Python’s native interface is a command line interpreter much like that of the non-graphical command-line-driven DOS operating system. This is where SQXL comes in.

SQXL allows Python solutions to offer the convenience, efficiency, and intuitiveness of the windows environment. With little more than drag and drop, virtually any Python program can be given the friendly interface users have come to expect.

Beyond that, SQXL provides whole classes of run-time features and functionality not available through Python alone.

Multiple Pythons

1. The results from code executed in the four independent PAD editors are directed to separate document windows. This means command line prompts are unnecessary and work product is kept separate, not intermixed with instructions.

2. Because the output windows are also document editors, comments and images that might be necessary to clarify or augment the result can easily be added. Finished documents can be printed in-part or in-full and saved as RTF files, which can be further edited with MS Word.

3. Besides being able to cut, copy, and paste into a PAD, any selection of code can be run, edited, and then rerun again without the need to retype the entire expression.

4. The more common Python modules are automatically imported with their alias on startup, saving having to constantly re-enter them. There is also a Python priming file for the same purpose that can be user configured.

5. There is syntax coloring, auto indexing, de-indexing, and auto-complete for both variables and methods. There are insertion menus for variables and file names to assist in recollection, as well as alleviating the need for typing them.

6. PAD editor contents, selected or full, can be printed or saved as either Python text, RTF, or HTML files. Contents can be loaded from Python text or extracted from RTF files.

7. A 30,000 character rolling history of all executed code is maintained for each Python engine allowing its examination, recovery, and execution should it be required.

8. The actual Python engines run in processes separate from the editors, meaning if some experimental code caused it to hang, say in an endless loop, all is not lost. Python can be restarted from within SQXL, preventing the loss of work and permitting a modified version of the culprit code to be tried again.

9. There are built-in Python methods that permit real-time access to operating system resources while simultaneously pausing (or not) code execution until requests have been completed.

10. Transparent detection and wrapping allows raw SQL code to be intermixed with Python code. SQXL packs the SQL within Python statements to permit it to be processed by the sqlite3 module.

11. The act of copying code from PDF files or websites and pasting into PAD editors automatically filters out the more common command line prompts and comments out any previously displayed results.

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  Executing Selected Python code
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  Auto-complete for variable and method names
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  Rolling history of Python execution
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  Mixed SQL and Python Code

SQXL Sire - taking Python beyond its borders

1. Load and display multiple spreadsheets of up 1,000,000 rows by 4,000 columns each from DataFrames, arrays, matrices, and CSV files. (memory permitting)

2. Cut, copy, paste, delete, insert, and rearrange columns and rows of DataFrames via spreadsheets.

3. Examine spreadsheet content with vertical and horizontal mouse scrolls, page up and down buttons, 2D mouse drag, or GOTO menu selections.

4. Create or edit DataFrame entries via spreadsheet cells (WYSIWYG), or load and manage spreadsheet content under Python control.

5. With a click of a button on any combination of columns and rows, including non-contiguous, or by dragging the mouse, make selections for creating new DataFrames, Series, arrays, matrices, or list, for printing tables in documents, or for feeding Python operations.

6. Perform DataFrame operations such as sorting, dropping duplicates, applying formulas, and etc. via spreadsheets selections.

7. Series results are recorded in the SERIES spreadsheet. Automatically performing a push down, or rather push to the right operation, the spreadsheet maintains a history of Series work products for later examination and recovery.

8. The Report document accepts results from Python operations, including images, plots, and charts. The code producing those results can be hidden in the document as an Execute button to be executed later from the Guide; perhaps when dependent data is available. It can also be hidden as Operator button to be recalled to a Panel for subsequent user configuration.

9. An entire Folder of Python Operators can be embedded (hidden) in a document along with spreadsheets, Venues, and Panels for later recall via associated buttons.

10. Passages composed of groups of buttons and text can be created within documents to create instructional treatises, adaptive questionnaires, and more, all interactive with Python routines and analysis.

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  Processing selected dataset columns and rows
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  Interactive Document Operation
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  Manipulating columns
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  Security