Import Python modules from dicts and JSON formatted documents.

Overview

Paker

Build Version Version

Paker is module for importing Python packages/modules from dictionaries and JSON formatted documents. It was inspired by httpimporter.

Important: Since v0.6.0 paker supports importing .pyd and .dll modules directly from memory. This was achieved by using _memimporter from py2exe project. Importing .so files on Linux still requires writing them to disk.

Installation

From PyPI

pip install paker -U

From source

git clone https://github.com/desty2k/paker.git
cd paker
pip install .

Usage

In Python script

You can import Python modules directly from string, dict or bytes (without disk IO).

import paker
import logging

MODULE = {"somemodule": {"type": "module", "extension": "py", "code": "fun = lambda x: x**2"}}
logging.basicConfig(level=logging.NOTSET)

if __name__ == '__main__':
    with paker.loads(MODULE) as loader:
        # somemodule will be available only in this context
        from somemodule import fun
        assert fun(2), 4
        assert fun(5), 25
        print("6**2 is {}".format(fun(6)))
        print("It works!")

To import modules from .json files use load function. In this example paker will serialize and import mss package.

import paker
import logging

file = "mss.json"
logging.basicConfig(level=logging.NOTSET)

# install mss using `pip install mss`
# serialize module
with open(file, "w+") as f:
    paker.dump("mss", f, indent=4)

# now you can uninstall mss using `pip uninstall mss -y`
# load package back from dump file
with open(file, "r") as f:
    loader = paker.load(f)

import mss
with mss.mss() as sct:
    sct.shot()

# remove loader and clean the cache
loader.unload()

try:
    # this will throw error
    import mss
except ImportError:
    print("mss unloaded successfully!")

CLI

Paker can also work as a standalone script. To dump module to JSON dict use dump command:

paker dump mss

To recreate module from JSON dict use load:

paker load mss.json

Show all modules and packages in .json file

paker list mss.json

How it works

When importing modules or packages Python iterates over importers in sys.meta_path and calls find_module method on each object. If the importer returns self, it means that the module can be imported and None means that importer did not find searched package. If any importer has confirmed the ability to import module, Python executes another method on it - load_module. Paker implements its own importer called jsonimporter, which instead of searching for modules in directories, looks for them in Python dictionaries

To dump module or package to JSON document, Paker recursively iterates over modules and creates dict with code and type of each module and submodules if object is package.

You might also like...
An executor that loads ONNX models and embeds documents using the ONNX runtime.

ONNXEncoder An executor that loads ONNX models and embeds documents using the ONNX runtime. Usage via Docker image (recommended) from jina import Flow

Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.

Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch

Turning SymPy expressions into PyTorch modules.

sympytorch A micro-library as a convenience for turning SymPy expressions into PyTorch Modules. All SymPy floats become trainable parameters. All SymP

DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms

DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme

Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules

DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr

Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules

DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr

Weight initialization schemes for PyTorch nn.Modules

nninit Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin. ##Update This repo has been

Pytorch modules for paralel models with same architecture. Ideal for multi agent-based systems
Pytorch modules for paralel models with same architecture. Ideal for multi agent-based systems

WideLinears Pytorch parallel Neural Networks A package of pytorch modules for fast paralellization of separate deep neural networks. Ideal for agent-b

Stacs-ci - A set of modules to enable integration of STACS with commonly used CI / CD systems
Stacs-ci - A set of modules to enable integration of STACS with commonly used CI / CD systems

Static Token And Credential Scanner CI Integrations What is it? STACS is a YARA

Comments
  • psutil example exits with module not found when using _memimporter

    psutil example exits with module not found when using _memimporter

    I pulled latest releases zip file, ran python setup.py build and attempted to run the psutil example with the compiled pyd. This resulted in the following error:

    DEBUG:jsonimporter:searching for pwd
    DEBUG:jsonimporter:searching for psutil._common
    INFO:jsonimporter:psutil._common has been imported successfully
    DEBUG:jsonimporter:searching for psutil._compat
    INFO:jsonimporter:psutil._compat has been imported successfully
    DEBUG:jsonimporter:searching for psutil._pswindows
    DEBUG:jsonimporter:searching for psutil._psutil_windows
    DEBUG:jsonimporter:searching for psutil._psutil_windows
    INFO:jsonimporter:using _memimporter to load '.pyd' file
    INFO:jsonimporter:unloaded all modules
    Traceback (most recent call last):
      File "c:\Users\User\Desktop\paker-0.7.1\paker-0.7.1\build\lib.win-amd64-cpython-310\psutil_example.py", line 20, in <module>
        import psutil
      File "c:\Users\User\Desktop\paker-0.7.1\paker-0.7.1\build\lib.win-amd64-cpython-310\paker\importers\jsonimporter.py", line 115, in load_module
        exec(jsonmod["code"], mod.__dict__)
      File "<string>", line 107, in <module>
      File "c:\Users\User\Desktop\paker-0.7.1\paker-0.7.1\build\lib.win-amd64-cpython-310\paker\importers\jsonimporter.py", line 115, in load_module
        exec(jsonmod["code"], mod.__dict__)
      File "<string>", line 35, in <module>
      File "c:\Users\User\Desktop\paker-0.7.1\paker-0.7.1\build\lib.win-amd64-cpython-310\paker\importers\jsonimporter.py", line 134, in load_module
        mod = _memimporter.import_module(fullname, path, initname, self._get_data, spec)
    ImportError: MemoryLoadLibrary failed loading psutil\_psutil_windows.pyd: The specified module could not be found. (126)
    

    Is this an issue with how I compiled memimporter, or something else?

    opened by rkbennett 1
Releases(v0.7.1)
Owner
Wojciech Wentland
Wojciech Wentland
details on efforts to dump the Watermelon Games Paprium cart

Reminder, if you like these repos, fork them so they don't disappear https://github.com/ArcadeHustle/WatermelonPapriumDump/fork Big thanks to Fonzie f

Hustle Arcade 29 Dec 11, 2022
The Illinois repository for Climatehack (https://climatehack.ai/). We won 1st place!

Climatehack This is the repository for Illinois's Climatehack Team. We earned first place on the leaderboard with a final score of 0.87992. An overvie

Jatin Mathur 20 Jun 09, 2022
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis

SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis Pretrained Models In this work, we created synthetic tissue

Emirhan Kurtuluş 1 Feb 07, 2022
CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation

CSKG: The CommonSense Knowledge Graph CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: AT

USC ISI I2 85 Dec 12, 2022
Scalable Graph Neural Networks for Heterogeneous Graphs

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

Facebook Research 67 Dec 03, 2022
How to Train a GAN? Tips and tricks to make GANs work

(this list is no longer maintained, and I am not sure how relevant it is in 2020) How to Train a GAN? Tips and tricks to make GANs work While research

Soumith Chintala 10.8k Dec 31, 2022
Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, L

3 Dec 02, 2022
Improving Convolutional Networks via Attention Transfer (ICLR 2017)

Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran

Sergey Zagoruyko 1.4k Dec 23, 2022
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images

MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images This repository contains the implementation of our paper MetaAvatar: Learni

sfwang 96 Dec 13, 2022
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better

weijunhong 4 Aug 15, 2022
PoseCamera is python based SDK for human pose estimation through RGB webcam.

PoseCamera PoseCamera is python based SDK for human pose estimation through RGB webcam. Install install posecamera package through pip pip install pos

WonderTree 7 Jul 20, 2021
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in

Valeo.ai 20 Jun 21, 2022
Code base of object detection

rmdet code base of object detection. 环境安装: 1. 安装conda python环境 - `conda create -n xxx python=3.7/3.8` - `conda activate xxx` 2. 运行脚本,自动安装pytorch1

3 Mar 08, 2022
HarDNeXt: Official HarDNeXt repository

HarDNeXt-Pytorch HarDNeXt: A Stage Receptive Field and Connectivity Aware Convolution Neural Network HarDNeXt-MSEG for Medical Image Segmentation in 0

5 May 26, 2022
Distributed Deep learning with Keras & Spark

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Max Pumperla 1.6k Jan 05, 2023
Logistic Bandit experiments. Official code for the paper "Jointly Efficient and Optimal Algorithms for Logistic Bandits".

Code for the paper Jointly Efficient and Optimal Algorithms for Logistic Bandits, by Louis Faury, Marc Abeille, Clément Calauzènes and Kwang-Sun Jun.

Faury Louis 1 Jan 22, 2022
A PyTorch-based library for semi-supervised learning

News If you want to join TorchSSL team, please e-mail Yidong Wang ([email protected]<

1k Jan 06, 2023
Code for ICCV2021 paper SPEC: Seeing People in the Wild with an Estimated Camera

SPEC: Seeing People in the Wild with an Estimated Camera [ICCV 2021] SPEC: Seeing People in the Wild with an Estimated Camera, Muhammed Kocabas, Chun-

Muhammed Kocabas 187 Dec 26, 2022
Pytorch implementation of the paper Improving Text-to-Image Synthesis Using Contrastive Learning

T2I_CL This is the official Pytorch implementation of the paper Improving Text-to-Image Synthesis Using Contrastive Learning Requirements Linux Python

42 Dec 31, 2022
a short visualisation script for pyvideo data

PyVideo Speakers A CLI that visualises repeat speakers from events listed in https://github.com/pyvideo/data Not terribly efficient, but you know. Ins

Katie McLaughlin 3 Nov 24, 2021