159

I have some Python code example I'd like to share that should do something different if executed in the terminal Python / IPython or in the IPython notebook.

How can I check from my Python code if it's running in the IPython notebook?

1
  • 8
    I suggest accepting Gustavo Bezerra's answer. The currently accepted answer doesn't answer the question, and Gustavo's answer is the highest-scored answer that still works in the latest version of Jupyter Notebook. Commented Sep 21, 2019 at 19:37

19 Answers 19

151

The following worked for my needs:

get_ipython().__class__.__name__

It returns 'TerminalInteractiveShell' on a terminal IPython, 'ZMQInteractiveShell' on Jupyter (notebook AND qtconsole) and fails (NameError) on a regular Python interpreter. The function get_ipython() is available on the global namespace by default when IPython is started.

Wrapping it in a simple function:

def is_notebook() -> bool:
    try:
        shell = get_ipython().__class__.__name__
        if shell == 'ZMQInteractiveShell':
            return True   # Jupyter notebook or qtconsole
        elif shell == 'TerminalInteractiveShell':
            return False  # Terminal running IPython
        else:
            return False  # Other type (?)
    except NameError:
        return False      # Probably standard Python interpreter

The above was tested with Python 3.5.2, IPython 5.1.0 and Jupyter 4.2.1 on macOS 10.12 and Ubuntu 14.04.4 LTS

EDIT: This still works fine in 2022 on newer Python/IPython/Jupyter/OS versions

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9 Comments

On jupyter console, unfortunately get_ipython() returns an instance of ZMQInteractiveShell also
If someone is interested in detecting whether the notebook is running on Google Colab you can check this: get_ipython().__class__.__module__ == "google.colab._shell"
This only works for code in the notebook. It doesn't work if the function is in an imported package.
@ChristopherBarber That's not what I see. If I paste this function into a file test.py then run from test import isnotebook; print(isnotebook()) in a Jupyter Notebook, it prints True. (Tested on Notebook server versions 5.2.1 and 6.0.1.)
the code of this answer is automatically generated by Github Copilot when you type the function name def we_are_in_jupyter() :) imgur.com/9mx9COw You've made it to the brain of the AI
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46

You can check whether python is in interactive mode with the following snippet [1]:

def is_interactive():
    import __main__ as main
    return not hasattr(main, '__file__')

I have found this method very useful because I do a lot of prototyping in the notebook. For testing purposes, I use default parameters. Otherwise, I read the parameters from sys.argv.

from sys import argv

if is_interactive():
    params = [<list of default parameters>]
else:
    params = argv[1:]

Following the implementation of autonotebook, you can tell whether you are in a notebook using the following code.

def in_notebook():
    try:
        from IPython import get_ipython
        if 'IPKernelApp' not in get_ipython().config:  # pragma: no cover
            return False
    except ImportError:
        return False
    except AttributeError:
        return False
    return True

8 Comments

python -c "def is_interactive(): > import main as main > return not hasattr(main, 'file') > print is_interactive()" True
is_interactive() does not distinguish between notebook and console.
Another caveat, issuing a %run from ipython is non-interactive. You could argue it should be, but it is still a gotcha.
The second half of this answer is useful, but the first half (about is_interactive) seems to me to be basically irrelevant to the question. It's also of dubious correctness; as @marscher points out, it counts anything run using python -c as being in "interactive" mode even though this isn't true. I don't want to do it myself since it's not my answer, but I think this would be improved by simply deleting the entire first half of the answer.
Note that get_ipython will returns None when run from an ordinary python shell or a running a script, so this code needs to guard against that case.
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40

To check if you're in a notebook, which can be important e.g. when determining what sort of progressbar to use, this worked for me:

def in_ipynb():
    try:
        cfg = get_ipython().config 
        if cfg['IPKernelApp']['parent_appname'] == 'ipython-notebook':
            return True
        else:
            return False
    except NameError:
        return False

5 Comments

In my IPython-Notebook (IPython version 3.1), cfg['IPKernelApp']['parent_appname'] is a IPython.config.loader.LazyConfigValue, which does not compare to True with "iypthon-notebook"
@juanjux get_ipython returns an IPython.kernel.zmq.zmqshell.ZMQInteractiveShell instance in ipynb (Jupyter) and an IPython.terminal.interactiveshell.TerminalInteractiveShell in a terminal REPL, in case you need to differentiate between notebooks and terminal/consoles (which affects plotting).
^ therefore you can replace the inside of the try block with: return str(type(get_ipython())) == "<class 'ipykernel.zmqshell.ZMQInteractiveShell'>"
Like @Dux, this doesn't work for me; it always returns false, even in a Notebook. Suspect that this answer became obsolete with the introduction of some sort of lazy config loading system.
Note also that your config may come back as an empty dict, in which case you would need to add KeyError to the except block. It is probably better however to use code based on Gustavo Bezerra's answer. Even though I get an empty config, I get shell='PyDevTerminalInteractiveShell' when inspecting the class name.
28

Recently I encountered a bug in Jupyter notebook which needs a workaround, and I wanted to do this without loosing functionality in other shells. I realized that keflavich's solution does not work in this case, because get_ipython() is available only directly from the notebook, and not from imported modules. So I found a way to detect from my module whether it is imported and used from a Jupyter notebook or not:

import sys

def in_notebook():
    """
    Returns ``True`` if the module is running in IPython kernel,
    ``False`` if in IPython shell or other Python shell.
    """
    return 'ipykernel' in sys.modules

# later I found out this:

def ipython_info():
    ip = False
    if 'ipykernel' in sys.modules:
        ip = 'notebook'
    elif 'IPython' in sys.modules:
        ip = 'terminal'
    return ip

Comments are appreciated if this is robust enough.

Similar way it is possible to get some info about the client, and IPython version as well:

import sys

if 'ipykernel' in sys.modules:
    ip = sys.modules['ipykernel']
    ip_version = ip.version_info
    ip_client = ip.write_connection_file.__module__.split('.')[0]

# and this might be useful too:

ip_version = IPython.utils.sysinfo.get_sys_info()['ipython_version']

5 Comments

Hm, I am using the Fedora 23 Jupyter, and there 'Ipython' in sys.modules evaluates to False. Perhaps you mean 'IPython' in sys.modules? This is True in my Jupyter environment. The sys.modules dictionary also doesn't include the 'ipykernel' key - when running inside a notebook.
This is the best answer so far, IMO. Short and sweet.
@danielpcox so which of the sub-answers is the best answer?
Some packages incorrectly detect running in Jupyter, and then import ipykernel, which results in this logic returning a false positive (e.g. Weights and Biases package). So it will work most of the time, but not always.
This fails in jupyter console
16

Tested for python 3.7.3

CPython implementations have the name __builtins__ available as part of their globals which btw. can be retrieved by the function globals().
If a script is running in an Ipython environment then __IPYTHON__ should be an attribute of __builtins__.
The code below therefore returns True if run under Ipython or else it gives False

hasattr(__builtins__,'__IPYTHON__')

9 Comments

Nice and simple!
You should probably import builtins though and check hasattr(builtins, "__IPYTHON__"), since __builtins__ is an implementation detail that could change.
Downvoted — this is also true in an IPython session
@jtlz2 You probably missed the quotes around the string.
This is a fine test for running in IPython, but not for running in a notebook. E.g. it returns true in PyCharm Python Console when using IPython.
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4

The question is what do you want execute differently.

We do our best in IPython prevent the kernel from knowing to which kind of frontend is connected, and actually you can even have a kernel connected to many differents frontends at the same time. Even if you can take a peek at the type of stderr/out to know wether you are in a ZMQ kernel or not, it does not guaranties you of what you have on the other side. You could even have no frontends at all.

You should probably write your code in a frontend independent manner, but if you want to display different things, you can use the rich display system (link pinned to version 4.x of IPython) to display different things depending on the frontend, but the frontend will choose, not the library.

12 Comments

I have one example: progress bars. Jupyter notebook terminal emulator does not support extended terminal control characters such as \x1b[A (move up), so it's not possible to print nested bars. No problem with ipywidgets, we can use native Jupyter widgets to display progress bars. But then we have two different means of displaying a progress bar, and an application might want to know what is the display environment in order to adapt and print the compatible bar.
for instance, I want to set IPython config to always run %matplotlib inline when it acts as a notebook, but not in a terminal, since that is not needed.
While this is a perfectly valid opinion, this answer does not address the actual question. No matter how much you would wish it be otherwise there will always be differences in behavior that may matter.
The intention is good, but the practice is different. There are perfectly valid reasons to make code depend on the environment. My application is the startup file startup.ipy. When in the terminal IPython, for convenience I like to have a few packages pre-imported. When in a notebook, that is considered bad style, and not necessary because I can put the imports in the first cell, not having to type them again and again.
This does not answer the question asked. The title is "How can I check if code is executed in the IPython notebook?" Please, either change the correct answer or the title of the question.
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4

All you have to do is to place these two cells at the beginning of your notebook:

Cell 1: (marked as "code"):

is_notebook = True

Cell 2: (marked as "Raw NBConvert"):

is_notebook = False

The first cell will always be executed, but the second cell will only be executed when you export the notebook as a Python script.

Later, you can check:

if is_notebook:
    notebook_code()
else:
    script_code()

Hope this helps.

1 Comment

Hahah i really like this approach. :-) Bravo.
2

The following captures the cases of https://stackoverflow.com/a/50234148/1491619 without needing to parse the output of ps

def pythonshell():
    """Determine python shell

    pythonshell() returns

    'shell' (started python on command line using "python")
    'ipython' (started ipython on command line using "ipython")
    'ipython-notebook' (e.g., running in Spyder or started with "ipython qtconsole")
    'jupyter-notebook' (running in a Jupyter notebook)

    See also https://stackoverflow.com/a/37661854
    """

    import os
    env = os.environ
    shell = 'shell'
    program = os.path.basename(env['_'])

    if 'jupyter-notebook' in program:
        shell = 'jupyter-notebook'
    elif 'JPY_PARENT_PID' in env or 'ipython' in program:
        shell = 'ipython'
        if 'JPY_PARENT_PID' in env:
            shell = 'ipython-notebook'

    return shell

1 Comment

For me, this just shows jupyter whether it is a jupyter console, jupyter qtconsole, or jupyter notebook.
2

I would recommend avoiding to detect specific frontend because there are too many of them. Instead you can just test if you are running from within iPython environment:

def is_running_from_ipython():
    from IPython import get_ipython
    return get_ipython() is not None

Above will return False if you are invoking running_from_ipython from usual python command line. When you invoke it from Jupyter Notebook, JupyterHub, iPython shell, Google Colab etc then it will return True.

5 Comments

Doesn't work for me -- When I try this in Jupyter Notebook on Ubuntu with Python3, get_ipython() returns <ipykernel.zmqshell.ZMQInteractiveShell at 0x7f750ba94320>.
The problem with this approach is that it doesn't solve the OP's question, "How can I check from my Python code if it's running in the IPython notebook?" (emphasis mine). The IPython shell is not a notebook, but when I run it in my Python Console in PyCharm, I get get_ipython() is not None returning True.
hm, how can I detect if I am running on jupyter vs. voila?
@ntg: That's a rather different distinction. If you'd genuinely like to know, consider submitting a new StackOverflow question.
@Cecil: Ahm, makes sense, actually there seems to be stackoverflow.com/questions/64676189/…
2

A very simple and efficient solution is to check if the top of the call stack refers to IPython environment, as follows:

import traceback

def is_in_notebook():
    rstk = traceback.extract_stack(limit=1)[0]
    return rstk[0].startswith("<ipython")

This code works for both Python 2 and 3, on IPython or Jupyter, with no need to check, set or change the environment.

2 Comments

Interesting. Can you give the content of your call stack please ?
Doesn't seem to work on Windows when using Powershell vs Jupyter. Both return false. Please explain how this is supposed to work? Output?
2

As far as I know, Here has 3 kinds of ipython that used ipykernel

  1. ipython qtconsole ("qtipython" for short)
  2. IPython in spyder ("spyder" for short)
  3. IPython in jupyter notebook ("jn" for short)

use 'spyder' in sys.modules can distinguish spyder

but for qtipython and jn are hard to distinguish because

they have same sys.modules and same IPython config:get_ipython().config

I find a different between qtipython and jn:

first run os.getpid() in IPython shell to get the pid number

then run ps -ef|grep [pid number]

my qtipython pid is 8699

yanglei   8699  8693  4 20:31 ?        00:00:01 /home/yanglei/miniconda2/envs/py3/bin/python -m ipykernel_launcher -f /run/user/1000/jupyter/kernel-8693.json

my jn pid is 8832

yanglei   8832  9788 13 20:32 ?        00:00:01 /home/yanglei/miniconda2/bin/python -m ipykernel_launcher -f /run/user/1000/jupyter/kernel-ccb962ec-3cd3-4008-a4b7-805a79576b1b.json

the different of qtipython and jn is the ipython's json name, jn's json name are longer than qtipython's

so, we can auto-detect all Python Environment using the following code:

import sys,os
def jupyterNotebookOrQtConsole():
    env = 'Unknow'
    cmd = 'ps -ef'
    try:
        with os.popen(cmd) as stream:
            if not py2:
                stream = stream._stream
            s = stream.read()
        pid = os.getpid()
        ls = list(filter(lambda l:'jupyter' in l and str(pid) in l.split(' '), s.split('\n')))
        if len(ls) == 1:
            l = ls[0]
            import re
            pa = re.compile(r'kernel-([-a-z0-9]*)\.json')
            rs = pa.findall(l)
            if len(rs):
                r = rs[0]
                if len(r)<12:
                    env = 'qtipython'
                else :
                    env = 'jn'
        return env
    except:
        return env
    
pyv = sys.version_info.major
py3 = (pyv == 3)
py2 = (pyv == 2)
class pyi():
    '''
    python info
    
    plt : Bool
        mean plt avaliable
    env :
        belong [cmd, cmdipython, qtipython, spyder, jn]
    '''
    pid = os.getpid()
    gui = 'ipykernel' in sys.modules
    cmdipython = 'IPython' in sys.modules and not gui
    ipython = cmdipython or gui
    spyder = 'spyder' in sys.modules
    if gui:
        env = 'spyder' if spyder else jupyterNotebookOrQtConsole()
    else:
        env = 'cmdipython' if ipython else 'cmd'
    
    cmd = not ipython
    qtipython = env == 'qtipython'
    jn = env == 'jn'
    
    plt = gui or 'DISPLAY' in os.environ 

print('Python Envronment is %s'%pyi.env)

The source code is here: Detection Python Environment, Especially distinguish Spyder, Jupyter notebook, Qtconsole.py

1 Comment

Fascinating. The issue here, of course, is the non-portability. You're calling the POSIX-specific ps command. That's bad. Windows isn't POSIX-compatible unless you're running under the Windows Subsystem for Linux (WSL), which means this fails on the world's most popular platform. Woops.
1

I am using Django Shell Plus to launch IPython, and I wanted to make 'running in notebook' available as a Django settings value. get_ipython() is not available when loading settings, so I use this (which is not bulletproof, but good enough for the local development environments it's used in):

import sys

if '--notebook' in sys.argv:
    ENVIRONMENT = "notebook"
else:
    ENVIRONMENT = "dev"

Comments

1

Assuming you have control of the Jupyter Notebook you could:

  1. set an environment value in a cell that uses this as a flag in your code. Place a unique comment in that cell (or all cells you want to exclude)

    # exclude_from_export
    %set_env is_jupyter=1

  2. Export the notebook as a python script to be used in a different context. The export would exclude the commented cell(s) and subsequently the code that sets the environment value. Note: replace your_notebook.ipynb with the name of your actual notebook file.

    jupyter nbconvert --to script --RegexRemovePreprocessor.patterns="['^# exclude_from_export']" your_notebook.ipynb

This will generate a file that will not have the jupyter environment flag set allowing for code that uses it to deterministically execute.

1 Comment

That's a fairly generous assumption you have there.
1

The following would let one know where the python code is being run... be it in Jupyter standalone, Python standalone, Spyder, VSCode or Jupyter notbeook within VSCode.

import os
import IPython as ipy

# add string sources only
sources = str(os.environ.keys()) + \
          ipy.get_ipython().__class__.__name__

# make pattern of unique keys
checks = {'SPYDER': 'Spyder', 'QTIPYTHON': 'qt IPython', 'VSCODE': 
          'VS Code', 'ZMQINTERACTIVEshell': 'Jupyter', }

results = []
msg = []

for k, v in checks.items():
    u = str(k.upper())
    if u in sources.upper():
        results.append(checks[k])

if not results:
    msg.append("Unknown IDE")
else:
    msg.append("Program working ")
    while results:
        msg.append(f"in {results.pop()}")
        if results:
            msg.append(' with')

print(''.join(msg))

Comments

1

This works:

def is_interactive():
    try:
        __IPYTHON__
        return True
    except NameError:
        return False

Comments

0

How about something like this:

import sys

inJupyter = sys.argv[-1].endswith('json')

print(inJupyter);

1 Comment

Yeah, that's demonstrably horrible. The last command-line argument passed to the current Python process is "json" != the current Python process is Jupyter. Those two conditions are only tangentially correlated at best. Good luck resolving false positives with a naively brute-force detection scheme like this.
0

I wanted to use a solution that would work if ipython wasn't installed, and I came up with this 1(?) liner which I found to be pretty useful.
No rescues are required for this approach.

Solution

if locals().get('get_ipython', lambda: None).__class__.__name__ == 'TerminalInteractiveShell':
    print('ipython interactive shell detected!')

Explanation

  • If ipython is installed and loaded, then the function will be in locals().

    locals().get('get_ipython')
    # -> <bound method InteractiveShell.get_ipython of 
    # <IPython.terminal.interactiveshell.TerminalInteractiveShell object at 0x107164a70>>
    
  • We can then call this function get_ipython(), and get the class name of the "interactive shell instance".

    locals().get('get_ipython')()
    # -> <IPython.terminal.interactiveshell.TerminalInteractiveShell at 0x107164a70>
    
  • If get_ipython is not available as a function, then we can return an empty lambda function for the class name comparison

    in ipython session:

    locals().get('get_ipython', lambda: None).__class__.__name__
    # -> 'TerminalInteractiveShell'
    

    not in ipython session:

    ☯ ~ python3 -c "print(locals().get('get_ipython', lambda: None)().__class__.__name__)"
    # -> NoneType
    

Comments

-1

You can try to eval('__IPYTHON__'), borrowed from pydantic:

def in_ipython() -> bool:
    """
    Check whether we're in an ipython environment, including jupyter notebooks.
    """
    try:
        eval('__IPYTHON__')
    except NameError:
        return False
    else:  # pragma: no cover
        return True

1 Comment

This will be true also if you are using the QtConsole
-2

Check the parent process

So far the only solution that worked for me is to check the parent processes using psutil:

import psutil
def runninginJupyterNotebook():
    for i in psutil.Process().parent().cmdline():
        if "jupyter-notebook" in i:
            return True
    else:
        return False

Or you can set a variable in one line:

RUNNING_IN_JUPYTER = any(["jupyter-notebook" in i for i in psutil.Process().parent().cmdline()])

RUNNING_IN_JUPYTER is True if you are running a Jupyter Notebook.

Note that it will be true also if you are running a Colab notebook.

in MacOS

import psutil
def runninginJupyterNotebook():
    for i in psutil.Process().parent().cmdline():
        if "jupyter-notebook" in i:
            return True
    else:
        return False

Or you can set a variable in one line:

RUNNING_IN_JUPYTER = any([i.endswith("bin/jupyter-notebook") for i in psutil.Process().parent().cmdline()])

Comparison to the other solutions:

get_ipython().__class__.__name__

All the solutions using get_ipython() work only if you don't care if it is running on a QtConsole.

Credits: https://stackoverflow.com/a/65498256/2132157

1 Comment

The one-liner: python.exe -c "import psutil as p; T=any([i.endswith('bin/jupyter-notebook') for i in p.Process().parent().cmdline()]);print(T);" works in powershell, but not running the same in Jupyter.

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