[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
       - id: trailing-whitespace
 
   - repo: https://github.com/rbubley/mirrors-prettier
-    rev: 787fb9f542b140ba0b2aced38e6a3e68021647a3 # frozen: v3.5.3
+    rev: 5ba47274f9b181bce26a5150a725577f3c336011 # frozen: v3.6.2
     hooks:
       - id: prettier
         files: \.(css|md|yml|yaml)
@@ -36,7 +36,7 @@ repos:
       - id: blacken-docs
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: ce40a160603ab0e7d9c627ae33d7ef3906e2d2b2 # frozen: v3.19.1
+    rev: 37bfa06d791fd38fb4e54910b36a2ff57641b074 # frozen: v3.20.0
     hooks:
       - id: pyupgrade
         args: [--py38-plus]

CONTRIBUTING.md

@@ -17,7 +17,6 @@ Scientific Python projects using GitHub pull requests.
 ### Development Workflow
 
 1.  If you are a first-time contributor:
-
     - Go to <https://github.com/scientific-python/scientific-python.org> and click the
       "fork" button to create your own copy of the project.
 
@@ -30,12 +29,10 @@ Scientific Python projects using GitHub pull requests.
           git remote add <your-username> git@github.com:<your-username>/scientific-python.org.git
 
     - Now, you have remote repositories named:
-
       - `origin`, which refers to the `scientific-python/scientific-python.org` repository
       - `<your-username>`, which refers to your personal fork
 
 2.  Develop your contribution:
-
     - Pull the latest changes from origin:
 
           git checkout main
@@ -49,15 +46,13 @@ Scientific Python projects using GitHub pull requests.
     - Commit locally as you progress (`git add` and `git commit`)
 
 3.  Submit your contribution:
-
     - Push your changes back to your fork on GitHub:
 
           git push <your-username> issue-148
 
     - Go to GitHub. The new branch will show up with a green Pull Request (PR) button---click it.
 
 4.  Review process:
-
     - Every PR update triggers a set of
       [continuous integration](https://en.wikipedia.org/wiki/Continuous_integration)
       services that check that the code is up to standards and passes all our tests.

content/code_of_conduct.md

@@ -56,7 +56,6 @@ We strive to:
     we take responsibility for our own speech.
     Be kind to others.Do not insult or put down other participants.
     We will not accept harassment or other exclusionary behaviour, such as:
-
     - Violent threats or language directed against another person.
     - Sexist, racist, or otherwise discriminatory jokes and language.
     - Posting sexually explicit or violent material.

content/summits/developer/2023/general-planning.md

@@ -24,14 +24,11 @@ birds-of-a-feather (BoF)-style talks, followed by more focused discussion.
 2. (10 min) Logistics
 
 3. (30) Meeting Topics
-
    - Jarrod Millman: Goal
-
      - Unique opportunity to work on cross-project concerns
      - We should think big, but focus on achievable short-term goals
 
    - Stéfan van der Walt: Build systems
-
      - Starting to see Meson emerge as an excellent build option for compiled Scientific Python libraries
        - But there's no "standard" configuration/documentation for standard workflows yet; numpy/scipy/scikit-image are all feeling it out
        - Editable installs just arrived, but work slightly differently to what we're used to with pip install -e ..
@@ -43,7 +40,6 @@ birds-of-a-feather (BoF)-style talks, followed by more focused discussion.
      - There is therefore technical, user interface, and documentation work to be done
 
    - Stéfan van der Walt: Sparse work
-
      - In the previous release of SciPy we introduced experimental Sparse Arrays
      - These arrays are limited to 2D, since they are built on top of Sparse Matrices
      - We hope to refactor scipy.sparse:
@@ -52,13 +48,11 @@ birds-of-a-feather (BoF)-style talks, followed by more focused discussion.
        - sparse arrays should closely follows numpy array semantics
 
    - Brigitta Sipőcz: Shared infrastructure for SPECS and beyond
-
      - SPECs: The current SPEC drafts are documents about policies the core libraries opt-in to follow (e.g. producing and using developer versions in testing), however, template implementation / suggested examples are needed to work out.
      - Testing: Libraries facing the same or very similar doctesting and docs building challenges, aggregating the needs and centralizing these efforts
      - Tutorial infrastructure
 
    - Juanita Gomez: Community
-
      - Community management
      - Documentation
 

content/summits/domain-stacks/meeting1.md

@@ -6,7 +6,6 @@ title: "Meeting 1"
 
 - When: September 6th 8am PDT
 - Where:
-
   - https://berkeley.zoom.us/j/93150321184?pwd=aEp4RGFhc1pLQ2l3b1VKNHJRUGpOUT09
   - Passcode: 029244
 
@@ -32,9 +31,7 @@ title: "Meeting 1"
 - (10 min) Stéfan discuss purpose of meeting and goals (10 min)
 
 - Topics
-
   - (20 min) Would something like
-
     - https://deploy-preview-286--scientific-python-org.netlify.app/software/
     - https://hackmd.io/1wioifmCTY2UVmGT-jcZsg
 

content/summits/sparse/meeting1.md

@@ -31,7 +31,6 @@ birds-of-a-feather (BoF)-style talks, followed by more focused discussion.
 1. (5 min) Welcome & Introductions (Jarrod Millman)
 
 2. (20 min) BoF Presentations (4 min each)
-
    - Dan Schult: Proposal for array semantics in `scipy.sparse` [(download)][scipy]
    - Hameer Abbasi: PyData/Sparse -- Future Plans [(download)][pydata-sparse]
    - Jim Kitchen: needs/roles of sparse in GraphBLAS

content/summits/sparse/meeting2.md

@@ -19,13 +19,10 @@ and what work can be accomplished during the [2023 Scientific Python developer s
 1. (5 min) Welcome & Introductions (Jarrod Millman)
 
 2. (50 min) Discussion
-
    - Who will be working on scipy sparse arrays during the summit?
-
      - How much time during the meeting will you be working on sparse?
 
    - What should/can we get done before the summit?
-
      - array creation PR merged ([PR 1](https://github.com/scipy/scipy/pull/16108) or [PR 2](https://github.com/scipy/scipy/pull/16033))?
      - 1d sparse arrays (Stefan); array semantics / indexing