Acryl DataHub Classify

0.0.12 · deprecated · verified Wed Apr 15

This library, currently at version 0.0.12, was designed to predict info types for DataHub metadata. It is explicitly deprecated, with its last release (v0.0.12) marking it as such and signaling the end of active development and support. The project has had an infrequent release cadence.

Common errors

```
ModuleNotFoundError: No module named 'acryl_datahub_classify'
```
cause The 'acryl-datahub-classify' package is not installed or not found in the Python environment.

fix Install the package using pip: 'pip install acryl-datahub-classify'.
```
ImportError: cannot import name 'predict_infotypes' from 'acryl_datahub_classify'
```
cause The function 'predict_infotypes' is not available in the 'acryl_datahub_classify' module, possibly due to a version mismatch or incorrect import.

fix Ensure you are using the correct import statement: 'from acryl_datahub_classify import predict_infotypes'.
```
TypeError: predict_infotypes() missing 1 required positional argument: 'column_infos'
```
cause The 'predict_infotypes' function was called without the necessary 'column_infos' argument.

fix Provide the required 'column_infos' argument when calling 'predict_infotypes'.
```
ValueError: Confidence level threshold must be between 0 and 1
```
cause An invalid confidence level threshold was provided to the 'predict_infotypes' function.

fix Ensure the confidence level threshold is a float between 0 and 1.
```
AttributeError: module 'acryl_datahub_classify' has no attribute 'predict_infotypes'
```
cause The 'predict_infotypes' function is not defined in the 'acryl_datahub_classify' module, possibly due to an outdated version.

fix Update the package to the latest version using pip: 'pip install --upgrade acryl-datahub-classify'.

Warnings

breaking This library (`acryl-datahub-classify`) is explicitly deprecated as of version 0.0.12 and will no longer receive updates or support from Acryl Data. It is recommended to migrate to alternative data classification solutions.
Fix: Discontinue use of `acryl-datahub-classify`. Explore DataHub's native classification features if they meet your needs, or integrate with other third-party classification tools.
gotcha Due to its deprecated status, the pinned or range-based dependencies (e.g., `pandas<2.0.0`, `spacy>=3.0.0`) may quickly become outdated, leading to dependency conflicts with newer libraries in your environment or compatibility issues with newer Python versions.
Fix: If continued use is unavoidable, carefully manage its dependencies in an isolated virtual environment to prevent conflicts. Be prepared for potential issues with newer Python interpreters or other libraries.

Install

pip install acryl-datahub-classify Install latest deprecated version

Imports

DataHubClassifier

from datahub_classify.classifier.classifier import DataHubClassifier

Quickstart

This quickstart demonstrates how to initialize the DataHubClassifier and apply it to a pandas DataFrame to infer information types for columns. The output will show the original and classified DataFrames, including the detected info types for each cell.

import pandas as pd
from datahub_classify.classifier.classifier import DataHubClassifier

# Create a sample DataFrame
data = {
    'email_address': ['test1@example.com', 'test2@example.com'],
    'first_name': ['John', 'Jane'],
    'social_security_number': ['XXX-XX-1234', 'XXX-XX-5678'],
    'city': ['New York', 'Los Angeles']
}
df = pd.DataFrame(data)

# Initialize the classifier
classifier = DataHubClassifier()

# Classify the DataFrame
classified_df = classifier.classify_dataframe(df)

# Print results
print("Original DataFrame:")
print(df)
print("\nClassified DataFrame with info types:")
print(classified_df)

# Accessing inferred info types for a specific column
# For example, 'email_address'
print("\nInferred info types for 'email_address' column:")
if 'email_address' in classified_df.columns:
    print(classified_df['email_address'].iloc[0].metadata.dataType.type.infoType)

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