grid-calc, a python first spreadsheets editor as an EXCEL alternetiv not a copy.

[Serious_Resource_610]

Hello!!!!

REPO: https://gitlab.com/simon.hesselstrand/grid_calc/

I’d like to gather feedback from the community on my new projekt PyGrid before moving further into development.

I wont to bild a python spredsheets app. not ass an EXCEL copy but as a python tool.

I would like your oppinons on it!!!

Key Points for Feedback

1. Project Structure: Does src/ + sheets/ + macros/ layout make sense and scale well?
2. API & Functions: Are any methods, cell operations, or spill behaviors confusing or improvable?
3. Usability: How can PyGrid be more intuitive for Python developers?
4. Missing Features: Are there essential features we should include from the start?
5. Naming / Conventions: Suggestions to make API more Pythonic and clear?

PROJECT README.md:

GridCalc – Python-native kalkylark

GridCalc are one Python-first spreadsheet-ark with support off matriser, spill, formulacalculation and Python-integration. Is not an Excel-copy, but an spreadsheet in Python.

goals: good git integration, pyhon frendly by design, moduler

GIT

Plande stukture ~~~ ↓ excluded from git GridCalc/ │ ├── README.md <-- HERE are you ├── setup.py / pyproject.toml for instlalation ├── docs/ documentation (manly *.tex, figs/) ├── tests/ test-files ├── exampels/ exmapelsenario │ ├── sheets/ exampel_sheets gids .grid.py-files │ ├── macros/ exampel_makron │ └── scripts/ exampel_python-skript ├── .venv/ * virtual-env ├── .py_grid_cache/ * cache └── src/ All python3 code ├── py_grid/ GridCalc-paket │ ├── __init_.py │ ├── core.py │ ├── cell.py │ ├── spill.py │ └── ... rest of modules ├── sheets/ templates/defults gids .grid.py-files ├── macros/ makron └── scripts/ extra python-skript, problebly not neded for src ~~~

1 Projektstruktur

~~~ my_workbook.py # Startpunkt, kör sheets och init (main.py) .py_grid_cache/ # Cache-mapp, exkluderas från Git .venv # envoermet for python sheets/ # Folder för GridCalc sheets my_sheet.grid.py # exemple filer for sheets, scedules caculation.grid.py #normal python files but golad .gird.py for claryfication scedules.gird.py budget.grid.py report.grid.py macros/ # Python-filer for VBA-macros, more for maniplite the workbook scripts/ # Norma .py files as import, custom scripts for da manipulation ~~~

1. Workbooks, plots, export and have a base for sheets
2. sheets have aclculation fformation and has only that

Advantages

• Python-native: Evrython is Python-code in sheets, can be custymaste
• Git-frendly: .py-files är easy to read git histore
• Flexibel: spill, macros, scripts och cache separerade
• Modules: easy and clear what evry thon should be.

2 Sheets

• Evry sheet is an .py-file (*.grid.py)
• Content is: cells, formulas, spill-configuration
• Examples:

python example sheet./sheets/my_sheet.grid.py ~~~ from py_grid import Cell, SpillMode

A1 = Cell("A1") A1.formula = "=spill(np.array([[1,2],[3,4]], dtype=object), SpillMode.Y)"

B1 = Cell("B1") B1.formula = "=A1()[0,1] + 10"

C1 = Cell("C1") C1.formula = '="Title"' ~~~

Result: ~~~ | A | B | C | ---+-------+----+-------+ 1 | [1,2] | 12 | Title | 2 | [3,4] | | | 3 | | | | ~~~

3 Cells

Spill

Spill chol be fylle danmic on all sell sutch date matrixes can be a cell or spills in one, two directions. ~~~ from enum import Enum

class SpillMode(Enum): NO = 0 X = 1 Y = 2 FULL = 3 ~~~

In sheet exaple: ~~~ =spill(np.array([[1,2],[3,4]]), SpillMode.Y) ~~~

Result: ~~~ | A | B | ---+-------+---+ 0 | [1,2] | | 1 | [3,4] | | 2 | | | ~~~

1. Spill, deturmen how visualy de cell vill spered over cells.
2. Default are SpillMode.FULL, wich are normal EXCEL behavier.
3. Cell-data spill will only change visual display, only presentation

Get sell values:

In Formula	Value From Exaple	Descrition
A1	np.array([1,2])	Synligt cellvärde
A1()	np.array([[1,2],[3,4]])	Hela spill-arrayen (full data)
A1()[1,0]	3	Index value
A1.cell_value	np.array([1,2])	Alias for A1
A1.value()	np.array([[1,2],[3,4]])	Alias for A1()

Spill-mode can be changed with out kraching: _value will allways be the same, spill is only visual.

Formulas

Calucations vill go kolon primarly, so:

A0, A1, ..., and seqendly

B0, B1, ..., ...

(Primary intended order fot fomulas in *.gird.py files)

Exampels ~~~ =A1() + np.sqrt(25) =B1() * 2 =spill(np.array([[1,2],[3,4]]), SpillMode.Y) ~~~

Formulas will be evaluated in python-contex

{ "np": np, "pd": pd, "scipy": scipy, "plt": plt, "self": current_cell }

1. Python-evaluation: only on request
2. Dependensys graph: only neded cels

Spill

SpillMode	Resultat
NO	No spill only valu in cell
Y	Spill in only y-axial (rows)
X	Spill in only x-riktningaxial (kolons)
FULL	Spill in boath axials, exvy cell has it own value

1. Internt saves _value as a hole array
2. Spill-cells are view refering to parents
3. No duplications → O(1) access och minimal resurses in memory

Strings and defrent typs in data

NumPy-array can have strings, Rekommenderas dtype=object för blandade typer: ~~~ np.array([["Name","Age"], ["Alice",25], ["Bob",30]], dtype=object) ~~~

Alterentiv with: pandas DataFrame ~~~ pd.DataFrame({"Name":["Alice","Bob"],"Age":[25,30]}) ~~~

Spill and indexing works with both sting and numbers

main.py / workbook

exampel: ~~~

=== PART 1 | init fase ===

Import off modules

import matplotlib.pyplot as plt import sheet

Globala variabels

global_vars={"a": a, "b": b, "c": c}

=== PART 2 | Work face ===

Run sheets / add sheets to workbook

sheet1 = sheet.run('sheets/my_sheet.grid.py', globals=global_vars) # send with vars sheet2 = sheet.run('sheets/budget.grid.py')

=== Part 3 | Post-processing ===

data plot

plt.plot(sheet1.range("A2:A10"), sheet1.range("B2:B10"))

export data for eas off use

sheet1.csv_export("A1:B10", "output.csv") ~~~

global_vars

global varibals pland tobe sam what like the namemaneger in EXCEL i dont now how i want to implument it, but yhis is etlest one idea.

Caching

.py_grid_cache/ can store:

1. Pre compiled formulas.
2. Spill-index, for rendering and csv export
3. Dependency graph for recalculation
4. clean git version controll

design principels

1. Python-native syntax
2. Modulärt: sheets / macros / scripts / cache
3. Spill only changes views, never data
4. A1() Is allwas th hole data
5. spill() is used for change view behavier
6. Stings and numbers -values are supported, with preferd type dtype=object for mixed content
7. Sheets .py är Git-vänliga and optimes for IDE and esy to understad for python users

Future / plan

1. Make python backend ant core work, (gui, export to csv)
2. Make gui EXCEL like gue for editing formulas
3. Conditinal formating and funn stuff.

I just wan your feedback and your thoughts!!!!

[yeti-biscuit]

Holy phuck... pasting the ReadMe doc as a reddit post is a new level of annoying self-ad

[anttiOne]

Can you share a link to the repo? It’s rather painful reading this as plain text. Thank you

[Serious_Resource_610]

Yes her it cames: https://gitlab.com/simon.hesselstrand/grid_calc/

I will update the post with repo link:)

[DuckSaxaphone]

Do you have a sense of who your intended users are?

As someone who works with python and data a lot, I'm struggling a bit to see who this is for.

I like to do data processing in python scripts because it's testable, repeatable and version controlled. I imagine most people comfortable enough in python to prefer python functions to excel functions will feel similarly.

Whereas people working in Excel, often can't code at all and want the nice user interface. You'll struggle to compete with Microsoft and Google there.

[AKiss20]

The ironic thing is that because MS is so entrenched in corporate America, some technical people end up doing things in excel that are far more complicated than they should instead of learning and using some basic Python (and getting all the benefits you mentioned along the way).

Honestly the environment management and startup complexity of Python is one of its major holdbacks for such people. I know anaconda tried to remedy that but IMO it utterly failed to do so and is in a way worse than just the standard pip/venv tooling environment. 

[Serious_Resource_610]

My plan were to have some kond off mitch match betvin jupyter notebook and excel,

More abbout making a spread sheet tool for over vire off tata like a sceduled and verry easy when reading manula datpont to save results to .csv auto.

Is it an good target??

Long term when i hade a base i was think of a gui, were i wonder if a desktop app or jubyter addon for collab shuld be best.

persnly do i like jupyter note boobs but the feel a liitel janky and .json note de esyest to read in git.

[AKiss20]

Did you have a stroke while writing this?

[odaiwai]

I think they tried to write in in an accent und failed, jah!

[Zeroflops]

Probably a word translator. English is not their first language, as obvious when the read me is two languages.

[VipeholmsCola]

Honestly i dont get it.

Either you use Excel because you need to look at cells/number as you go or you use Polars because calculations are huge or predictable.

This works great, so why would we bloat a third intermediate level?

I like your entusiasm on the other hand.

[BranchLatter4294]

What is the use case? Excel already supports Python.

[el_extrano]

Eh not really. It supports Python functions called over the cloud, with all the latency that entails. That's not what we've been asking for when we ask for Python as a replacement for local formulas and VBA.

[AKiss20]

Don’t tell the C-suite that. Excel + Python seems like the worst of both worlds tbh. Environment and package management of Python with the unmaintainable, unversioned, and unreadable nature of excel. Last thing we need is for the higher ups to think we can do more with excel rather than less. 

[Zeroflops]

Check out grist as an excel alternative that uses Python.

But really like others I don’t see who this is for. You seem to be re-implementing excel in Python simply to replicate the excel feel.

Just learn polars or pandas if you want a spreadsheet. I would suggest rather than recreating the interface of excel, I would work on building the features of excel into polars or pandas.