationtime": 0,
      "starttime": time.time(),
      "endtime":0,
      "tag": "",
      "log": "",
      "root_span_flag":True,
      "child_span": []
    }
    return self.dic

  def record_save(self, span):
    currenttracer = {"id": span["spanid"], "data": span}
    print(currenttracer)
    l.append(currenttracer)

  def record(self):
    self.span["servername"] = self.servername
    self.span["location"] = os.getcwd() + "." + self.servername
    self.span["endtime"] = time.time()
    self.span["durationtime"] = self.span["endtime"] - self.span["starttime"]

  def setspantag(self,tag):
    self.span["tag"] = tag

  def setspanlog(self,log):
    self.span["log"] = log



# 连续调用
with Recorder('server1') as span:
  time.sleep(1)
  span.setspantag("test")
  #调用server1方法
  print("server1")
  with Recorder('server2',span) as span1:
    time.sleep(2)
    # 调用server2方法
    print("server2")
    with Recorder('server3',span1) as span2:
      time.sleep(0.5)
      # 调用server3方法
      print("server3")


# 并级连续调用
# with Recorder('server1') as span1:
#   time.sleep(1)
#   span1.setspantag("test")
#   #调用server1方法
#   print("server1")
#   with Recorder('server2',span1) as span2:
#     time.sleep(2)
#     # 调用server2方法
#     print("server2")
#   with Recorder('server3',span1) as span3:
#     time.sleep(0.5)
#     # 调用server3方法
#     print("server3")

# #单独调用记录
# with Recorder('server4') as span_test1:
#   time.sleep(1.5)
#   print("server4")
#
# with Recorder('server5') as span_test2:
#   time.sleep(2)
#   print("server5")

总结

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持本站。

相关标签:

免责声明:本文内容仅供参考,不代表本站观点。转载或引用请注明出处。

Python 相关产品和应用

全部下载
Selenium

Selenium

4.51.0 · Windows

用于浏览器自动化和 Web 测试的 Python 工具。

scikit-learn

scikit-learn

1.9.1 · Windows

常用 Python 机器学习算法与模型评估工具库。

Black

Black

26.10.1 · Windows

强调一致性的 Python 自动代码格式化工具。

Ruff

Ruff

0.17.1 · macOS

由 Rust 编写的高速 Python 代码检查和格式化工具。

pytest

pytest

9.1.1 · Windows

简洁而强大的 Python 自动化测试框架。

FastAPI

FastAPI

0.146.0 · Windows

高性能 Python API 框架,支持类型提示和自动接口文档。

Flask

Flask

3.1.3 · Windows

轻量灵活的 Python Web 应用框架。

Django

Django

6.1.2 · Windows

成熟的 Python Web 框架,适合构建内容站点和业务系统。

Spyder

Spyder

6.1.7 · Windows

面向科学计算与数据分析的 Python 集成开发环境。

SciPy

SciPy

1.18.1 · Windows

面向科学、工程和技术计算的 Python 算法库。