Merge pull request #454 from Andrew-S-Rosen/patch-3

JOSS Paper: Reduce line-spacing in code blocks

.github/workflows/testing.yml

@@ -20,7 +20,10 @@ jobs:
           cache: pip
           cache-dependency-path: pyproject.toml
 
-      - uses: pre-commit/[email protected]
+      - name: Run pre-commit
+        run: |
+          pip install pre-commit
+          pre-commit run --all-files --show-diff-on-failure
 
   test:
     services:

.pre-commit-config.yaml

@@ -24,7 +24,7 @@ repos:
     hooks:
       - id: blacken-docs
         additional_dependencies: [black]
-        exclude: README.md
+        exclude: ^(README.md|paper/paper.md)$
   - repo: https://github.com/pycqa/flake8
     rev: 6.0.0
     hooks:

paper/paper.md

@@ -100,17 +100,14 @@ As a simple demonstration, the example below shows how one can construct a simpl
 ```python
 from jobflow import Flow, job, run_locally
 
-
 @job
 def add(a, b):
     return a + b
 
-
 @job
 def multiply(a, b):
     return a * b
 
-
 job1 = add(1, 2)  # 1 + 2 = 3
 job2 = multiply(job1.output, 3)  # 3 * 3 = 9
 flow = Flow([job1, job2])
@@ -128,23 +125,19 @@ Beyond the typical acyclic graph of jobs, Jobflow fully supports dynamic workflo
 from random import randint
 from jobflow import Flow, Response, job, run_locally
 
-
 @job
 def add(a, b):
     return a + b
 
-
 @job
 def make_list(val):
     return [val] * randint(2, 6)
 
-
 @job
 def add_distributed(vals, c):
     jobs = [add(val, c) for val in vals]
     return Response(replace=Flow(jobs))
 
-
 job1 = add(1, 2)  # 1 + 2 = 3
 job2 = make_list(job1.output)  # e.g., [3, 3, 3]
 job3 = add_distributed(job2.output, 10)  # [3 + 10, 3 + 10, 3 + 10]
@@ -168,7 +161,6 @@ from dataclasses import dataclass
 from jobflow import job, Flow, Maker
 from jobflow.managers.local import run_locally
 
-
 @dataclass
 class ExponentiateMaker(Maker):
     name: str = "Exponentiate"
@@ -178,7 +170,6 @@ class ExponentiateMaker(Maker):
     def make(self, a):
         return a**self.exponent
 
-
 job1 = ExponentiateMaker().make(a=2)  # 2**2 = 4
 job2 = ExponentiateMaker(exponent=3).make(job1.output)  # 4**3 = 64
 flow = Flow([job1, job2])