Metadata-Version: 2.1
Name: db-ops
Version: 0.0.2
Summary: Python class helper for working with sqlite3 databases and Pandas dataframes.
Home-page: https://github.com/stuianna/DBOps
Author: Stuart Ianna
Author-email: stuian@protonmail.com
License: UNKNOWN
Description: [![Build Status](https://travis-ci.org/stuianna/DBOps.svg?branch=master)](https://travis-ci.org/stuianna/DBOps)
        ![Codecov](https://img.shields.io/codecov/c/gh/stuianna/DBOps)
        ![GitHub](https://img.shields.io/github/license/stuianna/DBOps)
        
        Python class helper for sqlite3 databases.
        
        Example: Create, read and remove a table working with just dataframes.
        
        ```python
        from dbops.sqhelper import SQHelper
        import pandas as pd
        
        table_name = 'temperature'
        df = pd.DataFrame({"timestamp": [1587222785, 1587222786], 'celsius': [23.3, 23.9]})
        
        db = 'myDatabase.sql3'
        database = SQHelper(db)
        
        # The dataframe column names are used for the table's column names. 
        # All dataframe entries are automatically inserted.
        database.create_table(table_name,df)
        
        # Add some more entries to the database, in this case duplicates of the above entry are made.
        database.insert(table_name,df)
        
        # Read the content back into a dataframe
        new_df = database.table_to_df(table_name)
        
        # Remove the table from the database
        database.remove_table(table_name);
        
        ```
        
        Example: Create a table, add an entry and return it as a Pandas dataframe.
        
        ```python
        from dbops.sqhelper import SQHelper
        
        db = 'myDatabase.sql3'
        table_name = 'temperature'
        columns = {'timestamp': 'NUMERIC', 'celsius': 'REAL'}
        
        # Create a class instance for a single database
        database = SQHelper(db)
        
        # Add a table to the database
        database.create_table(table_name,columns)
        
        # Get all the tables in the database
        all_tables = database.get_table_names()
        
        # Add an entry to the database
        new_entry = {'timestamp': 1587222785, 'celsius': 34.2}
        database.insert(table_name, new_entry)
        
        # Return the table as a Pandas Dataframe
        df = database.table_to_df(table_name)
        
        # Return all rows based on a column query, returns matching rows as dataframe
        database.get_row(table_name, 'celsius', 34.2);
        ```
        
        
        Use help(SQHelper) for more detailed information.
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
