embdes 1.0.2

Professional build automation for EmbedDesire Python applications

EmbedDesire - Professional Python Asset Embedding

embdes is a production-ready tool for embedding static resources (images, sounds, text files, folders) directly into Python applications and building standalone executables with PyInstaller.

Features

• Embed resources into Python applications with optional compression
• Automatic extraction with built-in caching (100% cache hit rate)
• Development/Runtime modes — swap between reading from disk and reading from embedded data with one call
• PyInstaller integration — automated build process via embdes CLI
• Persistent storage — save/load embedded data manually if needed
• Production-ready — comprehensive logging, validation, error handling
• Cross-platform — Windows, macOS, Linux support
• Global CLI — callable from any directory as embdes command

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Installation

pip install embdes

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How It Works

embed() always returns the original file path. What changes between modes is what happens under the hood:

Mode	set_runtime_mode(...)	embed() behavior
Runtime mode	True	Skips embedding — just returns the path so you read from disk as normal
Embedded mode	False	Reads and stores the file in memory — the returned path is used to access embedded data in the built exe

This means your app code stays identical in both modes — you always just open(embed(...)).

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Basic Usage

from embeddesire import embed, set_runtime_mode

set_runtime_mode(True)  # Read from disk (development)

embedded = embed(".\\hello.txt", id="hello", compress=True)

with open(embedded, "r") as f:
    print(f.read())

Switch to set_runtime_mode(False) when you want to work with embedded data (e.g. inside a built exe where the original files no longer exist on disk).

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Building a Standalone Exe

Using embdes (Recommended)

embdes automates everything. Write your app normally, then build with one command.

app.py

from embeddesire import embed, set_runtime_mode

set_runtime_mode(True)  # During dev, reads from disk

config  = embed("config.json",    id="config",  compress=False)
sprites = embed("assets/sprites/",id="sprites", compress=True)
sounds  = embed("assets/sounds/", id="sounds",  compress=True)

with open(config, "r") as f:
    print(f.read())

# Use sprites and sounds paths however your app needs them

Build

embdes app.py

embdes will:

1. Validate all paths passed to embed() exist on disk
2. Execute your script to collect all embed() calls
3. Save the embedded data to embedded_data.pkl
4. Call PyInstaller with the pickle bundled in automatically
5. Clean up temporary files

The resulting exe in dist/ has all your assets baked in — no external files needed.

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Manual Build (Full Control)

Use this if you have an existing PyInstaller setup, a .spec file, or prefer not to use embdes.

Step 1 — Generate the pickle

Run a small preparation script once before building:

# prepare.py
from embeddesire import embed, save_embedded, set_runtime_mode

set_runtime_mode(False)  # Must be False so embed() actually stores the data

embed("config.json",    id="config",  compress=False)
embed("assets/sprites/",id="sprites", compress=True)
embed("assets/sounds/", id="sounds",  compress=True)

save_embedded("embedded_data.pkl")

python prepare.py

Step 2 — Pass the pickle to PyInstaller yourself

pyinstaller app.py --onefile --add-data "embedded_data.pkl;."

Step 3 — Load it inside the exe

# app.py
import sys, os
from embeddesire import embed, set_runtime_mode, load_embedded, extract

if getattr(sys, "frozen", False):
    # Inside the exe — load the bundled pickle, then use extract() to get files out
    load_embedded(os.path.join(sys._MEIPASS, "embedded_data.pkl"))
    config_dir = extract("config")
    config_path = os.path.join(config_dir, "config.json")
    with open(config_path, "r") as f:
        print(f.read())
else:
    # Development — read from disk as normal
    set_runtime_mode(True)
    config = embed("config.json", id="config", compress=False)
    with open(config, "r") as f:
        print(f.read())

Note: extract() only works on data already in memory from load_embedded(). It does not read from disk on its own.

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Embedding Options

Disable compression for pre-compressed formats

Compression (compress=True) is on by default. Turn it off for files already compressed to avoid wasted CPU and larger output:

embed("photo.jpg",   id="photo",   compress=False)
embed("music.mp3",   id="music",   compress=False)
embed("archive.zip", id="archive", compress=False)

Extract to a specific location (manual builds)

path = extract("sprites", output_path="./runtime/sprites")

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Managing Embedded Resources

from embeddesire import get_embedded_resources, remove_embedded_resource, get_cache_stats, clear_cache

# See all IDs currently embedded in memory
print(get_embedded_resources())
# ['config', 'sprites', 'sounds']

# Remove one to free memory
remove_embedded_resource("sounds")

# How many extract() calls were served from cache vs freshly written to disk
print(get_cache_stats())
# {'hits': 8, 'misses': 3, 'current_size': 0}

# Delete all temp extraction directories (next extract() call will re-extract)
clear_cache()

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Error Handling

from embeddesire import embed, extract, load_embedded
from embeddesire import EmbedError, ExtractError, PersistenceError, ValidationError

try:
    embed("nonexistent/path/file.txt", id="data")
except EmbedError as e:
    print(f"Embed failed: {e}")

try:
    extract("id_that_was_never_embedded")
except ExtractError as e:
    print(f"Extract failed: {e}")

try:
    load_embedded("missing_or_corrupt.pkl")
except PersistenceError as e:
    print(f"Load failed: {e}")

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Logging

from embeddesire import configure_logging, LogLevel

configure_logging(LogLevel.DEBUG)    # Full trace — sizes, cache hits, paths
configure_logging(LogLevel.WARNING)  # Quiet — only problems reported
configure_logging(LogLevel.INFO, format_string="%(levelname)s | %(message)s")

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CLI Reference

embdes <script.py> [pyinstaller_args...]

Arguments after the script are passed directly to PyInstaller:

embdes app.py                           # Basic build
embdes app.py --windowed                # No console window
embdes app.py --windowed --icon=app.ico # With custom icon
embdes app.py --name=MyApp              # Custom exe name
embdes app.py --add-data "extra.db;."   # Bundle extra files too

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API Reference

Function	Description
embed(path, id, compress=True)	Embed a file or folder; always returns the original path
extract(id, output_path=None)	Extract an in-memory resource to disk (cached)
set_runtime_mode(value)	True = read from disk, False = read from embedded data
save_embedded(file_path)	Save all embedded data to a pickle file
load_embedded(file_path)	Load embedded data from a pickle file into memory
clear_cache()	Delete all temp extraction directories
get_cache_stats()	Return {hits, misses, current_size} dict
get_embedded_resources()	List all currently embedded IDs
remove_embedded_resource(id)	Remove a resource from memory
configure_logging(level, format_string)	Set log level and format

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Configuration

export EMBEDDESIRE_COMPRESSION_LEVEL=9      # zlib level 0-9 (default 6)
export EMBEDDESIRE_MAX_FILE_SIZE=50000000   # bytes (default 100 MB)
export EMBEDDESIRE_MAX_CACHE_SIZE=250000000 # bytes (default 500 MB)

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Requirements

• Python 3.7+
• PyInstaller (required only for embdes CLI builds)

License

MIT License — See LICENSE file