Skip to main content

easily convert json like strings to dictionaries

Project description

String2Dict

Overview

String2Dict is a Python class designed to transform complex strings into Python dictionaries. It is particularly useful when working with text-based outputs from language models (LLMs) that need to be parsed into valid JSON objects or Python dictionaries. This class provides functionality for cleaning, sanitizing, and parsing such text data efficiently.

Main Use Case

The primary use case for String2Dict is to process outputs from Large Language Models (LLMs) like GPT-3/4 and convert them into valid JSON objects. Since LLMs often return data with extra characters, formatting inconsistencies, or embedded code markers, it can be challenging to directly parse the output into JSON or dictionaries. String2Dict aims to simplify this process by handling common formatting issues and providing a robust parsing mechanism.

Key Features

  • Strips Whitespace: Removes unnecessary leading and trailing whitespace from strings.
  • Removes Embedded Markers: Cleans code markers like json or ``` to ensure the string is ready for parsing.
  • Ensures Valid JSON Braces: Adjusts strings to ensure they start and end with curly braces ({}).
  • Supports JSON and Python Parsing: Tries to parse strings using json.loads first, and falls back to ast.literal_eval if needed.
  • Handles Multiple Dictionaries: Extracts and parses multiple dictionary-like strings from a single input.

Installation

To use String2Dict, copy the class definition into your Python script. Ensure you have the following Python standard libraries:

import re
import ast
import json
import logging

Usage

Example 1: Parsing a Single String

# Create a logger for debugging
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.DEBUG)

# Initialize the String2Dict class
s2d = String2Dict(debug=True)

# Input string from an LLM
llm_output = "```json\n{\"name\": \"ChatGPT\", \"version\": \"4.0\"}\n```"

# Convert the LLM output into a dictionary
parsed_dict = s2d.run(llm_output)
print(parsed_dict)

Output:

{'name': 'ChatGPT', 'version': '4.0'}

Sure! Here’s the fixed version with proper formatting:

Example 2: Parsing Multiple Dictionaries from a String

# Input string containing multiple dictionaries
llm_output = """
```json
{"name": "ChatGPT", "version": "4.0"}
{"name": "GPT-3", "version": "3.0"}
```"""

# Extract and convert each dictionary into a list of dictionaries
parsed_dicts = s2d.string_to_dict_list(llm_output)
print(parsed_dicts)

Output:

[
    {'name': 'ChatGPT', 'version': '4.0'},
    {'name': 'GPT-3', 'version': '3.0'}
]

This version has the input string correctly formatted, making it clear how to pass the LLM's output into the string_to_dict_list method for parsing multiple dictionaries.

Methods

1. strip_surrounding_whitespace(string: str) -> str

  • Strips leading and trailing whitespace from the input string.
  • Args: string (str) - The input string.
  • Returns: Stripped string.

2. remove_embedded_markers(string: str) -> str

  • Removes embedded markers like json and other code block markers.
  • Args: string (str) - The input string.
  • Returns: Cleaned string.

3. ensure_string_starts_and_ends_with_braces(string: str) -> str

  • Ensures the string starts and ends with curly braces ({}).
  • Args: string (str) - The input string.
  • Returns: Adjusted string.

4. parse_as_json(string: str) -> dict

  • Attempts to parse the string as JSON using json.loads.
  • Args: string (str) - The input JSON string.
  • Returns: Parsed dictionary.

5. parse_with_literal_eval(string: str) -> dict

  • Attempts to parse the string using Python's ast.literal_eval.
  • Args: string (str) - The input string.
  • Returns: Parsed dictionary.

6. run(string: str) -> dict

  • Processes a string through all cleaning and parsing steps, returning a parsed dictionary.
  • Args: string (str) - The input string.
  • Returns: Parsed dictionary or None if parsing fails.

7. string_to_dict_list(string: str) -> list

  • Extracts multiple dictionaries from a string and converts each to a Python dictionary.
  • Args: string (str) - The input string containing one or more dictionaries.
  • Returns: A list of parsed dictionaries, or None if parsing fails.

Logging

The String2Dict class supports logging for easier debugging. Set the debug parameter to True when initializing the class to enable detailed logging.

Error Handling

The class handles parsing errors gracefully:

  • If json.loads fails, it attempts to use ast.literal_eval.
  • If both methods fail, it logs an error and returns None.

License

This project is licensed under the MIT License. Feel free to use, modify, and distribute it as per the license terms.

Contributions

Contributions are welcome! If you find a bug or have a suggestion for improvement, feel free to submit an issue or pull request.


This String2Dict class makes it easier to parse and clean outputs from LLMs into usable JSON objects, simplifying the process of integrating AI-generated data into Python applications. Happy coding!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

string2dict-0.0.5.tar.gz (5.6 kB view details)

Uploaded Source

Built Distribution

string2dict-0.0.5-py3-none-any.whl (5.8 kB view details)

Uploaded Python 3

File details

Details for the file string2dict-0.0.5.tar.gz.

File metadata

  • Download URL: string2dict-0.0.5.tar.gz
  • Upload date:
  • Size: 5.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.20

File hashes

Hashes for string2dict-0.0.5.tar.gz
Algorithm Hash digest
SHA256 a89023cc08805d98aefe5f12e6c6d431873dd67b788f73fea3bee2910edf2a91
MD5 6c24d2a30fe9b137c8f1fc042065b86f
BLAKE2b-256 b7d23a21d3b457b7662ee0a94798666a23c0e173546c2ea20ea3ed5691391980

See more details on using hashes here.

File details

Details for the file string2dict-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: string2dict-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 5.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.20

File hashes

Hashes for string2dict-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 259551a58cb25d3b8f44cd38462734801bd8a430f1e556eec9521be70ba0e8ea
MD5 23725845e421155d8e7a97c6bd8355e4
BLAKE2b-256 055e31813c144d99bda698e2cd16b7a494e2fc215a844cf02f6205ac731d5c0f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page