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 toast.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 useast.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!
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