bclearer-interop-services 0.6.0

"A set of interop services to integrate and transfer data between different applications, model and storage technologies for the bclearer framework."

bclearer-interop-services

A set of I/O and interop connectors for the bclearer framework. It provides adapters to read and write data between in-memory “universe” representations and a variety of storage, file formats, and application services.

Installation

pip install bclearer-interop-services

Key Features

• Dictionary Service Convert data to and from generic Python dictionaries (e.g., mapping objects to table dictionaries).
• DataFrame Service Utilities for standardizing, filtering, merging, and converting Pandas (and PySpark) DataFrames.
• Delimited Text Read/write CSV and other delimited formats.
• Excel Services Import/export Excel (.xlsx) files.
• JSON, XML, HDF5, Parquet Native serializers and readers for common data formats.
• Relational Database Services Access MS Access, SQLite, and other RDBMS via SQL interfaces.
• Document Store Services MongoDB and JSON file store support.
• Graph Services Neo4j connector and network analysis utilities.
• EA Interop Service COM-based, SQL, and XML import/export for Enterprise Architect models.
• Session & Orchestration Helpers to manage connections, sessions, and orchestrate multi-step data flows.

Basic Usage

Below is a simple example using the Dictionary and DataFrame services:

from bclearer_interop_services.b_dictionary_service.table_as_dictionary_service import TableAsDictionaryFromCsvFileReader
from bclearer_interop_services.b_dictionary_service.table_as_dictionary_service import TableAsDictionaryToDataFrameConverter

# Read data from a CSV file into a table-as-dictionary
reader = TableAsDictionaryFromCsvFileReader()
table_dict = reader.read('data/example.csv')

# Convert the table-as-dictionary to a Pandas DataFrame
converter = TableAsDictionaryToDataFrameConverter()
df = converter.convert(table_dict)

# Standardize column names and filter rows using the DataFrame service
from bclearer_interop_services.dataframe_service.dataframe_helper import DataFrameHelper

helper = DataFrameHelper()
df = helper.standardize_column_names(df)
df_filtered = df[df['status'] == 'ACTIVE']

Documentation

Full documentation and examples can be found in the GitHub repository.

License

This project is licensed under the MIT License. See the LICENSE file for details.