2026年4月27日 研究日志¶
今日主题：整理目前收集到的样本，绘制样本统计表。本周的主要内容就是这个，目前暂未成型，本周五再进行展示吧。今天来总结一下Jupyter的magic吧！
先和不熟悉的朋友讲一声，Jupyter 的 Magic 指令（Magics）是 IPython 提供的“增强语法”，用于执行系统命令、计时、调试、运行脚本、管理环境等。
它们不是 Python 语法，而是 Notebook 环境的“扩展能力”。所以它们是只有jupyter notebook和相当于进化版的jupyter lab环境中可以使用的魔法哦！
Magic 分两类：
- 行魔法（Line Magics）：以
%开头，只作用于当前行 - 单元魔法（Cell Magics）：以
%%开头，作用于整个 cell
2. %%time — 计时整个 cell¶
用于测量整个 cell的执行时间。
In [1]:
%time sum([i*i for i in range(10_0000)])
CPU times: total: 15.6 ms Wall time: 7.55 ms
Out[1]:
333328333350000
In [2]:
%%time
total = 0
for i in range(10_0000):
total += i*i
total
CPU times: total: 15.6 ms Wall time: 12.3 ms
Out[2]:
333328333350000
3. %timeit — 多次运行取平均¶
适合测量短代码的平均性能。
4. %%timeit — 多次运行整个 cell¶
对整个 cell 做重复计时。
In [3]:
%timeit [i*i for i in range(1000)]
36.1 μs ± 4.73 μs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [4]:
%%timeit
x = []
for i in range(1000):
x.append(i*i)
36.8 μs ± 11.5 μs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
5. %pwd — 查看当前工作目录¶
In [5]:
%pwd
Out[5]:
'C:\\Users\\Admin\\TechBlog'
6. %cd — 切换目录¶
In [10]:
%cd ./data
C:\Users\Admin\TechBlog\data
7. %ls — 列出当前目录文件¶
In [11]:
%ls
Volume in drive C has no label.
Volume Serial Number is 12B8-C7B5
Directory of C:\Users\Admin\TechBlog\data
27/04/2026 17:08 <DIR> .
27/04/2026 17:08 <DIR> ..
0 File(s) 0 bytes
2 Dir(s) 518,734,532,608 bytes free
8. ! — 执行系统命令¶
在 Notebook 中运行 shell 命令。
（其实!不是 Magic，但也是IPython的机制，和magic一样用，就放在这里了）
In [1]:
!pip list
Package Version --------------------------------- -------------------- accelerate 1.13.0 aiobotocore 2.25.0 aiodns 3.5.0 aiofiles 24.1.0 aiohappyeyeballs 2.6.1 aiohttp 3.13.2 aioitertools 0.12.0 aiosignal 1.4.0 alabaster 0.7.16 altair 5.5.0 anaconda-anon-usage 0.7.1 anaconda-auth 0.8.6 anaconda-catalogs 0.2.0 anaconda-cli-base 0.6.0 anaconda-client 1.13.0 anaconda-navigator 2.6.6 anaconda-project 0.11.1 annotated-doc 0.0.4 annotated-types 0.6.0 anyio 4.10.0 appdirs 1.4.4 archspec 0.2.5 argon2-cffi 21.3.0 argon2-cffi-bindings 25.1.0 arrow 1.4.0 astroid 3.3.11 astropy 7.1.1 astropy-iers-data 0.2025.11.10.0.38.31 asttokens 3.0.0 async-lru 2.0.5 asyncssh 2.17.0 atomicwrites 1.4.0 attrs 25.4.0 audioop-lts 0.2.2 Automat 24.8.1 autopep8 2.0.4 babel 2.16.0 bcrypt 5.0.0 beautifulsoup4 4.13.5 binaryornot 0.4.4 biopython 1.86 black 25.9.0 bleach 6.2.0 blinker 1.9.0 bokeh 3.8.0 boltons 25.0.0 botocore 1.40.46 Bottleneck 1.4.2 brotli 1.2.0 brotlicffi 1.1.0.0 cachetools 5.5.1 certifi 2025.10.5 cffi 2.0.0 chardet 5.2.0 charset-normalizer 3.4.4 click 8.1.8 cloudpickle 3.1.1 colorama 0.4.6 colorcet 3.1.0 colored 2.3.2 comm 0.2.1 conda 25.9.1 conda-anaconda-telemetry 0.3.0 conda-anaconda-tos 0.2.2 conda-build 25.9.0 conda-content-trust 0.2.0 conda_index 0.7.0 conda-libmamba-solver 25.4.0 conda-pack 0.7.1 conda-package-handling 2.4.0 conda_package_streaming 0.11.0 conda-repo-cli 1.0.173 conda-token 0.6.0 constantly 23.10.4 contourpy 1.3.1 cookiecutter 2.6.0 cryptography 46.0.3 cssselect 1.2.0 cycler 0.11.0 dask 2025.10.0 datashader 0.18.2 debugpy 1.8.16 decorator 5.2.1 defusedxml 0.7.1 diff-match-patch 20200713 diffusers 0.38.0.dev0 dill 0.4.0 distributed 2025.10.0 distro 1.9.0 docstring-to-markdown 0.17 docutils 0.21.2 et_xmlfile 2.0.0 evalidate 2.0.3 executing 2.2.1 fastapi 0.135.1 fastjsonschema 2.20.0 ffmpy 1.0.0 filelock 3.20.0 flake8 7.1.1 Flask 3.1.2 fonttools 4.60.1 fqdn 1.5.1 frozendict 2.4.6 frozenlist 1.8.0 fsspec 2025.7.0 gitdb 4.0.12 GitPython 3.1.45 gmpy2 2.2.1 gradio 6.8.0 gradio_client 2.2.0 greenlet 3.2.4 groovy 0.1.2 h11 0.16.0 h5py 3.14.0 HeapDict 1.0.1 hf-xet 1.3.2 holoviews 1.21.0 httpcore 1.0.9 httpx 0.28.1 huggingface_hub 1.5.0 hvplot 0.12.1 hyperlink 21.0.0 idna 3.11 ImageIO 2.37.2 imagesize 1.4.1 imbalanced-learn 0.14.0 importlib_metadata 8.5.0 incremental 24.7.2 inflection 0.5.1 iniconfig 2.1.0 intake 2.0.8 intervaltree 3.1.0 ipykernel 6.31.0 ipython 8.30.0 ipython-genutils 0.2.0 ipywidgets 8.1.7 isoduration 20.11.0 isort 6.1.0 itemadapter 0.12.1 itemloaders 1.3.2 itsdangerous 2.2.0 jaraco.classes 3.4.0 jaraco.context 0.0.0 jaraco.functools 4.1.0 jedi 0.19.2 jellyfish 1.1.3 Jinja2 3.1.6 jiter 0.14.0 jmespath 1.0.1 joblib 1.5.2 json5 0.9.25 jsonpatch 1.33 jsonpointer 3.0.0 jsonschema 4.25.0 jsonschema-specifications 2025.9.1 jupyter 1.1.1 jupyter_client 8.6.3 jupyter-console 6.6.3 jupyter_contrib_core 0.4.2 jupyter_core 5.8.1 jupyter-events 0.12.0 jupyter-highlight-selected-word 0.2.0 jupyter-lsp 2.2.5 jupyter_server 2.16.0 jupyter_server_terminals 0.5.3 jupyterlab 4.3.4 jupyterlab_pygments 0.3.0 jupyterlab_server 2.28.0 jupyterlab_widgets 3.0.15 keyring 25.6.0 kiwisolver 1.4.8 lark 1.3.1 lazy_loader 0.4 lckr_jupyterlab_variableinspector 3.2.4 Levenshtein 0.27.3 libarchive-c 5.1 libmambapy 2.3.2 lief 0.16.4 linkify-it-py 2.0.3 llvmlite 0.45.1 lmdb 1.6.2 locket 1.0.0 lxml 5.3.0 lz4 4.4.5 Markdown 3.8 markdown-it-py 2.2.0 MarkupSafe 3.0.2 matlabengine 26.1 matplotlib 3.10.6 matplotlib-inline 0.2.1 mccabe 0.7.0 mdit-py-plugins 0.5.0 mdurl 0.1.2 menuinst 2.4.1 metakernel 1.0.0 mistune 3.1.2 mkl_fft 2.1.1 mkl_random 1.3.0 mkl-service 2.5.2 more-itertools 10.8.0 mpi4py 4.0.3 mpmath 1.3.0 msgpack 1.1.1 multidict 6.7.0 multipledispatch 1.0.0 mypy 1.17.1 mypy_extensions 1.0.0 narwhals 2.7.0 navigator-updater 0.5.1 nbclient 0.10.2 nbconvert 7.16.6 nbformat 5.10.4 nest_asyncio 1.6.0 networkx 3.5 nltk 3.9.2 notebook 7.3.2 notebook_shim 0.2.4 numba 0.62.1 numexpr 2.14.1 numpy 2.3.4 numpydoc 1.9.0 openai 2.32.0 openpyxl 3.1.5 orjson 3.11.7 overrides 7.7.0 packaging 25.0 pandas 2.3.3 pandocfilters 1.5.1 panel 1.8.3 param 2.2.1 parsel 1.10.0 parso 0.8.5 partd 1.4.2 pathspec 0.12.1 patsy 1.0.1 pexpect 4.9.0 pickleshare 0.7.5 pillow 12.0.0 pip 25.1 pkce 1.0.3 pkginfo 1.12.0 platformdirs 4.5.0 plotly 6.3.0 pluggy 1.5.0 ply 3.11 portalocker 3.2.0 prometheus_client 0.21.1 prompt_toolkit 3.0.52 propcache 0.3.1 Protego 0.4.0 protobuf 5.29.3 psutil 7.0.0 ptyprocess 0.7.0 pure_eval 0.2.3 py-cpuinfo 9.0.0 pyarrow 21.0.0 pyasn1 0.6.1 pyasn1_modules 0.4.2 pycares 4.10.0 pycodestyle 2.12.1 pycosat 0.6.6 pycparser 2.23 pyct 0.6.0 pycurl 7.45.7 pydantic 2.12.3 pydantic_core 2.41.4 pydantic-settings 2.10.1 PyDispatcher 2.0.7 pydocstyle 6.3.0 pydub 0.25.1 pyerfa 2.0.1.5 pyflakes 3.2.0 PyGithub 2.8.1 Pygments 2.19.2 PyJWT 2.10.1 pylint 3.3.8 pylint-venv 3.0.3 pyls-spyder 0.4.0 PyNaCl 1.6.0 pyodbc 5.3.0 pyOpenSSL 25.3.0 pyparsing 3.2.0 PyQt5 5.15.10 PyQt5_sip 12.13.0 PyQtWebEngine 5.15.6 PySocks 1.7.1 pytest 8.4.2 python-dateutil 2.9.0.post0 python-dotenv 1.1.0 python-json-logger 3.2.1 python-Levenshtein 0.27.3 python-lsp-black 2.0.0 python-lsp-jsonrpc 1.1.2 python-lsp-server 1.12.2 python-multipart 0.0.22 python-slugify 8.0.4 pytokens 0.2.0 pytoolconfig 1.2.6 pytz 2025.2 pyuca 1.2 pyviz_comms 3.0.6 PyWavelets 1.9.0 pywin32 311 pywin32-ctypes 0.2.2 pywinpty 2.0.15 PyYAML 6.0.2 pyzmq 27.1.0 QDarkStyle 3.2.3 qstylizer 0.2.2 QtAwesome 1.4.0 qtconsole 5.6.1 QtPy 2.4.3 quast 5.2.0 queuelib 1.8.0 RapidFuzz 3.14.3 readchar 4.2.1 referencing 0.37.0 regex 2026.4.4 requests 2.32.5 requests-file 2.1.0 requests-toolbelt 1.0.0 rfc3339_validator 0.1.4 rfc3986_validator 0.1.1 rfc3987-syntax 1.1.0 rich 14.2.0 roman-numerals-py 3.1.0 rope 1.14.0 rpds-py 0.28.0 rpy2 3.6.7 rpy2-rinterface 3.6.6 rpy2-robjects 3.6.5 rtree 1.4.1 ruamel.yaml 0.18.16 ruamel.yaml.clib 0.2.14 ruamel_yaml_conda 0.17.21 s3fs 2025.7.0 safehttpx 0.1.7 safetensors 0.8.0rc0 scikit-image 0.25.2 scikit-learn 1.7.2 scipy 1.16.3 Scrapy 2.13.3 seaborn 0.13.2 semantic-version 2.10.0 semver 3.0.4 Send2Trash 1.8.2 service-identity 24.2.0 setuptools 72.1.0 shellingham 1.5.4 simplejson 3.20.2 sip 6.7.12 six 1.17.0 smmap 4.0.0 sniffio 1.3.0 snowballstemmer 3.0.1 sortedcontainers 2.4.0 soupsieve 2.5 Sphinx 8.2.3 sphinxcontrib-applehelp 2.0.0 sphinxcontrib-devhelp 2.0.0 sphinxcontrib-htmlhelp 2.1.0 sphinxcontrib-jsmath 1.0.1 sphinxcontrib-qthelp 2.0.0 sphinxcontrib-serializinghtml 2.0.0 spyder 6.0.7 spyder-kernels 3.0.5 SQLAlchemy 2.0.43 stack_data 0.6.3 starlette 0.52.1 statsmodels 0.14.5 streamlit 1.51.0 superqt 0.7.6 sympy 1.14.0 tables 3.10.2 tabulate 0.9.0 tblib 3.1.0 tenacity 9.1.2 terminado 0.18.1 text-unidecode 1.3 textdistance 4.6.3 threadpoolctl 3.5.0 three-merge 0.1.1 tifffile 2025.10.4 tinycss2 1.4.0 tldextract 5.1.2 tokenizers 0.22.2 toml 0.10.2 tomli 2.2.1 tomlkit 0.13.3 toolz 1.0.0 torch 2.11.0 torchvision 0.24.1+cu130 tornado 6.5.1 tqdm 4.67.1 traitlets 5.14.3 transformers 5.6.0 truststore 0.10.1 Twisted 25.5.0 twisted-iocpsupport 1.0.2 typer 0.17.4 typing_extensions 4.15.0 typing-inspection 0.4.2 tzdata 2025.2 tzlocal 5.3.1 uc-micro-py 1.0.3 ujson 5.10.0 uri-template 1.3.0 urllib3 2.5.0 uvicorn 0.41.0 w3lib 2.1.2 watchdog 6.0.0 wcwidth 0.2.13 webcolors 25.10.0 webencodings 0.5.1 websocket-client 1.8.0 Werkzeug 3.1.3 whatthepatch 1.0.7 wheel 0.45.1 widgetsnbextension 4.0.14 win_inet_pton 1.1.0 winloop 0.3.1 wrapt 1.17.0 xarray 2025.10.1 xformers 0.0.35 xlwings 0.33.15 xyzservices 2025.4.0 yapf 0.43.0 yarl 1.22.0 zict 3.0.0 zipp 3.21.0 zope.interface 8.0.1 zstandard 0.23.0
9. %%writefile — 将 cell 内容写入文件¶
In [14]:
%%writefile hello.py
print("Hello, file!")
Writing hello.py
10. %run — 运行 Python 脚本¶
In [15]:
%run hello.py
Hello, file!
11. %%cmd — 在 cell 中书写并运行 cmd 脚本¶
怎么？我用Windows作为我的主要编程环境不行吗？需要用到Linux系统的场合我都是靠WSL解决的（在Linux中这个命令是%%bash，我用Windows所以是这个）
In [18]:
%%cmd
echo Hello from Windows CMD
dir
Microsoft Windows [Version 10.0.26200.8246]
(c) Microsoft Corporation. All rights reserved.
C:\Users\Admin\TechBlog\data>echo Hello from Windows CMD
Hello from Windows CMD
C:\Users\Admin\TechBlog\data>dir
Volume in drive C has no label.
Volume Serial Number is 12B8-C7B5
Directory of C:\Users\Admin\TechBlog\data
27/04/2026 17:21 <DIR> .
27/04/2026 17:25 <DIR> ..
27/04/2026 17:21 <DIR> .ipynb_checkpoints
27/04/2026 17:16 23 hello.py
1 File(s) 23 bytes
3 Dir(s) 518,740,402,176 bytes free
C:\Users\Admin\TechBlog\data>
12. %matplotlib inline — 在 Notebook 内显示图像¶
这个是Python kernel 专用的，R kernel之类的没法用。（不过一般情况下，除了我这个用jupyter lab写博客的，也没什么人会用R kernel的notebook了吧）
In [19]:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# 图像大小
width, height = 800, 600
# 生成复平面网格
x = np.linspace(-2.0, 1.0, width)
y = np.linspace(-1.2, 1.2, height)
X, Y = np.meshgrid(x, y)
C = X + 1j * Y
# 初始化
Z = np.zeros_like(C)
iterations = np.zeros(C.shape, dtype=int)
max_iter = 100
# 迭代计算 Mandelbrot 集合
for i in range(max_iter):
mask = np.abs(Z) <= 2
Z[mask] = Z[mask] * Z[mask] + C[mask]
iterations[mask] = i
# 绘图
plt.figure(figsize=(10, 7))
plt.imshow(iterations, cmap="magma", extent=[-2, 1, -1.2, 1.2])
plt.colorbar(label="Iterations")
plt.title("Mandelbrot Fractal (Matplotlib)")
plt.xlabel("Re")
plt.ylabel("Im")
plt.show()
📊 Magic 常用指令功能汇总表¶
（执行系统命令的指令也算进来了，反正都一样用，都一样都一样）
| 指令 | 类型 | 功能 |
|---|---|---|
%time |
行魔法 | 测量单行代码执行时间 |
%%time |
单元魔法 | 测量整个 cell 执行时间 |
%timeit |
行魔法 | 多次运行取平均时间 |
%%timeit |
单元魔法 | 多次运行整个 cell |
%pwd |
行魔法 | 显示当前工作目录 |
%ls |
行魔法 | 列出目录内容 |
%cd |
行魔法 | 切换目录 |
!command |
Shell | 执行系统命令 |
%run |
行魔法 | 运行 Python 脚本 |
%%bash |
单元魔法 | 在 cell 中运行 bash |
%matplotlib inline |
行魔法 | Notebook 内显示图像 |
%%writefile |
单元魔法 | 将 cell 内容写入文件 |
要是不嫌麻烦，用下面这个指令可以查看所有magic指令
In [13]:
%lsmagic
Out[13]:
Available line magics: %alias %alias_magic %autoawait %autocall %automagic %autosave %bookmark %cd %clear %cls %code_wrap %colors %conda %config %connect_info %copy %ddir %debug %dhist %dirs %doctest_mode %echo %ed %edit %env %gui %hist %history %killbgscripts %ldir %less %load %load_ext %loadpy %logoff %logon %logstart %logstate %logstop %ls %lsmagic %macro %magic %mamba %matplotlib %micromamba %mkdir %more %notebook %page %pastebin %pdb %pdef %pdoc %pfile %pinfo %pinfo2 %pip %popd %pprint %precision %prun %psearch %psource %pushd %pwd %pycat %pylab %qtconsole %quickref %recall %rehashx %reload_ext %ren %rep %rerun %reset %reset_selective %rmdir %run %save %sc %set_env %store %sx %system %tb %time %timeit %unalias %unload_ext %uv %who %who_ls %whos %xdel %xmode Available cell magics: %%! %%HTML %%SVG %%bash %%capture %%cmd %%code_wrap %%debug %%file %%html %%javascript %%js %%latex %%markdown %%perl %%prun %%pypy %%python %%python2 %%python3 %%ruby %%script %%sh %%svg %%sx %%system %%time %%timeit %%writefile Automagic is ON, % prefix IS NOT needed for line magics.