在 Manus 中运行任何 Skill
一键导入
一键导入
一键在 Manus 中运行任何 Skill
开始使用structlog
Structured logging for Python applications with context support and powerful processors
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更新时间2025年10月23日 16:27
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Structured logging for Python applications with context support and powerful processors
Database migration management for SQLAlchemy projects using Alembic
Advanced Python Scheduler - Task scheduling and job queue system
Build async APIs with FastAPI, including endpoints, dependency injection, validation, and testing. Use when creating REST APIs, web backends, or microservices.
Data validation and settings management using Python type annotations with Pydantic v2
ASGI server for Python web applications - Fast, production-ready server for async frameworks
Promise-based HTTP client for making requests from browser and Node.js
| name | structlog |
| description | Structured logging for Python applications with context support and powerful processors |
| when_to_use | When you need structured logging with context, JSON output, or enhanced logging capabilities for Python applications |
import structlog
# Basic usage
log = structlog.get_logger()
log.info("hello, %s!", "world", key="value", more_than_strings=[1, 2, 3])
import structlog
structlog.configure(
processors=[
structlog.contextvars.merge_contextvars,
structlog.processors.add_log_level,
structlog.processors.StackInfoRenderer(),
structlog.dev.set_exc_info,
structlog.processors.TimeStamper(fmt="%Y-%m-%d %H:%M:%S", utc=False),
structlog.dev.ConsoleRenderer()
],
wrapper_class=structlog.make_filtering_bound_logger(logging.NOTSET),
context_class=dict,
logger_factory=structlog.PrintLoggerFactory(),
cache_logger_on_first_use=False
)
import structlog
# Configure for JSON output
structlog.configure(
processors=[structlog.processors.JSONRenderer()]
)
log = structlog.get_logger()
log.info("Processing request", request_id="req-123", user_id=456)
# Output: {"event": "Processing request", "request_id": "req-123", "user_id": 456}
import logging
import structlog
# Configure standard logging
logging.basicConfig(
format="%(message)s",
stream=sys.stdout,
level=logging.INFO
)
# Configure structlog to use standard library
structlog.configure(
processors=[
structlog.stdlib.filter_by_level,
structlog.stdlib.add_logger_name,
structlog.stdlib.add_log_level,
structlog.stdlib.PositionalArgumentsFormatter(),
structlog.processors.StackInfoRenderer(),
structlog.processors.format_exc_info,
structlog.stdlib.render_to_log_kwargs,
],
context_class=dict,
logger_factory=structlog.stdlib.LoggerFactory(),
wrapper_class=structlog.stdlib.BoundLogger,
cache_logger_on_first_use=True,
)
import structlog
log = structlog.get_logger()
# Bind context that persists across log calls
request_log = log.bind(request_id="req-789", user="alice")
request_log.info("Processing started")
request_log.info("Database query executed", query="SELECT * FROM users")
request_log.info("Processing completed")
# Output includes request_id and user in all log entries
import time
def add_custom_context(logger, log_method, event_dict):
"""Add custom context to every log entry"""
event_dict["custom_field"] = "custom_value"
event_dict["timestamp"] = time.time()
return event_dict
structlog.configure(
processors=[
add_custom_context,
structlog.processors.JSONRenderer()
]
)
import structlog
structlog.configure(
processors=[
structlog.processors.dict_tracebacks,
structlog.processors.JSONRenderer(),
],
)
log = structlog.get_logger()
try:
1 / 0
except ZeroDivisionError:
log.exception("Division error occurred")
import pytest
import structlog
from structlog.testing import LogCapture
@pytest.fixture
def log_output():
return LogCapture()
@pytest.fixture(autouse=True)
def configure_structlog(log_output):
structlog.configure(
processors=[log_output]
)
def test_logging(log_output):
log = structlog.get_logger()
log.info("test message", key="value")
assert len(log_output.entries) == 1
assert log_output.entries[0]["event"] == "test message"
assert log_output.entries[0]["key"] == "value"
import structlog
structlog.configure(
processors=[
structlog.stdlib.filter_by_level,
structlog.stdlib.add_logger_name,
structlog.stdlib.add_log_level,
structlog.stdlib.PositionalArgumentsFormatter(),
structlog.processors.TimeStamper(fmt="iso"),
structlog.processors.StackInfoRenderer(),
structlog.processors.format_exc_info,
structlog.processors.UnicodeDecoder(),
structlog.processors.JSONRenderer()
],
context_class=dict,
logger_factory=structlog.stdlib.LoggerFactory(),
wrapper_class=structlog.stdlib.BoundLogger,
cache_logger_on_first_use=True,
)
import logging.config
import structlog
timestamper = structlog.processors.TimeStamper(fmt="%Y-%m-%d %H:%M:%S")
pre_chain = [
structlog.stdlib.add_log_level,
structlog.stdlib.ExtraAdder(),
timestamper,
]
logging.config.dictConfig({
"version": 1,
"disable_existing_loggers": False,
"formatters": {
"plain": {
"()": structlog.stdlib.ProcessorFormatter,
"processors": [
structlog.stdlib.ProcessorFormatter.remove_processors_meta,
structlog.dev.ConsoleRenderer(colors=False),
],
"foreign_pre_chain": pre_chain,
},
"colored": {
"()": structlog.stdlib.ProcessorFormatter,
"processors": [
structlog.stdlib.ProcessorFormatter.remove_processors_meta,
structlog.dev.ConsoleRenderer(colors=True),
],
"foreign_pre_chain": pre_chain,
},
},
"handlers": {
"default": {
"level": "DEBUG",
"class": "logging.StreamHandler",
"formatter": "colored",
},
"file": {
"level": "DEBUG",
"class": "logging.handlers.WatchedFileHandler",
"filename": "app.log",
"formatter": "plain",
},
},
"loggers": {
"": {
"handlers": ["default", "file"],
"level": "DEBUG",
}
}
})