PySnooper
16,572
Stars
971
Forks
226
Watchers
36
Open Issues
MIT
许可证
Python
语言
2019-04-18
创建时间
2026-06-08
最近更新
项目能做什么
让你无需再用 print 进行调试的 Python 实用调试工具。
来源:基于仓库元数据
· 内容以仓库实际 README 为准
使用说明 查看原始 README 原仓库文档
中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
# PySnooper - Never use print for debugging again
**PySnooper** is a poor man's debugger. If you've used Bash, it's like `set -x` for Python, except it's fancier.
Your story: You're trying to figure out why your Python code isn't doing what you think it should be doing. You'd love to use a full-fledged debugger with breakpoints and watches, but you can't be bothered to set one up right now.
You want to know which lines are running and which aren't, and what the values of the local variables are.
Most people would use `print` lines, in strategic locations, some of them showing the values of variables.
**PySnooper** lets you do the same, except instead of carefully crafting the right `print` lines, you just add one decorator line to the function you're interested in. You'll get a play-by-play log of your function, including which lines ran and when, and exactly when local variables were changed.
What makes **PySnooper** stand out from all other code intelligence tools? You can use it in your shitty, sprawling enterprise codebase without having to do any setup. Just slap the decorator on, as shown below, and redirect the output to a dedicated log file by specifying its path as the first argument.
## Example
We're writing a function that converts a number to binary, by returning a list of bits. Let's snoop on it by adding the `@pysnooper.snoop()` decorator:
```python
import pysnooper
@pysnooper.snoop()
def number_to_bits(number):
if number:
bits = []
while number:
number, remainder = divmod(number, 2)
bits.insert(0, remainder)
return bits
else:
return [0]
number_to_bits(6)
```
The output to stderr is:

Or if you don't want to trace an entire function, you can wrap the relevant part in a `with` block:
```python
import pysnooper
import random
def foo():
lst = []
for i in range(10):
lst.append(random.randrange(1, 1000))
with pysnooper.snoop():
lower = min(lst)
upper = max(lst)
mid = (lower + upper) / 2
print(lower, mid, upper)
foo()
```
which outputs something like:
```
New var:....... i = 9
New var:....... lst = [681, 267, 74, 832, 284, 678, ...]
09:37:35.881721 line 10 lower = min(lst)
New var:....... lower = 74
09:37:35.882137 line 11 upper = max(lst)
New var:....... upper = 832
09:37:35.882304 line 12 mid = (lower + upper) / 2
74 453.0 832
New var:....... mid = 453.0
09:37:35.882486 line 13 print(lower, mid, upper)
Elapsed time: 00:00:00.000344
```
## Features
If stderr is not easily accessible for you, you can redirect the output to a file:
```python
@pysnooper.snoop('/my/log/file.log')
```
You can also pass a stream or a callable instead, and they'll be used.
See values of some expressions that aren't local variables:
```python
@pysnooper.snoop(watch=('foo.bar', 'self.x["whatever"]'))
```
Show snoop lines for fu
阅读完整原文
商业机会分析 规则生成(AI 未配置)
综合评分 60.2 分。该项目在“个人可实施性”维度得 60 分,“付费可能性”维度得 40.0 分,差异化空间 100.0 分(评分依据见评分卡)。
将 PySnooper 改造为垂直场景 SaaS
| 产品构想 | 保留核心能力,针对某一类用户(如某行业团队)做托管版,收取月费。 |
| 目标用户 | 有该需求的中小团队 / 独立站长 |
| 难度/周期 | 中 · 2~4 周(MVP) |
| 收费模式 | 订阅制(如 ¥29~99/月) |
| 竞争风险 | 需验证付费意愿;注意许可证合规 |
| 依据 | 数据支持的判断:许可证与关键词显示存在商用与付费场景 |
面向细分需求的二次开发产品
| 产品构想 | 基于 PySnooper 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。 |
| 目标用户 | 该细分场景用户 |
| 难度/周期 | 中 · 2~6 周 |
| 收费模式 | 买断制 / 订阅制 / 广告 |
| 竞争风险 | 细分需求规模需验证 |
| 依据 | AI 推测:基于项目主题标签的判断 |
封装为在线小工具或 API 服务
| 产品构想 | 把项目最常用的一个功能做成网页小工具,靠流量变现或按量计费。 |
| 目标用户 | 搜索引擎带来的长尾用户 |
| 难度/周期 | 低 · 1~3 周 |
| 收费模式 | 免费引流 + 增值功能 / API 按量计费 |
| 竞争风险 | 同质化竞争,需做好 SEO |
| 依据 | AI 推测:基于技术栈与部署特征的判断 |
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心
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以上为通过 GitHub 官方 Search API 检索的相似项目,功能差异与优劣势需进一步人工确认,配置 AI 后可生成对比分析。
项目优势与风险
| 技术成熟度 | 创建于 2019-04-18,最近推送 2026-06-08,发布过 1 个 Release |
| 社区活跃 | Star 16,572 / Fork 971 / Issue 36(数据支持,可自行核实) |
| 许可证 | MIT |
| 主要风险 | 上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价 |
安装与使用
快速开始(以仓库 README 为准)
git clone https://github.com/cool-RR/PySnooper.git cd PySnooper # 请阅读仓库 README 获取确切安装步骤(依赖、配置、启动命令)
术语说明:Docker=应用容器(把程序和依赖打包运行);API Key=调用外部服务的密钥;Git Clone=把仓库代码下载到本地。常见错误:API Key 未配置 / 端口占用 / 数据库连接失败,多数项目在 README 的 Troubleshooting 章节有说明。