Observed since 21 Oct, 10:24 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Can be used to pre process data before ai processing
This tool is intended for preparing data for further processing. It contains different text processing steps that can be enabled or disabled dynamically.
pip install ai-data-preprocessing-queue
from ai_data_preprocessing_queue import Pipeline
state = {}
pre_processor_dict = {
'to_lower' : None,
'spellcheck' : 'test\r\ntesting'
}
pipeline = Pipeline(pre_processor_dict)
value = pipeline.consume('Input text', state)
state is optional here and can be used to cache preprocessing data between pipeline calls.
The preprocessors that the pipeline should use have to be transmitted as keys within a dictionary. Some preprocessors also require additional data to function. The data must be converted into string form and assigned to its preprocessor within the dictionary.
This dictionary then needs to be transmitted to the pipeline through its constructor.
Note: Pipeline has to be instantiated only once and can be reused.
Name: to_lower
Required additional data: -
Converts the text to lower case characters.
Name: remove_numbers
Required additional data: -
Removes all numbers from the text.
Name: remove_punctuation
Required additional data: -
Removes all special characters from the text.
Name: text_only
Required additional data: -
Removes all special characters and numbers from the text.
Name: spellcheck
Required additional data: A string containing words, separated by newline, i.e. "word1\r\nword2"
Takes a list of words representing the correct spelling. Words within the given text that are close to a word from this list will be replaced with the listed word.
Name: regex_replacement
Required additional data: CSV data in string form with the following line format: <pattern>,<replacement>,<order>
This preprocessor will search for occurrences of specific entities in your text and replace them by a specified pattern.
Name: token_replacement
Required additional data: CSV data in string form with the following line format: <text>,<replacement>,<order>
With this preprocessor you can replace specific words and abbreviations within the text with specified tokens. It is also possible to replace abbreviations ending with a dot. Other special characters are not supported, though.
Name: remove_signature
Removes greeting expressions and everything following them, as well as thank you expressions. Should be used before the other processing steps.
Just install VS Code with the Dev Containers extension. All required extensions and configurations are prepared automatically.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 1.7.2 | 17 Mar 2026 | 11 |
This describes our collected data; it is not a security assessment.
Shared repository data · GitHub
Observed since 21 Oct, 10:24 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:e0879ddb7a311eb4d0dd0b58ed59335779f5f1fed887d7c34dcd769d8ac8bf3b