Important

This documentation covers IPython versions 6.0 and higher. Beginning with version 6.0, IPython stopped supporting compatibility with Python versions lower than 3.3 including all versions of Python 2.7.

If you are looking for an IPython version compatible with Python 2.7, please use the IPython 5.x LTS release and refer to its documentation (LTS is the long term support release).

7.x Series

IPython 7.0.0

Released Thursday September 27th, 2018

IPython 7 include major features improvement as you can read in the following changelog. This is also the second major version of IPython to support only Python 3 – starting at Python 3.4. Python 2 is still community supported on the bugfix only 5.x branch, but we remind you that Python 2 “end of life” is on Jan 1st 2020.

We were able to backport bug fixes to the 5.x branch thanks to our backport bot which backported more than 70 Pull-Requests, but there are still many PRs that required manually work, and this is an area of the project were you can easily contribute by looking for PRs still needed backport

IPython 6.x branch will likely not see any further release unless critical bugs are found.

Make sure you have pip > 9.0 before upgrading. You should be able to update by simply running

pip install ipython --upgrade

Or if you have conda installed:

conda install ipython

Prompt Toolkit 2.0

IPython 7.0+ now uses prompt_toolkit 2.0, if you still need to use earlier prompt_toolkit version you may need to pin IPython to <7.0.

Autowait: Asynchronous REPL

Staring with IPython 7.0 and on Python 3.6+, IPython can automatically await code at top level, you should not need to access an event loop or runner yourself. To know more read the Asynchronous in REPL: Autoawait section of our docs, see PR #11265 or try the following code:

Python 3.6.0
Type 'copyright', 'credits' or 'license' for more information
IPython 7.0.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import aiohttp
   ...: result = aiohttp.get('https://api.github.com')

In [2]: response = await result
<pause for a few 100s ms>

In [3]: await response.json()
Out[3]:
{'authorizations_url': 'https://api.github.com/authorizations',
 'code_search_url': 'https://api.github.com/search/code?q={query}{&page,per_page,sort,order}',
...
}

Note

Async integration is experimental code, behavior may change or be removed between Python and IPython versions without warnings.

Integration is by default with asyncio, but other libraries can be configured, like curio or trio, to improve concurrency in the REPL:

In [1]: %autoawait trio

In [2]: import trio

In [3]: async def child(i):
   ...:     print("   child %s goes to sleep"%i)
   ...:     await trio.sleep(2)
   ...:     print("   child %s wakes up"%i)

In [4]: print('parent start')
   ...: async with trio.open_nursery() as n:
   ...:     for i in range(3):
   ...:         n.spawn(child, i)
   ...: print('parent end')
parent start
   child 2 goes to sleep
   child 0 goes to sleep
   child 1 goes to sleep
   <about 2 seconds pause>
   child 2 wakes up
   child 1 wakes up
   child 0 wakes up
parent end

See Asynchronous in REPL: Autoawait for more information.

Asynchronous code in a Notebook interface or any other frontend using the Jupyter Protocol will need further updates of the IPykernel package.

Non-Asynchronous code

As the internal API of IPython are now asynchronous, IPython need to run under an even loop. In order to allow many workflow, (like using the %run magic, or copy_pasting code that explicitly starts/stop event loop), when top-level code is detected as not being asynchronous, IPython code is advanced via a pseudo-synchronous runner, and will not may not advance pending tasks.

Change to Nested Embed

The introduction of the ability to run async code had some effect on the IPython.embed() API. By default embed will not allow you to run asynchronous code unless a event loop is specified.

Effects on Magics

Some magics will not work with Async, and will need updates. Contribution welcome.

Expected Future changes

We expect more internal but public IPython function to become async, and will likely end up having a persisting event loop while IPython is running.

Thanks

This took more than a year in the making, and the code was rebased a number of time leading to commit authorship that may have been lost in the final Pull-Request. Huge thanks to many people for contribution, discussion, code, documentation, use-case: dalejung, danielballan, ellisonbg, fperez, gnestor, minrk, njsmith, pganssle, tacaswell, takluyver , vidartf … And many others.

Autoreload Improvement

The magic %autoreload 2 now captures new methods added to classes. Earlier, only methods existing as of the initial import were being tracked and updated.

This new feature helps dual environment development - Jupyter+IDE - where the code gradually moves from notebook cells to package files, as it gets structured.

Example: An instance of the class MyClass will be able to access the method cube() after it is uncommented and the file file1.py saved on disk.

..code:

# notebook

from mymodule import MyClass
first = MyClass(5)
# mymodule/file1.py

class MyClass:

    def __init__(self, a=10):
        self.a = a

    def square(self):
        print('compute square')
        return self.a*self.a

    # def cube(self):
    #     print('compute cube')
    #     return self.a*self.a*self.a

Misc

The autoindent feature that was deprecated in 5.x was re-enabled and un-deprecated in PR #11257

Make %run -n -i ... work correctly. Earlier, if %run was passed both arguments, -n would be silently ignored. See PR #10308

The %%script` (as well as %%bash`, %%ruby`… ) cell magics now raise by default if the return code of the given code is non-zero (thus halting execution of further cells in a notebook). The behavior can be disable by passing the --no-raise-error flag.

Deprecations

A couple of unused function and methods have been deprecated and will be removed in future versions:

  • IPython.utils.io.raw_print_err
  • IPython.utils.io.raw_print

Backwards incompatible changes

  • The API for transforming input before it is parsed as Python code has been completely redesigned, and any custom input transformations will need to be rewritten. See Custom input transformation for details of the new API.