Alexandre B A Villares 🐍
@villares@ciberlandia.pt
Cheers, #CreativeCoding friends!
I'm going to try out something, let's see what happens... next Saturday (2025-03-29) and possibly on some other Saturdays after that. I'm going to host an online space where I show something about Creative Coding with #Python and #py5. I'm calling it "Python Creative Coding Free Walking Tour". I'll also do some "py5 Office Hours", Q&A and on-boarding.
It will be free, and I'll accept donations, just like the free walking tour we have showing off nice spots of São Paulo for tourists. I hope it will be even better than that: as I studied architecture I find the tour guide's explanations a bit over the top and sometimes missing the point, but maybe mine will also be an over the top creative coding tour, who knows? you'll have to judge by yourselves.
The first, "walking tour" part will be from 11:00AM BRT (UCT -3) to 12:00 and then, the second, "office hours" part, will be from 12:15 to 13:00, when people will be able to ask me anything about py5 and I'll try to answer to the best of my knowledge, it will also be an opportunity to get help setting up your tools/environment in order to take your first steps drawing with code.
- To get the video-conference link, send me a DM or fill this form: https://form.jotform.com/Alexandre_Villares/python-creative-coding-walking-tour
![Two ways in Python to select 1 of 4 options based on values of 2 bool values
# 1 - nested if-else
if caseless:
if asKeyword:
parse_element_class = CaselessKeyword
else:
parse_element_class = CaselessLiteral
else:
if asKeyword:
parse_element_class = Keyword
else:
parse_element_class = Literal
# 2 - dict with bool tuples
parse_element_class = {
(True, True): CaselessKeyword,
(True, False): CaselessLiteral,
(False, True): Keyword,
(False, False): Literal,
}[(caseless, asKeyword)]](https://cdn.fosstodon.org/media_attachments/files/114/203/000/192/843/180/original/855e5ef5bd5ccb0f.jpg)
![A regular expression for matching chemical symbols:
Ac|Ag|Al|Am|Ar|As|At|Au|Ba|Be|Bh|Bi|Bk|Br|B|Ca|Cd|Ce|Cf|Cl|Cm|Cn|
Co|Cr|Cs|Cu|C|Db|Ds|Dy|Er|Es|Eu|Fe|Fl|Fm|Fr|F|Ga|Gd|Ge|He|Hf|Hg|
Ho|Hs|H|In|Ir|I|Kr|K|La|Li|Lr|Lu|Lv|Mc|Md|Mg|Mn|Mo|Mt|Na|Nb|Nd|Ne
|Nh|Ni|No|Np|N|Og|Os|O|Pa|Pb|Pd|Pm|Po|Pr|Pt|Pu|P|Ra|Rb|Re|Rf|Rg|
Rh|Rn|Ru|Sb|Sc|Se|Sg|Si|Sm|Sn|Sr|S|Ta|Tb|Tc|Te|Th|Ti|Tl|Tm|Ts|U|V|
W|Xe|Yb|Y|Zn|Zr
An optimized regular expression for matching chemical symbols:
A[cglmrstu]|B[aehikr]?|C[adeflmnorsu]?|D[bsy]|E[rsu]|F[elmr]?|G[ade]
|H[efgos]?|I[nr]?|Kr?|L[airuv]|M[cdgnot]|N[abdehiop]?|O[gs]?|P[abdmo
rtu]?|R[abefghnu]|S[bcegimnr]?|T[abcehilms]|U|V|W|Xe|Yb?|Z[nr]](https://cdn.fosstodon.org/media_attachments/files/114/198/875/625/401/287/original/96f306559e141ad9.jpg)
![L = []
for i in range(10):
def f():
return i
L.append(f)
for f in L:
print(f())](https://cdn.masto.host/mastodongamedevplace/media_attachments/files/114/149/041/356/060/898/original/80850ead5fa89555.png)
![❯ python3.11
Python 3.11.9 (v3.11.9:de54cf5be3, Apr 2 2024, 07:12:50) [Clang 13.0.0 (clang-1300.0.29.30)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import cgi
<stdin>:1: DeprecationWarning: 'cgi' is deprecated and slated for removal in Python 3.13
>>> ^D
❯ python3.12
Python 3.12.9 (v3.12.9:fdb81425a9a, Feb 4 2025, 12:21:36) [Clang 13.0.0 (clang-1300.0.29.30)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import cgi
<stdin>:1: DeprecationWarning: 'cgi' is deprecated and slated for removal in Python 3.13
>>>](https://files.mastodon.social/media_attachments/files/114/001/390/573/634/074/original/7743f036956b2bcb.png)
Qiita - 人気の記事
bzw. mir was drunter posten 
da er selbst kein Interesse an Social Media hat.
![Using `for params["page"] in ...` to move through paged results in a search API. Full text at https://gist.github.com/nedbat/d04b7d1bef5fb84542f23126424c814c](https://media.hachyderm.io/media_attachments/files/113/498/200/375/008/299/original/6634d756fcab33bb.png)
![import mastodon
from mastodon import Mastodon
import time
m = Mastodon(access_token=<YOUR TOKEN HERE>, api_base_url=<YOUR INSTANCE HERE>)
follow_notifications = m.notifications(types=['follow'])
for follow in follow_notifications:
print('follow notification: ' + follow['account']['acct'])
print('following back id: ' + str(follow['account']['id']))
try:
m.account_follow(follow['account']['id'])
except:
print("couldn't follow")
print('dismissing notification: ' + str(follow['id']))
try:
m.notifications_dismiss(str(follow['id']))
except:
print("couldn't dismiss")
time.sleep(3)](https://files.techhub.social/media_attachments/files/113/495/620/521/714/732/original/b16cc9cf73004665.png)
prompt from dull:
version in active Python virtual environment:
in visually pleasant yet non-intrusive manner, seeing active branch and status:
![AttributeError: cython_sources
[end of output]](https://social-coop-media.ams3.cdn.digitaloceanspaces.com/media_attachments/files/113/361/791/371/328/256/original/a63d574bc5d7ae42.png){kind=small}
![API Changes
Default resampling filter for I;16* image modes
The default resampling filter for I;16, I;16L, I;16B and I;16N has been changed from Image.NEAREST to Image.BICUBIC, to match the majority of modes.
API Additions
Writing XMP bytes to JPEG and MPO
XMP data can now be saved to JPEG files using an xmp argument:
im.save("out.jpg", xmp=b"test")
The data can also be set through info, for use when saving either JPEG or MPO images:
im.info["xmp"] = b"test"
im.save("out.jpg")
Other Changes
Python 3.13
Pillow 10.4.0 had wheels built against Python 3.13 beta, available as a preview to help others prepare for 3.13, and to ensure Pillow could be used immediately at the release of 3.13.0 final (2024-10-07, PEP 719).
Pillow 11.0.0 now officially supports Python 3.13.
Support has also been added for the experimental free-threaded mode of PEP 703.
Python 3.13 only supports macOS versions 10.13 and later.
C-level Flags
Some compiling flags like WITH_THREADING, WITH_IMAGECHOPS, and other WITH_* were removed. These flags were not available through the build system, but they could be edited in the C source.](https://cdn.fosstodon.org/media_attachments/files/113/312/105/590/942/667/original/84c9990f7d23c99a.png)
New [renfe-cli](
![Screenshot of python script:
import time
a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] # TODO: Add more numbers
b = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] # TODO: Add more numbers
c = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] # TODO: Add more numbers
n = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11] # TODO: Add more numbers
def test_equation(a, b, c, n) -> bool:
print("------------------\n")
print(f"Testing if {a}^{n} + {b}^{n} = {c}^{n}\n")
print("Simplifying equation...\n")
a_n = a**n
b_n = b**n
time.sleep(2) # Allow time for pc to process
print(f"Simplified equation: {a_n} + {b_n} = {c}^{n}\n")
print("Simplifying equation...\n")
c_n = c**n
a_b_n = a_n + b_n
time.sleep(2) # Allow time for pc to process
print(f"Simplified equation: {a_b_n} = {c_n}\n")
print("Checking result...")
result = a_b_n == c_n
time.sleep(2) # Allow time for pc to process
print(f"The equation is {result}")
print("------------------\n")
return result
for a_val in a:
for b_val in b:
for c_val in c:
for n_val in n:
if test_equation(a_val, b_val, c_val, n_val):
print("UH OH theorem disproven\n\n")
break
else:
print("Theorem needs more proving\n\n")](https://tomkahe.com/system/media_attachments/files/113/160/014/365/964/011/original/21af4f4daad56279.png)
![[This and the following images aren't very screen reader friendly with a lot of code in them. I'll describe what's going on in brackets and then put the text below.
In this image: a demonstration of the basic usage of numpydantic, declaring an "array" field on a pydantic model with an NDArray class with a shape and dtype specification. The model can then be used with a number of different array libraries and data formats, including validation.]
Numpydantic allows you to do this:
from pydantic import BaseModel
from numpydantic import NDArray, Shape
class MyModel(BaseModel):
array: NDArray[Shape["3 x, 4 y, * z"], int]
And use it with your favorite array library:
import numpy as np
import dask.array as da
import zarr
# numpy
model = MyModel(array=np.zeros((3, 4, 5), dtype=int))
# dask
model = MyModel(array=da.zeros((3, 4, 5), dtype=int))
# hdf5 datasets
model = MyModel(array=('data.h5', '/nested/dataset'))
# zarr arrays
model = MyModel(array=zarr.zeros((3,4,5), dtype=int))
model = MyModel(array='data.zarr')
model = MyModel(array=('data.zarr', '/nested/dataset'))
# video files
model = MyModel(array="data.mp4")](https://media.neuromatch.social/media_attachments/files/112/499/343/871/274/862/original/7111010d7847d8ef.png)
![[Further demonstration of validation and array expression, where a Union of NDArray specifications can specify a more complex data type - eg. an image that can be any shape in x and y, an RGB image, or a specific resolution of a video, each with independently checked dtypes]
For example, to specify a very special type of image that can either be
a 2D float array where the axes can be any size, or
a 3D uint8 array where the third axis must be size 3
a 1080p video
from typing import Union
from pydantic import BaseModel
import numpy as np
from numpydantic import NDArray, Shape
class Image(BaseModel):
array: Union[
NDArray[Shape["* x, * y"], float],
NDArray[Shape["* x, * y, 3 rgb"], np.uint8],
NDArray[Shape["* t, 1080 y, 1920 x, 3 rgb"], np.uint8]
]
And then use that as a transparent interface to your favorite array library!
Interfaces
Numpy
The Coca-Cola of array libraries
import numpy as np
# works
frame_gray = Image(array=np.ones((1280, 720), dtype=float))
frame_rgb = Image(array=np.ones((1280, 720, 3), dtype=np.uint8))
# fails
wrong_n_dimensions = Image(array=np.ones((1280,), dtype=float))
wrong_shape = Image(array=np.ones((1280,720,10), dtype=np.uint8))
# shapes and types are checked together, so this also fails
wrong_shape_dtype_combo = Image(array=np.ones((1280, 720, 3), dtype=float))](https://media.neuromatch.social/media_attachments/files/112/499/361/475/260/219/original/606340afc7d4bd8c.png)
![[Demonstration of usage outside of pydantic as just a normal python type - you can validate an array against a specification by checking it the array is an instance of the array specification type]
And use the NDArray type annotation like a regular type outside of pydantic – eg. to validate an array anywhere, use isinstance:
array_type = NDArray[Shape["1, 2, 3"], int]
isinstance(np.zeros((1,2,3), dtype=int), array_type)
# True
isinstance(zarr.zeros((1,2,3), dtype=int), array_type)
# True
isinstance(np.zeros((4,5,6), dtype=int), array_type)
# False
isinstance(np.zeros((1,2,3), dtype=float), array_type)
# False](https://media.neuromatch.social/media_attachments/files/112/499/363/179/526/128/original/283484ca6e6f3ba9.png)
![[Demonstration of JSON schema generation using the sort of odd case of an array with a specific dtype but an arbitrary shape. It has to use a recursive JSON schema definition, where the items of a given JSON array can either be the innermost dtype or another instance of that same array. Since JSON Schema doesn't support extended dtypes like 8-bit integers, we encode that information as maximum and minimum constraints on the `integer` class and add it in the schema metadata. Since pydantic renders all recursive schemas like this in the same $defs block, we use a blake2b hash against the dtype specification to keep them deduplicated.]
numpydantic can even handle shapes with unbounded numbers of dimensions by using recursive JSON schema!!!
So the any-shaped array (using nptyping’s ellipsis notation):
class AnyShape(BaseModel):
array: NDArray[Shape["*, ..."], np.uint8]
is rendered to JSON-Schema like this:
{
"$defs": {
"any-shape-array-9b5d89838a990d79": {
"anyOf": [
{
"items": {
"$ref": "#/$defs/any-shape-array-9b5d89838a990d79"
},
"type": "array"
},
{"maximum": 255, "minimum": 0, "type": "integer"}
]
}
},
"properties": {
"array": {
"dtype": "numpy.uint8",
"items": {"$ref": "#/$defs/any-shape-array-9b5d89838a990d79"},
"title": "Array",
"type": "array"
}
},
"required": ["array"],
"title": "AnyShape",
"type": "object"
}](https://media.neuromatch.social/media_attachments/files/112/499/363/584/367/121/original/176de6d43fde919e.png)
Source code 
VA7OMM CN89
Kacey
