#ipython — Public Fediverse posts

Every terminal debugger forces a choice: a REPL with full evaluation power but no source context, or an editor with visual breakpoints but a crippled debug console. dap-mux removes the need to choose.

Connect your editor and your REPL to the same debug session. Both are first-class clients. Neither knows the other is there.

Ships with an IPython frontend. Speaks standard DAP — any language, any editor. This is the very first release. There's so much work to do.

github.com/dap-mux/dap-mux
#Python #debugging #Helix #neovim #IPython

Taking a python path on plural sight now, and I find it puzzling that none of these python suggest installing `ipython` ... Why is it so?

#python #ipython #question #fediverse #askfedi #computerscience #datascience #devops #linux

Taking a python path on plural sight now, and I find it puzzling that none of these people suggest installing `ipython` ... Why is it so?

#python #ipython #question #fediverse #askfedi #computerscience #datascience #devops #linux

One Open-source Project Daily

Beautiful spinners for terminal, IPython and Jupyter

https://github.com/manrajgrover/halo

#1ospd #opensource #async #halo #ipython #jupyter #ora #python #spinner

One Open-source Project Daily

Beautiful spinners for terminal, IPython and Jupyter

https://github.com/manrajgrover/halo

#1ospd #opensource #async #halo #ipython #jupyter #ora #python #spinner

#sagemath #ipython #kitty #kitten #kissat
Много лет пользуюсь x11-terms/kitty поэтому радуюсь появлению https://github.com/sagemath/sage/issues/42054
(а sci-mathematics/kissat я собираю с --no-kitten)

Did not expect to get a reminder about International Transgender Day of Visibility in #ipython, but glad I did :)

Nice tip from IPython today.

> Tip: Happy International Transgender Day of Visibility! You are valid. You matter. https://en.wikipedia.org/wiki/International_Transgender_Day_of_Visibility

#Python #IPython

Nice tip from IPython today.

> Tip: Happy International Transgender Day of Visibility! You are valid. You matter. https://en.wikipedia.org/wiki/International_Transgender_Day_of_Visibility

#Python #IPython

Windows at work, always a fresh inconvenience:

C:\>python -m pip install ipython
Requirement already satisfied: ipython in c:\users\[...]

C:\>ipython
'ipython' is not recognized [...]

#ipython #windows #python

Windows at work, always a fresh inconvenience:

C:\>python -m pip install ipython
Requirement already satisfied: ipython in c:\users\[...]

C:\>ipython
'ipython' is not recognized [...]

#ipython #windows #python

I'm still learning how to submit a patch or pull request to Guix to propose updated definitions of some packages... but---while I figure things out---here's a general guide on how to get new packages installed by defining package variants and rewriting package inputs. In short, the steps to do so are:

1. Get the sha256sum hash in the nix-base-32 format (either via `guix download` or `guix hash` of a repository)
2. Prepare the package variant Scheme file (see images; e.g. "package-variant.scm")
3. Run `guix build -f ./package-variant.scm` to build the new package in the store
4. (Optional, but recommended) Test that things work by running `git shell -f ./package-variant.scm`
5. Install the package by running `guix package -f ./package-variant.scm`

#guix #python #emacs #JupyterNotebook #ipython #sql #package #variants

I'm still learning how to submit a patch or pull request to Guix to propose updated definitions of some packages... but---while I figure things out---here's a general guide on how to get new packages installed by defining package variants and rewriting package inputs. In short, the steps to do so are:

1. Get the sha256sum hash in the nix-base-32 format (either via `guix download` or `guix hash` of a repository)
2. Prepare the package variant Scheme file (see images; e.g. "package-variant.scm")
3. Run `guix build -f ./package-variant.scm` to build the new package in the store
4. (Optional, but recommended) Test that things work by running `git shell -f ./package-variant.scm`
5. Install the package by running `guix package -f ./package-variant.scm`

#guix #python #emacs #JupyterNotebook #ipython #sql #package #variants

The site has a handful of "synthetic users" that serve to hold items from external sources like #Django debug pages and the #iPython "%pastebin" magic. Their profile pages recently got a little revamp, with a bot icon and more account info.

If you'd like a similar setup for your public dpaste.com integration, drop a line!

* https://dpaste.com/profile/2
* https://dpaste.com/profile/1003

How to best create, maintain and archive custom environments from within Jupyter? .. just updated the documentation for Carto-Lab Docker with examples for Python [1] and R [2].

The tricky part is linking Kernels from custom envs with a Jupyter kernelspec (specifically if the Jupyter server and the Kernel are in two different environments). However, most of this can be stored in Jupyter notebook cells, for reproducibility.

There's also a section on archival of package versions with Conda's `env export` (yml approach) and `conda list --explicit` (full archival).

[1]: https://cartolab.theplink.org/use-cases/#create-your-own-environment-in-a-bind-mount-and-install-the-ipkernel
[2]: https://cartolab.theplink.org/use-cases/#example-create-an-environment-with-a-specific-r-version

#jupyter #R #ipython # #reproducibility #Notebooks #conda

Do you use pg.ConsoleWidget and have some preference for it over #IPython ‘s QtConsole? If so I’d like to hear from you. We’re considering deprecating ConsoleWidget and directing users to use the Jupyter/IPython QtConsole instead.

That's a nice little surprise!
Happy #TransDayOfVisibility to you too #IPython! :heart_trans:

Apparently ipython has a special tip if launched today!

#Python #IPython

Jeden błąd w #PyPy naprawiony, i #IPython w #Gentoo jest na #PyPy 3.11.

Jeden błąd w bibliotece standardowej #Pythona naprawiony, #Django w Gentoo jest na PyPy 3.11.

Powiedziałbym, że całkiem udany dzień.

https://github.com/pypy/pypy/pull/5239
https://github.com/python/cpython/pull/130962

#Python

One #PyPy bug fixed, and #Gentoo gets #IPython on #PyPy 3.11.

One #Python stdlib bug fixed, and Gentoo gets #Django on PyPy 3.11.

I dare say that's a pretty good day.

https://github.com/pypy/pypy/pull/5239
https://github.com/python/cpython/pull/130962

One #PyPy bug fixed, and #Gentoo gets #IPython on #PyPy 3.11.

One #Python stdlib bug fixed, and Gentoo gets #Django on PyPy 3.11.

I dare say that's a pretty good day.

https://github.com/pypy/pypy/pull/5239
https://github.com/python/cpython/pull/130962

Some fun numbers: out of 823 packages featuring #PyPy 3.x support in #Gentoo, 712 have already been ported to PyPy 3.11. There are a few significant blockers left (notably #IPython, with hanging IPyParallel), and a fair number of packages that simply don't have tests (so I haven't looked at them yet).

Interesting enough, the most common test failures seen while porting to PyPy 3.11 are:

• flaky tests (i.e. just need to rerun, especially without parallelization of testing 70 packages simultaneously)
• existing, irrelevant test regressions (i.e. confirmed by testing with CPython 3.11)
• existing test problems with PyPy3.10 (i.e. need to copy deselects)
• some minor differences, such as slightly different exception messages

Serious issues are really rare, and they are often fixed (or worked around by me) promptly. Really great release! Thanks to everyone involved!

Some fun numbers: out of 823 packages featuring #PyPy 3.x support in #Gentoo, 712 have already been ported to PyPy 3.11. There are a few significant blockers left (notably #IPython, with hanging IPyParallel), and a fair number of packages that simply don't have tests (so I haven't looked at them yet).

Interesting enough, the most common test failures seen while porting to PyPy 3.11 are:

• flaky tests (i.e. just need to rerun, especially without parallelization of testing 70 packages simultaneously)
• existing, irrelevant test regressions (i.e. confirmed by testing with CPython 3.11)
• existing test problems with PyPy3.10 (i.e. need to copy deselects)
• some minor differences, such as slightly different exception messages

Serious issues are really rare, and they are often fixed (or worked around by me) promptly. Really great release! Thanks to everyone involved!

It's been a while without news, but #IPython 9.0 beta 1 is out. "biggest" features are complete rewrite of the theme engine which now supports arbitrary colors, and unicode (I'd love new themes please !) also optional LLM integrations. PLease help me write the changelog as well : https://ipython.readthedocs.io/en/latest/whatsnew/version9.html

It's been a while without news, but #IPython 9.0 beta 1 is out. "biggest" features are complete rewrite of the theme engine which now supports arbitrary colors, and unicode (I'd love new themes please !) also optional LLM integrations. PLease help me write the changelog as well : https://ipython.readthedocs.io/en/latest/whatsnew/version9.html

I have no idea what magic makes this possible, but I love it: https://github.com/evcxr/evcxr/blob/main/evcxr_jupyter/README.md #Evcxr, a #Rust #Jupyter kernel.

I've been planning to actually sit down and start learning the language finally but have been putting it off.

But... a Rust REPL in Jupyter? Yes, Finally. #IPython/Jupyter have become my natural habitat over the past decade. This will make playing around with and learning to think in Rust *much* easier.

My svg-turtle library now has #IPython support, so you can include #Python #TurtleGraphics in your #Jupyter notebooks.
https://donkirkby.github.io/svg-turtle/

@data @datadon

#DataViz on two requirements:
* zooming, panning and rescaling
* shareable dashboards

"Plotly vs. Bokeh: Interactive Python Visualisation Pros and Cons", by Dr Paul Iacomi: https://pauliacomi.com/2020/06/07/plotly-v-bokeh.html

#dataDev #retrieval #dataMining #plotly #Dash #Bokeh #python #dataInteraction #data #dataDon #widgets #ipython #jupyter #dashboards #businessIntelligence

@data @datadon

#DataViz on two requirements:
* zooming, panning and rescaling
* shareable dashboards

"Plotly vs. Bokeh: Interactive Python Visualisation Pros and Cons", by Dr Paul Iacomi: https://pauliacomi.com/2020/06/07/plotly-v-bokeh.html

#dataDev #retrieval #dataMining #plotly #Dash #Bokeh #python #dataInteraction #data #dataDon #widgets #ipython #jupyter #dashboards #businessIntelligence

Wow! New #Python discovery, I knew you could invoke a python or #ipython shell inside a script to examine variables and such, but I somehow always thought it was impossible to actually change them. Turns out there is no such protection in place, you can jump into an ipython shell in a running program with lots of threads doing stuff and manually actually... do stuff. Added a shell drop command to debug - now it's the most powerful UI element and my whole namespace is just.. there.

#Jupyter #Python folks:

Anyone else find that you just do *everything* in Jupyter and #ipython?

Every time I boot up my computer, I start a #jupyterlab server running and launch a browser to connect to it. That browser window will then run in full-screen on it's own desktop for days, weeks, possibly months to come, various notebook tabs being opened and closed and a scratch notebook always open for just doing "stuff" on my computer (whatever I wanna use my computer for at the moment).

A guide on integrating #emacs + #python + #hatch using [mostly] builtin tooling and project local .dir-locals.el variables.

Specifically, this setup uses #Eglot + #pyright for live syntax checking, #pytest for code running, #MyPy for type-checking, and #IPython as the shell

Feedback would be welcome -- trying to get it robust + idiomatic.

https://jtmoulia.srht.site/guides/emacs-python-hatch/

Great, #IPython finally fixed #PyTest 8 compatibility.

Oh, wait… they've just fixed one trivial issue and declared it fixed, without actually testing at all or looking at the bugs already reported. Quality work!

https://github.com/ipython/ipython/commit/cdacafdccaf1f562e59b21b3c9f2c1a28eba54da

#Gentoo #Python

Recently I've added a cheap hack to the standard #Gentoo invocation for #PyTest to throw errors if unhandled async functions are detected. The goal was to increase our chances of finding packages with missing dependency on dev-python/pytest-asyncio (or another equivalent plugin), or packages disabling plugin autoloading and failing to load such a plugin.

Today, I've gotten a first bug report, regarding dev-python/ipython. I've grepped the sources and confirmed that the package depends on PyTest-AsyncIO, except that it pins to < 0.22. Well, we don't have one that old but let's hope it works anyway. So I've tried adding the dep, `-p asyncio`… and PyTest still apparently couldn't find the plugin. I've scratched my head and tried `PYTEST_PLUGINS` instead — still the same result. What the…?

So I've checked the git repository out, tried with older PyTest-AsyncIO, and indeed the tests worked. Tried with the newest, 0.23.6, and the same issue occurred. I've checked the git history and discovered that the version pin was added because of a buggy 0.22.0 release. However, the issue has been fixed since, the release was yanked and my problem was nothing like that.

So I've investigated more. For some reason, #IPython test suite does not mark tests with `pytest.mark.asyncio` marker directly. Instead, it globally iterates over all test functions, and implicitly adds the marker to all coroutines. This used to work with older versions, but does not work anymore — the test is correctly marked, but for some reason it stops being recognized as a coroutine. So I've made a minimal reproducer and filed a bug.

The key point here is: the (potential) bug went unnoticed for a while now, because of the premature, then obsolete pin in IPython.

https://gitweb.gentoo.org/repo/gentoo.git/commit/eclass/python-utils-r1.eclass?id=1f35acddca01e91d4477f3d0340c47329517f474
https://bugs.gentoo.org/928411
https://github.com/ipython/ipython/commit/e27ee203ad54df0431d817abad09ec1caafde4d6
https://github.com/pytest-dev/pytest-asyncio/issues/810

#Python

#IPython 8.23 includes improved autocomplete (when jedi is turned off) now being able to suggest completions based on advanced Python return type annotations (like `Literal`, `Protocol`, `Union`, etc). https://github.com/ipython/ipython/pull/14357

https://chaos.social/@Mbussonn/112190472273181185

New #IPython release 8.23, see what's new there. https://ipython.readthedocs.io/en/8.23.0/whatsnew/version8.html Usually on Fridays, but for one on Sunday. So dedicated to out :trans_flag: friends. #TransDayOfVisiblity ❤️

You can use a question mark in any #iPython derivative, such as #Jupyter.

Using #IPython #Jupyter Magic Commands to Improve the #JupyterNotebook Experience

The article we’ll show how your team can turn any utility function(s) into reusable IPython Jupyter magics.

By Stefan Krawczyk | Feb, 2024 | Towards Data Science https://towardsdatascience.com/using-ipython-jupyter-magic-commands-to-improve-the-notebook-experience-f2c870cab356

#Programming