例如,一个名为“Table of Contents”的扩展为你的notebook生成一个目录,使大型notebook更易于可视化和导航 另一个称为 Variable Inspector 的工具将向你显示notebook中每个变量的值、类型、大小和形状,以便快速参考和调试 另一个名为 ExecuteTime 的方法可以让你知道每个单元格运行的时间和持续时间—如果试图加快代码...
Default: True --NotebookApp.token=<Unicode> Token used for authenticating first-time connections to the server. The token can be read from the file referenced by JUPYTER_TOKEN_FILE or set directly with the JUPYTER_TOKEN environment variable. When no password is enabled, the default is to gene...
同样在Nbextention选项卡中勾选Autopep8,在工具栏中会多一个“锤子”一样的按钮,可以帮助我们排版代码,使其符合pep8标准。 (3)Variable inspector 该插件可以帮助我们查看当前notebook中所有的变量的名称,类型,大小和值。省去了df.shape,type()等语句的执行,也代替了前文提到的魔法函数“%whos”的执行,读者可以...
copy In[62]:data= 'this is the stringIwant to pass to different notebook'%storedatadeldata#Thishas deleted the variable copy Stored'data' (str) 现在,在一个新的notebook文档里…… copy In[1]: %store -rdataprint(data) copy thisisthestringI wanttopasstodifferent notebook 10、Jupyter Magic...
Variable Type Data/Info---a int 10aaaaa int 10add_sum function <function add_sum at 0x000001957CA21840>func1 function <function func1 at 0x000001957CEEB840>hello function <function hello at 0x000001957CEEB8C8>numpy module <module 'numpy' from 'C:\<...>ges\\numpy\\__init__.py'>...
| Delete self[key]. | | __eq__(self, value, /) | Return self==value. | | __ge__(self, value, /) | Return self>=value. | | __getattribute__(self, name, /) | Return getattr(self, name). | | __getitem__(...) ...
# The line below sets the environment# variable OMP_NUM_THREADS%envOMP_NUM_THREADS=4env: OMP_NUM_THREADS=4 Magic-%run:运行python代码 %run 可以运行.py格式的python代码——这是众所周知的。不那么为人知晓的事实是它也可以运行其它的jupyter notebook文件,这一点很有用。
#NOTE:Need todeletebrowser cache after running jt-r # Ifthisdoesn't work,trystarting anewnotebooksession.jt-r # toggle toolbarONand notebook nameONjt-t grade3-T-N# toggle kernel logo.kernel logo isinsame containerasname # toggledwith-N.That means that making the kernel logo visible is ...
Variable Explorer and Data Viewer Within a Python Notebook, it's possible to view, inspect, sort, and filter the variables within your current Jupyter session. By selecting theVariablesicon in the main toolbar after running code and cells, you'll see a list of the current variables, which ...
(for variable inspection and debugging) x1 = 0 # counter for NameError x2 = 0 # counter for assignment error (used in cells below) mr = 0 # counter for manual relaunch by button ErrorTriggers=[] # container for ErroTriggers print('NameErrors = ', x1) else: x1 = x1 + 1 Error...