A library that can print Python objects in human readable format

Overview

objprint

build coverage pypi support-version license commit

A library that can print Python objects in human readable format

Install

pip install objprint

Usage

op

Use op() (or objprint()) to print objects.

from objprint import op

class Position:
    def __init__(self, x, y):
        self.x = x
        self.y = y

class Player:
    def __init__(self):
        self.name = "Alice"
        self.age = 18
        self.items = ["axe", "armor"]
        self.coins = {"gold": 1, "silver": 33, "bronze": 57}
        self.position = Position(3, 5)

op(Player())
<Player 0x7fe44e1e3070
  .age = 18,
  .coins = {'bronze': 57, 'gold': 1, 'silver': 33},
  .items = ['axe', 'armor'],
  .name = 'Alice',
  .position = <Position
    .x = 3,
    .y = 5
  >
>

You can print multiple objects just like print, except op will print them in separate lines

op([1, 2], {'a': 1})
[1, 2]
{'a': 1}

add_objprint

If you want to use print() to print your object, you can also use the class decorator add_objprint to add __str__ method for your class.

from objprint import add_objprint

class Position:
    def __init__(self, x, y):
        self.x = x
        self.y = y

@add_objprint
class Player:
    def __init__(self):
        self.name = "Alice"
        self.age = 18
        self.items = ["axe", "armor"]
        self.coins = {"gold": 1, "silver": 33, "bronze": 57}
        self.position = Position(3, 5)

# This will print the same thing as above
print(Player())

objstr

If you want the str representation of the object, instead of printing it on the screen, you can use objstr function

from objprint import objstr

s = objstr(my_object)

objjson

objprint supports print objects to json to make it easier to serialze an object.

objjson returns a jsonifiable object that can be dumped with json.dumps

from objprint import objjson

json_obj = objjson(Player())

print(json.dumps(json_obj, indent=2))
{
  ".type": "Player",
  "name": "Alice",
  "age": 18,
  "items": [
    "axe",
    "armor"
  ],
  "coins": {
    "gold": 1,
    "silver": 33,
    "bronze": 57
  },
  "position": {
    ".type": "Position",
    "x": 3,
    "y": 5
  }
}

You can use op to print in json format directly with format="json". You can pass in argument for json.dumps

op(Player(), format="json", indent=2)

add_objprint also works with format="json"

@add_objprint(format="json", indent=2)
class Player:
    pass

include/exclude attributes

You can include/exclude attributes using regular expression so objprint will only print out the attributes you are interested in.

op(Player(), include=["name"])
<Player
  .name = 'Alice'
>
op(Player(), exclude=[".*s"])
<Player 0x7fe44e1e3070
  .name = 'Alice',
  .age = 18,
  .position = <Position
    .x = 3,
    .y = 5
  >
>

If you specify both include and exclude, it will do a inclusive check first, then filter out the attributes that match exclusive check.

include and exclude arguments work on objprint, objstr and @add_objprint.

config

objprint formats the output based on some configs

  • config_name(default_value) - this config's explanation
  • depth(100) - how deep objprint goes into nested data structures
  • indent(2) - the indentation
  • width(80) - the maximum width a data structure will be presented as a single line
  • elements(-1) - the maximum number of elements that will be displayed, -1 means no restriction
  • color(True) - whether to use colored scheme
  • skip_recursion(True) - whether skip printing recursive data, which would cause infinite recursion without depth constraint
  • honor_existing(True) - whether to use the existing user defined __repr__ or __str__ method

You can set the configs globally using config function

from objprint import config

config(indent=4)

Or you can do a one time config by passing the arguments into objprint function

from objprint import op

op(var, indent=4)

install

Maybe you don't want to import op in every single file that you want to use. You can use install to make it globally accessible

from objprint import install

# Now you can use op() in any file
install()

# You can specify a name for objprint()
install("my_print")
my_print(my_object)

Bugs/Requests

Please send bug reports and feature requests through github issue tracker.

License

Copyright Tian Gao, 2020-2021.

Distributed under the terms of the Apache 2.0 license.

Comments
  • 在面对继承自pydantic里BaseModel的实例时无法得到预期的输出

    在面对继承自pydantic里BaseModel的实例时无法得到预期的输出

    如题

    from pydantic import BaseModel
    from objprint import op
    
    
    class pyt_class(BaseModel):
        x: int
        y: int
    
    
    obj_test = pyt_class(x=0, y=1)
    
    op(obj_test)
    print(obj_test)
    

    他打印:

    x=0 y=1
    x=0 y=1
    

    希望后续更新能够支持! (B站码农高天的视频我是期期都看,期期都三连)

    opened by Sclock 3
  • Also print the actual expression whose value is being printed

    Also print the actual expression whose value is being printed

    The https://github.com/gruns/icecream lib has an useful feature where it also prints the expression. Please see the following example:

    d = {'key': {1: 'one'}}
    ic(d['key'][1])
    
    class klass():
        attr = 'yep'
    ic(klass.attr)
    

    It prints:

    ic| d['key'][1]: 'one'
    ic| klass.attr: 'yep'
    

    As you can see icecream lib also prints the expression d['key'][1]. Is it possible to add this feature? This is the only feature holding me back from switching to objprint.

    opened by riyadparvez 3
  • Duplicate output when op() argument wasn't an object.

    Duplicate output when op() argument wasn't an object.

    import hashlib op(hashlib) <module 'hashlib' from 'C:\Users\guojoan\AppData\Local\Programs\Python\Python310\lib\hashlib.py'> <module 'hashlib' from 'C:\Users\guojoan\AppData\Local\Programs\Python\Python310\lib\hashlib.py'>

    a = [] a.append(a) op(a) [[ ... ]] [[...]]

    and so on

    opened by CokeStudios 2
  • type 类创建问题

    type 类创建问题

    通过type 构建的 class 通过 op 正确打印,这个feature 能否实现?

    from objprint import op
    
    class Action:
        pass
    
    def Category(label):
        return type("MCategory", (Action,), {"label": label,
                                            "__type__": "category"})
    
    
    class ECategory(Action):
        def __init__(self,label):
            self.label = label
            self.__type__ = 'category'
    
    
    
    mm = Category('test')
    nn = ECategory('test')
    op(mm)
    op(nn)
    
    >> <class '__main__.MCategory'>
    >> <UCategory 0x1f2da7b2b00
    >>   .label = 'test'
    >> >
    
    
    opened by wuqingjing2010 2
  • 如何实现“增量”打印?

    如何实现“增量”打印?

    您好!我正在使用objprint跟踪迭代过程,代码大致如下:

    for i in range(i_max):
        obj.step()
        op(obj)
    

    已知obj中有些变量在执行step后是不发生改变的,在第二次到最后一次调用op时,是否能够不打印这些变量?也就是只打印发生了变化的变量?

    opened by Saltsmart 2
  • weird escaped characters in jupyter notebook's output

    weird escaped characters in jupyter notebook's output

    I used pyreadstat module to read a simple SAS file. the code goes like this in jupyter notebook

    import pyreadstat as pyrs
    from objprint import op
    
    sas_path = './test_sas/foo.sas7bdat'
    df, meta = pyrs.read_sas7bdat(sas_path, metadataonly=True)
    # just wanted to check out what meta contains 
    op(meta)
    

    the brief output of current cell seems normal

    Output exceeds the [size limit]. Open the full output data[ in a text editor]
    <metadata_container 0x1bcf4bfa3e0
      .column_labels = [
        'projectid',
        'project',
    ...
        'project': '$'
      },
      .variable_value_labels = {}
    >
    <pyreadstat._readstat_parser.metadata_container at 0x1bcf4bfa3e0>
    

    but after I clicked "in a text editor", the first lines look like this:

    <metadata_container 0x1bcf4bfa3e0
      .column_labels = [
        'projectid',
        'project',
    

    the weird characters actually look like small suqares contains 3 small letters ESC in the text editor.

    opened by Asuralf 2
  • 在面对Enum对象时,输出的结果不符合预期。

    在面对Enum对象时,输出的结果不符合预期。

    测试代码:

    from enum import Enum
    from objprint import op,add_objprint
    
    class temp_a(Enum):
        a = 1
    
    @add_objprint
    class temp_b(Enum):
        b = 1
    
    print("temp_a:\n",temp_a,"\n")
    
    print("temp_a.a:\n",temp_a.a,"\n")
    
    print("op_temp_a:")
    op(temp_a)
    print("\n")
    
    print("op_temp_a.a:")
    op(temp_a.a)
    print("\n")
    
    print("================================================================\n")
    
    print("temp_b:\n",temp_b,"\n")
    
    print("temp_b.b:\n",temp_b.b,"\n")
    
    print("op_temp_b:")
    op(temp_b)
    print("\n")
    
    print("op_temp_b.b:")
    op(temp_b.b)
    print("\n")
    

    输出:

    temp_a:
     <enum 'temp_a'> 
    
    temp_a.a:
     temp_a.a
    
    op_temp_a:
    <enum 'temp_a'>
    
    
    op_temp_a.a:
    temp_a.a
    
    
    ================================================================
    
    temp_b:
     <enum 'temp_b'>
    
    temp_b.b:
     <temp_b 0x24a740c2ee0
      .__objclass__ = <enum 'temp_b'>,
      ._name_ = 'b',
      ._value_ = 1
    >
    
    op_temp_b:
    <enum 'temp_b'>
    
    
    op_temp_b.b:
    <temp_b 0x24a740c2ee0
      .__objclass__ = <enum 'temp_b'>,
      ._name_ = 'b',
      ._value_ = 1
    >
    

    符合直觉的结果应该是:

    class temp_a(Enum):
        a = 1
    op(temp_a)
    

    输出:

     <temp_a 0xFFFFFFFF
      .__objclass__ = <enum 'temp_a'>,
      .temp_a.a = < xxxxxxx
          ._name_ = 'b',
          ._value_ = 1
      >
    >
    
    opened by Sclock 2
  • 大佬,objprint可以打印出函数的内容吗?类似于js中console.log()方法。

    大佬,objprint可以打印出函数的内容吗?类似于js中console.log()方法。

    //JavaScript function ad(a, b) {

    return a + b;
    

    }

    console.log(ad.toString())

    //输出 // function ad(a, b) { // // return a + b; // }

    //python def ad(a,b): return a+b print(ad)

    输出

    <function ad at 0x000002511B318550>

    opened by xuxiaobo-bobo 1
  • Change the output order of line number and arg name

    Change the output order of line number and arg name

    For the following example:

    from objprint import config, install, objjson, op
    
    config(line_number=True)
    config(arg_name=True)
    
    x = 1
    op(x)
    

    This is the output right now:

    x:
    <module> (/path/to/objprint-test.py:7)
    1
    

    What I think more intuitive is argument name followed by the value and the file and line number at the top. In this particular case:

    <module> (/path/to/objprint-test.py:7)
    x:
    1
    

    Any thoughts?

    opened by riyadparvez 1
  • question: how to use install()

    question: how to use install()

    I created two python file to play with the install() feature:

    temp1.py:

    from objprint import op, install
    
    # Now you can use op() in any file
    install()
    

    temp2.py:

    op("hello")
    

    But run the temp2.py, it throws error : NameError: name 'op' is not defined What is the correct usage of install() ? Thanks !

    opened by wwdok 1
  • 在打印链表的时候结构不是很清晰

    在打印链表的时候结构不是很清晰

    打印链表会输出

    <Node 0x18136a4bd30
      .next = <Node 0x18136a4b3d0
        .next = <Node 0x18136dd5750
          .next = <Node 0x18136dd5930
            .next = <Node 0x18136dd5810
              .next = <Node 0x18136dd5870
                .next = None,
                .value = 'node_5'
              >,
              .value = 'node_4'
            >,
            .value = 'node_3'
          >,
          .value = 'node_2'
        >,
        .value = 'node_1'
      >,
      .value = 'Head'
    >
    

    可以考虑在打印属性为对象的属性的时候缩进幅度大一些

    <Node 0x18136a4bd30
        .next = <Node 0x18136a4b3d0
                .next = <Node 0x18136dd5750
                        .next = <Node 0x18136dd5930
                                    .next = <Node 0x18136dd5810
                                            .next = <Node 0x18136dd5870
                                                    .next = None,
                                                    .value = 'node_5'
                                            >,
                                            .value = 'node_4'
                                    >,
                                    .value = 'node_3'
                        >,
                        .value = 'node_2'
                >,
                .value = 'node_1'
         >,
         .value = 'Head'
    >
    

    或者结构修改一下

    <Node 0x18136a4bd30 ->  .next = <Node 0x18136a4b3d0 ->  .next = <Node 0x18136dd5750 ->  .next = <Node 0x18136dd5930 ->  .next = <Node 0x18136dd5810 ->  .next = <Node 0x18136dd5870 ->  .next = None,
                                                                                                                                                                                            .value = 'node_5'
                                                                                                                                                                                            >,         
                                                                                                                                                            .value = 'node_4'
                                                                                                                                                            >,
                                                                                                                            .value = 'node_3'
                                                                                                                            >,
                                                                                            .value = 'node_2'
                                                                                            >,
                                                            .value = 'node_1'
                                                            >,
                            .value = 'Head'
                            >
    

    简单的建议,希望能优化一下!

    opened by Sclock 1
  • pydantic.BaseModel 对象无法正确打印

    pydantic.BaseModel 对象无法正确打印

    我在使用 pydantic + objprint,打印对象使用了 #52 中的方法,但程序在 op 处阻塞住。

    from objprint import op
    from pydantic import BaseModel
    
    
    class A(BaseModel):
        a: int
    
    
    obj = A(a=1)
    op(obj, honor_existing=False)
    
    opened by Eric-fuyc 2
  • Detect repl for returning objects

    Detect repl for returning objects

    Now op() returns the object it prints to make calling chain possible. But in repl, that will print two instances. We should fix that for a better user experience.

    opened by gaogaotiantian 0
Releases(0.2.2)
Owner
Author of VizTracer, watchpoints and objprint
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

Hybrid solving process for combinatorial optimization problems Combinatorial optimization has found applications in numerous fields, from aerospace to

117 Dec 13, 2022
A minimal implementation of Gaussian process regression in PyTorch

pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b

Sangwoong Yoon 38 Nov 25, 2022
Official implementation of "Robust channel-wise illumination estimation"

This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).

Firas Laakom 4 Nov 08, 2022
Object detection (YOLO) with pytorch, OpenCV and python

Real Time Object/Face Detection Using YOLO-v3 This project implements a real time object and face detection using YOLO algorithm. You only look once,

1 Aug 04, 2022
Malware Bypass Research using Reinforcement Learning

Malware Bypass Research using Reinforcement Learning

Bobby Filar 76 Dec 26, 2022
[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

MIT Graphics Group 65 Jan 07, 2023
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Google 148 Nov 18, 2022
Code and data to accompany the camera-ready version of "Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation" in EMNLP 2021

Code and data to accompany the camera-ready version of "Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation" in EMNLP 2021

Mozhdeh Gheini 16 Jul 16, 2022
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb

Arthur Juliani 2.2k Jan 01, 2023
DSAC* for Visual Camera Re-Localization (RGB or RGB-D)

DSAC* for Visual Camera Re-Localization (RGB or RGB-D) Introduction Installation Data Structure Supported Datasets 7Scenes 12Scenes Cambridge Landmark

Visual Learning Lab 143 Dec 22, 2022
SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers

SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers This repo contains our codes for the paper "No Parameters Left Behind: Sensitivity Gu

Chen Liang 23 Nov 07, 2022
ICRA 2021 - Robust Place Recognition using an Imaging Lidar

Robust Place Recognition using an Imaging Lidar A place recognition package using high-resolution imaging lidar. For best performance, a lidar equippe

Tixiao Shan 293 Dec 27, 2022
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation AniGAN: Style-Guided Generative Adversarial Networks for U

Bing Li 81 Dec 14, 2022
Data and code from COVID-19 machine learning paper

Machine learning approaches for localized lockdown, subnotification analysis and cases forecasting in São Paulo state counties during COVID-19 pandemi

Sara Malvar 4 Dec 22, 2022
Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning. Code will be available soon.

Official-PyTorch-Implementation-of-TransMEF Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fu

117 Dec 27, 2022
Repository for the COLING 2020 paper "Explainable Automated Fact-Checking: A Survey."

Explainable Fact Checking: A Survey This repository and the accompanying webpage contain resources for the paper "Explainable Fact Checking: A Survey"

Neema Kotonya 42 Nov 17, 2022
Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

An official implementation of paper Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

11 Nov 23, 2022
VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data

VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data Introduction Requirements Installation and Setup Supported Hardware and Software R

SigmaLab 1 Jun 14, 2022
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View

Rethinking Semantic Segmentation: A Prototype View Rethinking Semantic Segmentation: A Prototype View, Tianfei Zhou, Wenguan Wang, Ender Konukoglu and

Tianfei Zhou 239 Dec 26, 2022
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

D-X-Y 137 Dec 20, 2022