Pack Python codebases into Markdown optimized for LLM context delivery (pack/unpack/patch/apply)
Project description
codecrate
codecrate turns a Python repository into a Markdown "context pack" optimized for LLM consumption, with full round-trip support:
pack: repo → context.mdunpack: context.md → reconstructed filespatch: old context.md + current repo → diff-only patch.mdapply: patch.md → apply changes to repo
Features
- Markdown-native output: Generates self-contained Markdown files with syntax highlighting
- Symbol index: Quick navigation to functions and classes
- Deduplication: Optionally deduplicate identical function bodies to save tokens
- Two layout modes:
stubs: Compact file stubs with function bodies in a separate "Function Library"full: Complete file contents (no stubbing)
- Round-trip support: Reconstruct original files exactly from Markdown packs
- Diff generation: Create minimal patch Markdown files showing only changed code
- Gitignore support: Respect
.gitignorewhen scanning files
Installation
pip install -e .
Or for development:
pip install -e ".[dev]"
Quick Start
Pack a Repository
Pack your current directory into context.md:
codecrate pack .
Pack with specific output file:
codecrate pack . -o my_project.md
Unpack to Reconstruct Files
Reconstruct files from a packed Markdown:
codecrate unpack context.md -o reconstructed/
Generate and Apply Patches
- Pack your repository as a baseline:
codecrate pack . -o baseline.md
-
Make changes to your code
-
Generate a patch:
codecrate patch baseline.md . -o changes.md
- Apply the patch:
codecrate apply changes.md .
Configuration
Create a codecrate.toml file in your repository root:
[codecrate]
# File patterns to include (default: ["**/*.py"])
include = ["**/*.py"]
# File patterns to exclude
exclude = ["**/test_*.py", "**/tests/**"]
# Deduplicate identical function bodies (default: false)
dedupe = true
# Keep docstrings in stubbed file view (default: true)
keep_docstrings = true
# Respect .gitignore when scanning (default: true)
respect_gitignore = true
# Output layout: "auto", "stubs", or "full" (default: "auto")
# - auto: use stubs only if dedupe collapses something
# - stubs: always use stubs + Function Library
# - full: emit complete file contents
layout = "auto"
# Split output into multiple files if char count exceeds this (0 = no split)
split_max_chars = 0
Command Reference
pack - Pack Repository to Markdown
codecrate pack <root> [OPTIONS]
Options:
-o, --output PATH: Output markdown path (default:context.md)--dedupe: Deduplicate identical function bodies--layout {auto,stubs,full}: Output layout mode--keep-docstrings/--no-keep-docstrings: Keep docstrings in stubs--respect-gitignore/--no-respect-gitignore: Respect.gitignore--include GLOB: Include glob pattern (repeatable)--exclude GLOB: Exclude glob pattern (repeatable)--split-max-chars N: Split output into.partN.mdfiles
unpack - Reconstruct Files from Markdown
codecrate unpack <markdown> -o <out-dir>
Options:
-o, --out-dir PATH: Output directory for reconstructed files (required)
patch - Generate Diff-Only Patch
codecrate patch <old_markdown> <root> [OPTIONS]
Options:
-o, --output PATH: Output patch markdown (default:patch.md)
apply - Apply Patch to Repository
codecrate apply <patch_markdown> <root>
validate-pack - Validate Pack
codecrate validate-pack <markdown> [--root PATH]
Options:
--root PATH: Optional repo root to compare reconstructed files against
Layout Modes
Stubs Mode (Default for auto when dedupe is effective)
Creates compact file stubs with function bodies replaced by markers:
def f(x):
... # ↪ FUNC:0F203CE2
class C:
def m(self):
... # ↪ FUNC:6F8ECF73
Function bodies are stored in a separate "Function Library" section:
## Function Library
### 0F203CE2 — `a.f` (a.py:L1–L2)
```python
def f(x):
return x + 1
```
6F8ECF73 — a.C.m (a.py:L5–L6)
def m(self):
return 42
This is ideal for:
- LLMs with limited context windows
- Repositories with duplicate code (when using `--dedupe`)
- Code review and analysis workflows
### Full Mode
Emits complete file contents without stubbing:
```python
def f(x):
return x + 1
class C:
def m(self):
return 42
This is ideal for:
- Repositories without much duplicate code
- When you need complete context in one place
- When token limits are not a concern
Workflow Example
Initial Pack
# Create a baseline pack of your repository
codecrate pack . -o baseline.md
# Send baseline.md to an LLM for analysis
# LLM can navigate using the Symbol Index
# and read full code in the Files section
Iterate with LLM
# After the LLM suggests changes, generate a patch
codecrate patch baseline.md . -o iteration1.md
# Send iteration1.md to the LLM (much smaller than full pack)
# Apply the LLM's changes
codecrate apply iteration1.md .
# Create new baseline for next iteration
codecrate pack . -o baseline.md
Advanced Usage
Packing Multiple Projects
# Pack different directories separately
codecrate pack src/backend -o backend.md
codecrate pack src/frontend -o frontend.md
# Or pack with specific include patterns
codecrate pack . --include "**/*.py" --exclude "**/migrations/**"
Handling Large Contexts
# Split into multiple files to fit context windows
codecrate pack . --split-max-chars 50000
# This creates context.md, context.part1.md, context.part2.md, etc.
Deduplication
# Enable deduplication to save tokens on duplicate code
codecrate pack . --dedupe
# Deduplication is most effective when you have:
# - Copy-pasted functions
# - Boilerplate code
# - Similar utility functions across modules
How It Works
- Discovery: Scans files according to include/exclude patterns
- Parsing: Extracts symbol information (functions, classes) using Python's AST
- Packing: Creates a structured manifest and canonical function definitions
- Rendering: Generates Markdown with directory tree, symbol index, and file contents
- Validation: Ensures round-trip consistency with SHA256 checksums
The Markdown format is designed to be:
- Self-contained: All necessary information in one file
- Navigable: Symbol index with jump links
- Reversible: Can reconstruct original files exactly
- Diff-friendly: Easy to generate minimal patches
License
MIT
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