========= jsonTOxls

Create Excel files using json requests. Send json to create xls,xlsx files using XlsxWriter (https://github.com/jmcnamara/XlsxWriter). You can optionally run a tornado server to accept the requests.

It works as basic functionality (add values, sheets, formats, conditional formatting, merging)

#Requires

python3 (may work with 2 as well)
and the libraries mentioned above

#To run

server (optional) : python3 jsonTOxls_server.py
python3 jsonTOxls.py (will run example 4)

if you want to run different examples run :
    python3 jsonTOxls.py 1
    python3 jsonTOxls.py 2
    python3 jsonTOxls.py 3
    python3 jsonTOxls.py 4

#Documentation

For input documentation used to create files you can check xlsxwritter documentation at:https://xlsxwriter.readthedocs.org/en/latest/

Example 1:

Just a "Hello World example".

 -The json contains a list of sheets.
 -Each sheet is a dictionary sheet name to data

     sheet_data = {
        'A1': 'Item',
        'B1': 'Cost',
        #
        'A2': 'Rent',
        'A3': 'Gas',
        'A4': 'Food',
        'A5': 'Gym',
        'A6': 'Total',
        #
        'B2': '10.10',
        'B3': '100.1',
        'B4': '300.5',
        'B5': '50.0',
        'B6': '=SUM(B1:B4)'
    }

    sheet = {
        'sheets': [
            {"Test Sheet": sheet_data}
        ]
    }

Example 1 Output:

Example 2:

Formats

-Json structure: {'sheets' : list of sheets, 'formats': dict of formats}
-You can use either A1 or 0,0 it gives the same result
-You can also use either '0,0':'Foo' or '0,0':{'value':'Foo','format':'the_format'}
-For more about formats check the xlsxWritter doc

   sheet_data = {
        'A1': {'value': 'Item', 'format': 'bold'},
        'B1': {'value': 'Cost', 'format': 'bold'},
        #
        '1,0': 'Rent',
        '2,0': 'Gas',
        '3,0': 'Food',
        '4,0': 'Gym',
        '5,0': 'Total',
        #
        '1,1': {'value': '50.50', 'format': 'number_bold_red'},
        '2,1': {'value': '15.88', 'format': 'number_bold_red'},
        '3,1': {'value': '33.90', 'format': 'number_bold_red'},
        '4,1': {'value': '80.55', 'format': 'number_bold_red'},
        '5,1': {'value': '=SUM(B2:B5)', 'format': 'number_bold_red'}
    }

    sheet = {
        'sheets': [
            {"Test Sheet": sheet_data},
        ],
        "formats": {
            'bold': {'bold': True},
            'bold_red': {'bold': True, 'font_color': 'red'},
            #
            'number': {'num_format': '$#,##.##'},
            'number_bold_red': {'bold': True, 'font_color': 'red', 'num_format': '$#,##.##'},
            'number_bold_blue': {'bold': True, 'font_color': 'red', 'bg_color': '#99CCFF', 'num_format': '$#,##.##'},
        }
    }

Example 2 Output:

Example 3:

 -Resize is inside the sheet data because different sheets may have different column sizes, same for conditional formatting.

     sheet_data = {
        'A1': {'value': 'Item', 'format': 'bold'},
        'B1': {'value': 'Cost', 'format': 'bold'},
        'C1': {'value': 'Date', 'format': 'bold'},
        #
        '1,0': 'Rent',
        '2,0': 'Gas',
        '3,0': 'Food',
        '4,0': 'Gym',
        '5,0': 'Total',
        #
        '1,1': {'value': '500.50', 'format': 'number_bold_red'},
        '2,1': {'value': '150.88', 'format': 'number_bold_red'},
        '3,1': {'value': '330.90', 'format': 'number_bold_red'},
        '4,1': {'value': '80.55', 'format': 'number_bold_red'},
        '5,1': {'value': '=SUM(B2:B5)', 'format': 'sum_format'},
        #
        '1,2': {'date': '2013-01-01', 'format': 'date_format'},
        '2,2': {'date': '2013-02-01', 'format': 'date_format'},
        '3,2': {'date': '2013-03-01', 'format': 'date_format2'},
        '4,2': {'date': '2013-04-01', 'format': 'date_format2'},
        #


        "conditional_formats": {
            'B2:B5': {
                'type': 'cell', 'criteria': '>=', 'value': 300, 'format': 'number_bold_blue'
            }
        },
        #
        "column_size": {
            'A:B': 15,
            'C:C': 25
        }
    }

    sheet = {
        'sheets': [
            {"Test Sheet": sheet_data},
        ],
        "formats": {
            'bold': {'bold': True},
            'bold_red': {'bold': True, 'font_color': 'red'},
            #
            'number': {'num_format': '$#,##.##'},
            'number_bold_red': {'bold': True, 'font_color': 'red', 'num_format': '$#,##.##'},
            'number_bold_blue': {'bold': True, 'font_color': 'red', 'bg_color': '#99CCFF', 'num_format': '$#,##.##'},
            #
            'sum_format': {'bold': True, 'bg_color': '#E9AA94'},
            'date_format': {'num_format': 'yyyy d mmmm'},
            'date_format2': {'num_format': 'yy dd mmm'}
        }
    }

Example 3 Output:

Example 4:

This example is very big but the generated json and xls file is in the project examples folder.

Merge

To merge use this:

 A1-D1:'merged region'

Progress

You can check PROGRESS.txt for implemented functionality, coming functionality and known issues.

Motivation: Why do we need this anyway?

Unified approach, It's not specific to your programming language (if you run tornado).
Abstraction: Chunking Up from excel specific code as shown in 3 to json dicts lists
Personally i dislike report code, hence this pseudo code example*:

     rowIndex, colIndex = 1,0
     row = sheet.createRow(rowIndex)
     cell = row.createCell(colIndex)
     cell.setValue(values[(rowIndex,colIndex)])
     cell.setStyle(styles[(rowIndex,colIndex)])

Changes to:

     row,col = 1,0
     sheet[str(row) + "," + str(col)] = {
               "value":values[(row,col)],
               "format":formats[(row,col)]
     }

And with some imagination:

     row,col = 1,0
     key = lambda row,col: str(row) + "," + str(col)
     val = lambda row,col:(
              {
                 "value":values[(row,col)],
                  "format":formats[(row,col)]
              }
     )
     sheet[key(row,col)] = val(row,col)

*Note i didn't run this code, I just wrote it in the readme file to demonstrate an example.

And you end up applying divide and conquer technique for the problem which is now split in 4 steps:
- Fetch data
- Process data (decide which cells hold which values - create values and formats dictionaries) -Create json as shown above -Send json to create xls without writing code

I will try to demonstrate this in the up-coming Exmaple 5 because theory is easier than practice (sometimes).

Feedback

If you disagree with anything or want to request a feature feel free: ANY feedback is much appreciated as well as criticism.

solancer / jsonTOxls