Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Copy-edit "interactive figures & async programming" guide. #29650

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Feb 21, 2025
Merged

Copy-edit "interactive figures & async programming" guide. #29650

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 11 additions & 11 deletions galleries/users_explain/figure/interactive_guide.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ Interactive figures and asynchronous programming

Matplotlib supports rich interactive figures by embedding figures into
a GUI window. The basic interactions of panning and zooming in an
Axes to inspect your data is 'baked in' to Matplotlib. This is
Axes to inspect your data is "baked in" to Matplotlib. This is
supported by a full mouse and keyboard event handling system that
you can use to build sophisticated interactive graphs.

Expand Down Expand Up @@ -54,7 +54,7 @@ user hits the 'z' key, please run this other function". This allows
users to write reactive, event-driven, programs without having to
delve into the nitty-gritty [#f3]_ details of I/O. The core event loop
is sometimes referred to as "the main loop" and is typically started,
depending on the library, by methods with names like ``_exec``,
depending on the library, by methods with names like ``exec``,
``run``, or ``start``.


Expand Down Expand Up @@ -83,7 +83,7 @@ for user input and lets us register functions to be run when that
happens. However, if we want to do both we have a problem: the prompt
and the GUI event loop are both infinite loops that each think *they*
are in charge! In order for both the prompt and the GUI windows to be
responsive we need a method to allow the loops to 'timeshare' :
responsive we need a method to allow the loops to "timeshare" :

1. let the GUI main loop block the python process when you want
interactive windows
Expand All @@ -109,7 +109,7 @@ Blocking the prompt


The simplest "integration" is to start the GUI event loop in
'blocking' mode and take over the CLI. While the GUI event loop is
"blocking" mode and take over the CLI. While the GUI event loop is
running you cannot enter new commands into the prompt (your terminal
may echo the characters typed into the terminal, but they will not be
sent to the Python interpreter because it is busy running the GUI
Expand Down Expand Up @@ -147,7 +147,7 @@ While running the GUI event loop in a blocking mode or explicitly
handling UI events is useful, we can do better! We really want to be
able to have a usable prompt **and** interactive figure windows.

We can do this using the 'input hook' feature of the interactive
We can do this using the "input hook" feature of the interactive
prompt. This hook is called by the prompt as it waits for the user
to type (even for a fast typist the prompt is mostly waiting for the
human to think and move their fingers). Although the details vary
Expand Down Expand Up @@ -386,8 +386,8 @@ sure that you are locking in the critical sections.



Eventloop integration mechanism
===============================
Event loop integration mechanism
================================

CPython / readline
------------------
Expand All @@ -404,7 +404,7 @@ run the event loop until a key is pressed on stdin.
Matplotlib does not currently do any management of :c:data:`PyOS_InputHook` due
to the wide range of ways that Matplotlib is used. This management is left to
downstream libraries -- either user code or the shell. Interactive figures,
even with Matplotlib in 'interactive mode', may not work in the vanilla python
even with Matplotlib in "interactive mode", may not work in the vanilla python
repl if an appropriate :c:data:`PyOS_InputHook` is not registered.

Input hooks, and helpers to install them, are usually included with
Expand Down Expand Up @@ -433,9 +433,9 @@ method. The source for the ``prompt_toolkit`` input hooks lives at
then the loop would look something like ::

fds = [...]
while True: # Loop
inp = select(fds).read() # Read
eval(inp) # Evaluate / Print
while True: # Loop
inp = select(fds).read() # Read
eval(inp) # Evaluate / Print

.. [#f2] Or you can `write your own
<https://www.youtube.com/watch?v=ZzfHjytDceU>`__ if you must.
Expand Down
Loading