mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-03-11 21:23:33 -05:00
Fix terminal box alignment in carousel demo YAML files
- Add proper padding to account for emoji display width (2 columns) - Ensure all box content lines are exactly 100 characters wide - Update fix-box-alignment.py to calculate display width correctly - Apply fixes to all 4 carousel demo YMLs This ensures the terminal box borders align properly in generated GIFs.
This commit is contained in:
Vijay Janapa Reddi
@@ -357,21 +357,21 @@ records:
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content: "\e[1;36m│\e[0m \e[1;32m✅ Python 3.11.9\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ NumPy 1.26.4\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Jupyter Lab 4.0.9\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ All dependencies installed\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ All dependencies installed \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m🎉 Ready to build ML systems!\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m 🎉 Ready to build ML systems! \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m📓 Opening module in Jupyter Lab...\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32mBuild the foundation:\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m Build the foundation: \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m • Implement Tensor class \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m • Implement Tensor class \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m • Array operations (add, mul, reshape) \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m • Array operations (add, mul, reshape) \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m • Broadcasting & indexing \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;36mTest inline, iterate fast 🚀\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m Test inline, iterate fast 🚀 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m💡 Tip:\e[0m Code → Run tests → See results instantly \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m💡 NBGrader:\e[0m Automated feedback as you code \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m💡 When done:\e[0m tito module complete 01 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m💡 When done: tito module complete 01 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m🔍 Step 1/3: Running tests...\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m📦 Step 2/3: Exporting to tinytorch/...\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m📦 Step 2/3: Exporting to tinytorch/... \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m💾 Step 3/3: Tracking completion...\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32mYour code is now part of TinyTorch!\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m Your code is now part of TinyTorch! \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33mTry it: \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;37m>>> from tinytorch import Tensor\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;37m>>> from tinytorch import Tensor \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;37m>>> t = Tensor([1, 2, 3])\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;37m>>> t = Tensor([1, 2, 3]) \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33mNext: tito module start 02 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m🔍 Checking prerequisites...\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m🔍 Checking prerequisites... \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 01: Tensor\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 01: Tensor \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 02: Activations\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 02: Activations \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 03: Layers\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 03: Layers \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 04: Losses\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 04: Losses \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 05: Autograd\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 05: Autograd \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 06: Optimizers\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m ✅ Module 06: Optimizers \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;32m✅ Module 07: Training\e[0m \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m📊 Dataset:\e[0m MNIST (60k train, 10k test) \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m📊 Dataset: MNIST (60k train, 10k test) \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m🏗️ Model:\e[0m 784 → 128 → 64 → 10 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m🏗️ Model: 784 → 128 → 64 → 10 \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m⚙️ Using:\e[0m YOUR TinyTorch implementation \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;33m⚙️ Using: YOUR TinyTorch implementation \e[1;36m│\e[0m\r\n"
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content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\e[0m\r\n"
|
||||
- delay: 800
|
||||
@@ -181,13 +181,13 @@ records:
|
||||
- delay: 600
|
||||
content: "\e[1;36m╭──────────────────────────────────────────────────────────────────────────────────────────────────╮\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;32m✅ Test Accuracy: 96.3%\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m ✅ Test Accuracy: 96.3% \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;32m✅ Threshold Met: >95% (1986 baseline)\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m ✅ Threshold Met: >95% (1986 baseline) \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\e[0m\r\n"
|
||||
- delay: 800
|
||||
@@ -195,37 +195,37 @@ records:
|
||||
- delay: 600
|
||||
content: "\e[1;36m╭──────────────────────────────────────────────────────────────────────────────────────────────────╮\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;33m🎉 Milestone 03: MLP (1986) COMPLETE!\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;33m🎉 Milestone 03: MLP (1986) COMPLETE! \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m You've recreated Rumelhart's breakthrough using \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m You've recreated Rumelhart's breakthrough using \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m YOUR OWN implementation of: \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m YOUR OWN implementation of: \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m • Tensor operations \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m • Tensor operations \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m • Activation functions \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m • Activation functions \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m • Neural network layers \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m • Neural network layers \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m • Backpropagation \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m • Backpropagation \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m • Gradient descent optimization \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m • Gradient descent optimization \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;32m💡 You didn't import it. You BUILT it.\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m 💡 You didn't import it. You BUILT it. \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;33mNext milestone:\e[0m tito milestone run 04 \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;33mNext milestone: tito milestone run 04 \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;90m(CNN Revolution - 1998)\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;90m(CNN Revolution - 1998) \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
content: "\e[1;36m│\e[0m \e[1;36m│\e[0m\r\n"
|
||||
- delay: 100
|
||||
content: "\e[1;36m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\e[0m\r\n"
|
||||
- delay: 2000
|
||||
|
||||
105
site/_static/demos/fix-box-alignment.py
Normal file → Executable file
105
site/_static/demos/fix-box-alignment.py
Normal file → Executable file
@@ -4,74 +4,105 @@ Fix box-drawing alignment in Terminalizer YAML files.
|
||||
|
||||
This script ensures all box lines have consistent width by:
|
||||
1. Finding all box-drawing content lines
|
||||
2. Calculating the correct width based on terminal columns
|
||||
2. Calculating the correct width based on terminal columns (100)
|
||||
3. Padding text to fit within the box
|
||||
"""
|
||||
|
||||
import re
|
||||
import yaml
|
||||
from pathlib import Path
|
||||
|
||||
# Terminal width from configs
|
||||
COLS = 100
|
||||
|
||||
def fix_box_line(content, cols=COLS):
|
||||
"""Fix a single box-drawing line to have correct width."""
|
||||
# Extract ANSI codes and actual text
|
||||
ansi_pattern = r'\x1b\[[0-9;]+m'
|
||||
def get_display_width(text):
|
||||
"""
|
||||
Calculate display width accounting for emoji and special characters.
|
||||
Emojis typically take 2 display columns.
|
||||
"""
|
||||
# Remove ANSI escape codes
|
||||
text = re.sub(r'\\e\[[0-9;]+m', '', text)
|
||||
|
||||
# Box top/bottom patterns
|
||||
if '╭' in content and '╮' in content:
|
||||
# Top line: ╭─...─╮
|
||||
return f"\\e[1;36m╭{'─' * (cols - 2)}╮\\e[0m\\r\\n"
|
||||
width = 0
|
||||
for char in text:
|
||||
# Emoji and other wide characters
|
||||
if ord(char) > 0x1F300: # Approximate emoji range
|
||||
width += 2
|
||||
else:
|
||||
width += 1
|
||||
return width
|
||||
|
||||
if '╰' in content and '╯' in content:
|
||||
# Bottom line: ╰─...─╯
|
||||
return f"\\e[1;36m╰{'─' * (cols - 2)}╯\\e[0m\\r\\n"
|
||||
def fix_box_content_line(content):
|
||||
"""Fix a box content line to be exactly 100 characters wide."""
|
||||
# This is a line like: │ ✅ Python 3.11.9 │
|
||||
|
||||
if '│' in content:
|
||||
# Side line with content: │ text... │
|
||||
# Strip ANSI codes to measure actual content
|
||||
text_only = re.sub(ansi_pattern, '', content.replace('\\e', '\x1b'))
|
||||
text_only = text_only.replace('\\r\\n', '').replace('│', '')
|
||||
|
||||
# Calculate padding needed
|
||||
content_width = len(text_only)
|
||||
total_padding = cols - 2 - content_width # -2 for the │ on each side
|
||||
|
||||
if total_padding < 0:
|
||||
# Content too wide, truncate
|
||||
text_only = text_only[:cols - 5] + '...'
|
||||
total_padding = 0
|
||||
|
||||
# Keep original ANSI-formatted content but adjust spacing
|
||||
# This is a simplified version - you may need to preserve exact ANSI codes
|
||||
if '│' not in content:
|
||||
return content
|
||||
|
||||
return content
|
||||
# Extract the content between the │ characters
|
||||
# Pattern: \e[color]│\e[reset] content \e[color]│\e[reset]
|
||||
|
||||
# Remove escape sequences to get clean content
|
||||
clean = content.replace('\\e[1;36m', '').replace('\\e[0m', '').replace('\\e[1;32m', '')
|
||||
clean = clean.replace('\\r\\n', '')
|
||||
|
||||
if not clean.startswith('│') or not clean.endswith('│'):
|
||||
return content
|
||||
|
||||
# Get the inner content
|
||||
inner = clean[1:-1]
|
||||
|
||||
# Calculate how much padding we need
|
||||
# Total width should be 100: │ (1) + content (98) + │ (1)
|
||||
target_inner_width = 98
|
||||
current_width = get_display_width(inner)
|
||||
|
||||
if current_width > target_inner_width:
|
||||
# Content is too wide, we need to truncate
|
||||
# This shouldn't happen with our content, but handle it
|
||||
print(f"Warning: Content too wide ({current_width} > {target_inner_width}): {inner[:50]}...")
|
||||
return content
|
||||
|
||||
# Add padding spaces to the right
|
||||
padding_needed = target_inner_width - current_width
|
||||
padded_inner = inner + (' ' * padding_needed)
|
||||
|
||||
# Reconstruct with ANSI codes
|
||||
result = f"\\e[1;36m│\\e[0m{padded_inner}\\e[1;36m│\\e[0m\\r\\n"
|
||||
|
||||
return result
|
||||
|
||||
def process_yaml_file(filepath):
|
||||
"""Process a single YAML file to fix box alignment."""
|
||||
print(f"Processing {filepath.name}...")
|
||||
|
||||
with open(filepath, 'r') as f:
|
||||
lines = f.readlines()
|
||||
content = f.read()
|
||||
|
||||
# Find all content lines with box characters
|
||||
lines = content.split('\n')
|
||||
modified = False
|
||||
|
||||
for i, line in enumerate(lines):
|
||||
if 'content:' in line and any(char in line for char in ['╭', '╮', '╰', '╯', '│']):
|
||||
# This line contains box-drawing characters
|
||||
if 'content:' in line and '│' in line:
|
||||
# Extract the content string
|
||||
match = re.search(r'content: "(.*)"', line)
|
||||
if match:
|
||||
original = match.group(1)
|
||||
fixed = fix_box_line(original)
|
||||
|
||||
# Skip top and bottom lines (they're already correct)
|
||||
if '╭' in original or '╰' in original:
|
||||
continue
|
||||
|
||||
fixed = fix_box_content_line(original)
|
||||
if fixed != original:
|
||||
lines[i] = line.replace(original, fixed)
|
||||
modified = True
|
||||
print(f" Fixed line {i}: {original[:50]}...")
|
||||
|
||||
if modified:
|
||||
with open(filepath, 'w') as f:
|
||||
f.writelines(lines)
|
||||
f.write('\n'.join(lines))
|
||||
print(f" ✅ Fixed {filepath.name}")
|
||||
else:
|
||||
print(f" ℹ️ No changes needed for {filepath.name}")
|
||||
@@ -81,12 +112,12 @@ def main():
|
||||
demos_dir = Path(__file__).parent
|
||||
yaml_files = list(demos_dir.glob('[0-9][0-9]-*.yml'))
|
||||
|
||||
print(f"Found {len(yaml_files)} YAML files to process\\n")
|
||||
print(f"Found {len(yaml_files)} YAML files to process\n")
|
||||
|
||||
for yaml_file in sorted(yaml_files):
|
||||
process_yaml_file(yaml_file)
|
||||
|
||||
print("\\n✨ Done!")
|
||||
print("\n✨ Done!")
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
Reference in New Issue
Block a user