dacite | Simple creation of data classes from dictionaries | JSON Processing library

 by   konradhalas Python Version: 1.8.1 License: MIT

kandi X-RAY | dacite Summary

kandi X-RAY | dacite Summary

dacite is a Python library typically used in Utilities, JSON Processing applications. dacite has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install dacite' or download it from GitHub, PyPI.

This module simplifies creation of data classes (PEP 557) from dictionaries.
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            kandi-support Support

              dacite has a medium active ecosystem.
              It has 1433 star(s) with 88 fork(s). There are 13 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 21 open issues and 123 have been closed. On average issues are closed in 253 days. There are 11 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of dacite is 1.8.1

            kandi-Quality Quality

              dacite has 0 bugs and 0 code smells.

            kandi-Security Security

              dacite has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              dacite code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              dacite is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              dacite releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              dacite saves you 568 person hours of effort in developing the same functionality from scratch.
              It has 1355 lines of code, 209 functions and 21 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed dacite and discovered the below as its top functions. This is intended to give you an instant insight into dacite implemented functionality, and help decide if they suit your requirements.
            • Create a new instance from a dict .
            • Checks if value is an instance of type_ .
            • Transform value based on type hooks .
            • Build the value for a given union .
            • Build a value for a given collection .
            • Build a value from data .
            • Checks if the given type is a generic collection type .
            • Returns the default value for a field .
            • Extract generic arguments .
            • Checks if the given type is a literal .
            Get all kandi verified functions for this library.

            dacite Key Features

            No Key Features are available at this moment for dacite.

            dacite Examples and Code Snippets

            copy iconCopy
            python==3.8.2
            torch==1.4.0
            torchvision==0.5.0
            numpy==1.18.1
            pandas==1.0.3
            Pillow==7.2.0
            h5py==2.10.0
            matplotlib==3.1.3
            seaborn==0.10.1
            bidict==0.19.0
            dacite==1.5.0
            nltk==3.4.5
            pycocotools==2.0.0
            tqdm==4.43.0
            attrs==19.3.0
            attr==0.3.1
            rouge_score==0.0  
            :penguin: :snake: Anime Scrobbler (,Dependencies,Dacite
            Pythondot img2Lines of Code : 20dot img2License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            from dataclasses import dataclass
            from dacite import from_dict
            
            
            @dataclass
            class User:
                name: str
                age: int
                is_active: bool
            
            
            data = {
                'name': 'john',
                'age': 30,
                'is_active': True,
            }
            
            user = from_dict(data_class=User, data=data  
            dacite,License
            Rustdot img3Lines of Code : 13dot img3License : Non-SPDX (ISC License)
            copy iconCopy
            Copyright (c) 2017, Dennis Hamester 
            
            Permission to use, copy, modify, and/or distribute this software for any
            purpose with or without fee is hereby granted, provided that the above
            copyright notice and this permission notice appear in all copies.
            
            T  
            Adding dataclass fields dynamically with dacite.from_dict
            Pythondot img4Lines of Code : 134dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from __future__ import annotations
            
            from dataclasses import dataclass
            from dataclass_wizard import JSONWizard
            
            
            @dataclass(frozen=True)
            class Data(JSONWizard):
                parameters: dict[str, TimeSeries]
            
            
            @dataclass(frozen=True)
            class TimeSerie
            python : using type hints to dynamically check types
            Pythondot img5Lines of Code : 26dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from dataclasses import dataclass
            from dacite import from_dict
            @dataclass
            class C:
              a:int = 0
            
            d1 = {'a':3}
            
            c1: C = from_dict(C,d1)
            print(c1)
            print(C.__annotations__)
            
            d2 = {'a':'3'}
            
            c2: C = from_dict(C,d2)
            
            C(a=
            How to serialise and deserialise complex POCO data structures in Python to/from JSON
            Pythondot img6Lines of Code : 51dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
             from dataclasses import dataclass, asdict
             from typing import List
             from dacite import from_dict
            
            
             @dataclass
             class Address(object):
                 city: str
                 postcode: str
            
            
             @dataclass
             class Person():
                 name: str
                 addresses: List[Ad
            JSON object mapper for Python
            Pythondot img7Lines of Code : 58dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
              from dataclasses import dataclass
              from datetime import datetime
              from uuid import UUID
              from typing import List
              from dacite import from_dict
            
            
              @dataclass
              class BusinessUnit:
                  code: int
                  type: str
            
            
              @dataclass
              clas
            find words that can be made from a string in python
            Pythondot img8Lines of Code : 41dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def find_anagrams(seek_word):
                sorted_seek_word = sorted(seek_word.lower())
                for word in open("/usr/share/dict/words"):
                    word = word.strip()  # remove trailing newline
                    sorted_word = sorted(word.lower())
                    if sort
            Python dataclass from a nested dict
            Pythondot img9Lines of Code : 21dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from dataclasses import dataclass
            from dacite import from_dict
            
            @dataclass
            class User:
                name: str
                age: int
                is_active: bool
            
            data = {
                'name': 'john',
                'age': 30,
                'is_active': True,
            }
            
            user = from_dict(data_class=User, 
            What's the pythonic way to instantiate multiple objects from **kwargs?
            Pythondot img10Lines of Code : 6dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from dacite import from_dict
            
            def create_objects(**kwargs):
                obj1 = from_dict(data_class=Object1, data=kwargs)
                obj2 = from_dict(data_class=Object2, data=kwargs)
            

            Community Discussions

            QUESTION

            Adding dataclass fields dynamically with dacite.from_dict
            Asked 2022-Mar-07 at 07:22

            I am using dacite to transform a Python dictionary into a dataclass. Is there a way to dynamically add fields to a dataclass? Like in the example below, where the dataclass "Parameters" has defined only one timeseries "timeseriesA", but there might be additional ones (provided through the dictionary) that cannot be declared.

            ...

            ANSWER

            Answered 2022-Mar-04 at 05:41

            In general, dynamically adding fields to a dataclass, after the class is defined, is not good practice. However, this does present a good use case for using a dict within a dataclass, due to the dynamic nature of fields in the source dict object.

            Here is a straightforward example of using a dict field to handle a dynamic mapping of keys in the source object, using the dataclass-wizard which is also a similar JSON serialization library. The approach outlined below handles extraneous data in the dict object like timeseriesB for instance.

            Source https://stackoverflow.com/questions/71334683

            QUESTION

            How to store result of pip command into Pandas Datafarme
            Asked 2020-Nov-17 at 11:04

            For getting the list of installed libraries, I run the following command in Jupyter Notebook:

            ...

            ANSWER

            Answered 2020-Nov-17 at 11:03

            We can use os module to create the pip list, then we use pandas.read_csv with \s+ as seperator to read the pip list into a dataframe:

            Source https://stackoverflow.com/questions/64873796

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install dacite

            To install dacite, simply use pip:.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            Install
          • PyPI

            pip install dacite

          • CLONE
          • HTTPS

            https://github.com/konradhalas/dacite.git

          • CLI

            gh repo clone konradhalas/dacite

          • sshUrl

            git@github.com:konradhalas/dacite.git

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