basic-framework 3.4.1

Python framework with containers, conditions, and file operations

Basic Framework

A Python framework providing essential utilities for data processing, file handling, configuration management, and structured logging.

Overview

The Basic Framework was originally part of the Krefeld Prototype project and has been extracted into a standalone, installable Python package. It provides a comprehensive set of tools for:

• Abstract Containers & Iterators: Generic data container interfaces with filtering capabilities
• Condition Handling: Flexible condition system for data filtering (equals, not, and operations)
• File System Extensions: Enhanced file and directory operations
• Configuration Management: INI file handling with section inheritance
• Process Framework: Structured logging and process lifecycle management
• Text File Processing: Text files as table-like data structures
• Environment Variables: Type-safe access to environment variables

Installation

From Source (Development)

cd basic_framework
pip install -e .

From GitHub

pip install git+https://github.com/hennig-ai/basic-framework.git

Dependencies

• Python >= 3.10 (tested with 3.10, 3.11, 3.12, 3.13)
• configparser >= 5.0.0

Quick Start

from basic_framework import (
    IniConfigFile,
    proc_frame_start,
    proc_frame_end,
    log_msg,
    log_and_raise,
    file_exists
)

# Process framework with logging
proc_frame_start("MyProcess", "1.0.0", "config.ini")

try:
    log_msg("Processing started")

    if not file_exists("data.csv"):
        log_and_raise("Required file data.csv not found")

    log_msg("Processing completed successfully")
finally:
    proc_frame_end()

Core Components

Abstract Containers

from basic_framework import AbstractContainer, create_new_iterator

# Create custom data containers with filtering capabilities
# Implement AbstractContainer interface for your data sources

Conditions System

from basic_framework import ConditionEquals, ConditionAnd, ConditionNot

# Create flexible filtering conditions
condition = ConditionAnd([
    ConditionEquals("status", "active"),
    ConditionNot(ConditionEquals("type", "archived"))
])

File System Extensions

from basic_framework import file_exists, file_must_exist, replace_path

# Enhanced file operations
if file_exists("myfile.txt"):
    processed_path = replace_path("~/data/file.csv")
    file_must_exist(processed_path)  # Raises error if missing

Process Framework & Logging

from basic_framework import proc_frame_start, proc_frame_end, log_msg, log_and_raise

# Structured process lifecycle
proc_frame_start("DataProcessing", "1.0.0", "config.ini")
try:
    log_msg("Processing started")
    # Your processing logic
    log_msg("Processing completed successfully")
except Exception as e:
    log_and_raise(f"Processing failed: {e}")
finally:
    proc_frame_end()

Configuration with INI Files

from basic_framework import IniConfigFile, get_global_par

# After proc_frame_start, access config via global functions
value = get_global_par("parameter_name", "section_name")

# Or use IniConfigFile directly
config = IniConfigFile()
config.init("settings.ini")
value = config.get_value("Section", "Key", "DefaultValue")
int_value = config.get_int_value("Section", "Count", 10)
bool_value = config.get_bool_value("Section", "Enabled", False)

INI files support section inheritance via parent_section:

[default]
timeout = 30
retry_count = 3

[production]
parent_section = default
timeout = 60

Environment Variables

from basic_framework import (
    env_par_exists,
    get_env_value,
    get_env_int_value,
    get_env_float_value,
    get_env_bool_value
)

# Type-safe environment variable access
if env_par_exists("DATABASE_URL"):
    db_url = get_env_value("DATABASE_URL")

port = get_env_int_value("DB_PORT")
timeout = get_env_float_value("TIMEOUT_SECONDS")
debug = get_env_bool_value("DEBUG_MODE")  # Supports: true/false, yes/no, 1/0

Text File as Table

from basic_framework import TextFileAsTable, create_new_iterator

# Process text files as structured data
table = TextFileAsTable()
table.init("data.csv", field_separator=",")

# Iterate over rows
iterator = table.create_iterator()
while not iterator.is_empty():
    name = iterator.value("Name")
    value = iterator.value("Value")
    iterator.pp()  # Move to next row

Utilities

Path and File Operations

from basic_framework import (
    get_name_from_full_reference,
    get_path_from_full_reference,
    remove_file_postfix,
    is_hyperlink
)

# File path utilities
filename = get_name_from_full_reference("C:/data/file.csv")  # "file.csv"
name_only = remove_file_postfix(filename)  # "file"
path = get_path_from_full_reference("C:/data/file.csv")  # "C:/data/"

# URL detection
if is_hyperlink("https://example.com/file.csv"):
    # Handle URL
    pass

String Operations

from basic_framework import escape_access_sql_string, get_format_now_stamp

# SQL string escaping for Access queries
safe_string = escape_access_sql_string("user's [data]")

# Timestamp formatting
timestamp = get_format_now_stamp(with_seconds=True)  # "20231201_1430_25"

Architecture

The framework follows these design principles:

• Modular Design: Each module has clear responsibilities and minimal dependencies
• Logging Integration: Comprehensive logging throughout all operations
• Fail-Fast: Errors are raised immediately with log_and_raise() rather than silently ignored
• Type Safety: Full type hints for better IDE support and code clarity

License

MIT License - Copyright (c) 2024-2026 Lars Hennig

See LICENSE for details.

Support

For issues and feature requests, please use the issue tracker.