Quick Start
Get up and running with typstyle in minutes.
Create a simple Typst file:
// example.typ
#import "@preview/cetz:0.2.2": draw, canvas,
#import"@preview/fletcher:0.5.1"as fletcher:diagram,node,edge
#set page( margin:(x:1.2in, y:1in ) )
#set text(font:("Times New Roman",)
)
Mathematical Analysis of Algorithm Performance
Consider the time complexity analysis for sorting algorithms.The bubble sort algorithm has quadratic time complexity.
= Performance Comparison
#figure(
table(columns:(auto, )+(1fr,)*3,
[Algorithm],[Best Case],[Average Case],[Worst Case],
[Bubble Sort],$O(n)$,$O(n^2)$,$O(n^2)$,[Quick Sort],$O(n log n)$,$O(n log n)$,$O(n^2)$,
[Merge Sort],$O(n log n)$,$O(n log n)$,$O(n log n)$),caption:[Time complexity comparison]
)
The mathematical relationship between input size and execution time can be expressed as:
$
T(n)&=sum_(i=1)^(n-1) sum_(j=1)^(n-i) 1\
&= sum_(i=1)^(n-1) (n-i)\
&= sum_(k=1)^(n-1) k "where" k=n-i\
&= (n-1)n/2\
&= O(n^2)
$
#figure(canvas(length:1cm,{
draw.plot.plot(size:(8,6),x-tick-step:none,y-tick-step:none,{
draw.plot.add(((0,0),(1,1),(2,4),(3,9),(4,16)))
})}),caption:[Quadratic growth visualization])// example.typ
#import "@preview/cetz:0.2.2": draw, canvas,
#import"@preview/fletcher:0.5.1"as fletcher:diagram,node,edge
#set page( margin:(x:1.2in, y:1in ) )
#set text(font:("Times New Roman",)
)
Mathematical Analysis of Algorithm Performance
Consider the time complexity analysis for sorting algorithms.The bubble sort algorithm has quadratic time complexity.
= Performance Comparison
#figure(
table(columns:(auto, )+(1fr,)*3,
[Algorithm],[Best Case],[Average Case],[Worst Case],
[Bubble Sort],$O(n)$,$O(n^2)$,$O(n^2)$,[Quick Sort],$O(n log n)$,$O(n log n)$,$O(n^2)$,
[Merge Sort],$O(n log n)$,$O(n log n)$,$O(n log n)$),caption:[Time complexity comparison]
)
The mathematical relationship between input size and execution time can be expressed as:
$
T(n)&=sum_(i=1)^(n-1) sum_(j=1)^(n-i) 1\
&= sum_(i=1)^(n-1) (n-i)\
&= sum_(k=1)^(n-1) k "where" k=n-i\
&= (n-1)n/2\
&= O(n^2)
$
#figure(canvas(length:1cm,{
draw.plot.plot(size:(8,6),x-tick-step:none,y-tick-step:none,{
draw.plot.add(((0,0),(1,1),(2,4),(3,9),(4,16)))
})}),caption:[Quadratic growth visualization])Format it with typstyle:
typstyle example.typtypstyle example.typOutput:
// example.typ
#import "@preview/cetz:0.2.2": canvas, draw
#import "@preview/fletcher:0.5.1" as fletcher: diagram, edge, node
#set page(margin: (x: 1.2in, y: 1in))
#set text(font: ("Times New Roman",))
Mathematical Analysis of Algorithm Performance
Consider the time complexity analysis for sorting algorithms.The bubble sort algorithm has quadratic time complexity.
= Performance Comparison
#figure(
table(
columns: (auto,) + (1fr,) * 3,
[Algorithm], [Best Case], [Average Case], [Worst Case],
[Bubble Sort], $O(n)$, $O(n^2)$, $O(n^2)$,
[Quick Sort], $O(n log n)$, $O(n log n)$, $O(n^2)$,
[Merge Sort], $O(n log n)$, $O(n log n)$, $O(n log n)$,
),
caption: [Time complexity comparison],
)
The mathematical relationship between input size and execution time can be expressed as:
$
T(n) & =sum_(i=1)^(n-1) sum_(j=1)^(n-i) 1 \
& = sum_(i=1)^(n-1) (n-i) \
& = sum_(k=1)^(n-1) k "where" k=n-i \
& = (n-1)n/2 \
& = O(n^2)
$
#figure(
canvas(length: 1cm, {
draw.plot.plot(size: (8, 6), x-tick-step: none, y-tick-step: none, {
draw.plot.add(((0, 0), (1, 1), (2, 4), (3, 9), (4, 16)))
})
}),
caption: [Quadratic growth visualization],
)
// example.typ
#import "@preview/cetz:0.2.2": canvas, draw
#import "@preview/fletcher:0.5.1" as fletcher: diagram, edge, node
#set page(margin: (x: 1.2in, y: 1in))
#set text(font: ("Times New Roman",))
Mathematical Analysis of Algorithm Performance
Consider the time complexity analysis for sorting algorithms.The bubble sort algorithm has quadratic time complexity.
= Performance Comparison
#figure(
table(
columns: (auto,) + (1fr,) * 3,
[Algorithm], [Best Case], [Average Case], [Worst Case],
[Bubble Sort], $O(n)$, $O(n^2)$, $O(n^2)$,
[Quick Sort], $O(n log n)$, $O(n log n)$, $O(n^2)$,
[Merge Sort], $O(n log n)$, $O(n log n)$, $O(n log n)$,
),
caption: [Time complexity comparison],
)
The mathematical relationship between input size and execution time can be expressed as:
$
T(n) & =sum_(i=1)^(n-1) sum_(j=1)^(n-i) 1 \
& = sum_(i=1)^(n-1) (n-i) \
& = sum_(k=1)^(n-1) k "where" k=n-i \
& = (n-1)n/2 \
& = O(n^2)
$
#figure(
canvas(length: 1cm, {
draw.plot.plot(size: (8, 6), x-tick-step: none, y-tick-step: none, {
draw.plot.add(((0, 0), (1, 1), (2, 4), (3, 9), (4, 16)))
})
}),
caption: [Quadratic growth visualization],
)
To modify the file directly:
typstyle -i example.typtypstyle -i example.typcat example.typ | typstyle > formatted.typcat example.typ | typstyle > formatted.typ# Format specific files
typstyle -i file1.typ file2.typ
# Format entire directory
typstyle -i src/
# Format with specific line width
typstyle -l 100 -i src/# Format specific files
typstyle -i file1.typ file2.typ
# Format entire directory
typstyle -i src/
# Format with specific line width
typstyle -l 100 -i src/Use check mode in CI/CD to ensure code is properly formatted:
typstyle --check src/
typstyle --diff src/typstyle --check src/
typstyle --diff src/This exits with code 0 if files are properly formatted, non-zero otherwise.
# Set maximum line width to 100 characters
typstyle -l 100 file.typ# Set maximum line width to 100 characters
typstyle -l 100 file.typ# Use 4 spaces for indentation instead of default 2
typstyle -t 4 file.typ# Use 4 spaces for indentation instead of default 2
typstyle -t 4 file.typ# Disable automatic import sorting
typstyle --no-reorder-import-items file.typ# Disable automatic import sorting
typstyle --no-reorder-import-items file.typ# Enable text wrapping in markup
typstyle --wrap-text file.typ# Enable text wrapping in markup
typstyle --wrap-text file.typ- Install Tinymist extension
-
Add to
settings.jsonsettings.json:{ "tinymist.formatterMode": "typstyle", "editor.formatOnSave": true }{ "tinymist.formatterMode": "typstyle", "editor.formatOnSave": true }
- Learn about features
- See detailed CLI usage