Emit csv-viewer's CsvGrid interactive tables from pandas DataFrames (Jupyter / Quarto / static HTML).
Project description
csv_grid
Python emitter for CsvGrid, the embeddable interactive table of the
csv-viewer project: render a pandas
DataFrame as a sortable, filterable, type-aware grid in Jupyter, Quarto
(.qmd), or any static HTML you generate.
The grid re-infers column types from the data exactly as the viewer app does (numbers right with greater_tables-style formatting, dates ISO and centered, fzf search, equal-risk column widths). NaN / None become blank cells.
Install
uv add csv-grid # or: pip install csv-grid
or local path install from a clone of this repo:
uv add --editable path/to/csv-viewer/python
The grid's built JS/CSS assets ship inside the package (refreshed by the
repo's npm run build).
Use
from csv_grid import show, to_html
show(df) # Jupyter / qmd cell: display the grid
show(df, align="llrcr", fmt=[None, None, ",d", "year", ",.2f"])
html = to_html(df, name="results.df", assets="inline") # fragment string
show(df, **options)displays via IPython. Each grid carries the JS + CSS via an idempotent<head>guard (assets="inline", the default), so fragments are self-contained and re-running/clearing a notebook cell can't strip a shared stylesheet. Useassets="https://…/base"to link the assets from a URL instead, orassets=Falseif they are already on the page.to_html(df, **options)returns a self-contained HTML fragment; fragments compose freely (no need to mark a "first" one).payload(df)returns the{records, columns}dict the grid consumes, if you want to ship data yourself.- Options mirror the JS API in snake_case:
global_search,column_filters,sortable,status_bar,expand_buttons,align('llrcr…'),formats/fmt(per-column: a number spec[,][.N](f|d|%|e|s)/'year'/'eng', or on a date column a strftime pattern%Y %y %m %d %H %M %S %f—%fis 3-digit milliseconds here, not Python's 6-digit microseconds — and%%is a literal%; None = auto). Date columns auto-show their finest present resolution: date-only when no times are present,HH:MMwhen minutes are,:SS[.fff]down to milliseconds otherwise, with a uniform fractional width per column. An explicit date pattern overrides the auto rule.width_mode('equal-risk'default, or'coverage'to maximize the count of fully-shown cells),display_mode('auto'formatted /'raw'verbatim),rows(cap the viewport to ~N rows, vertical scroll for the rest) /max_height(raw CSS, e.g.'400px'),render_cap,eager_cells,worker(default False — data is inlined), plusname(status line) andindex(include the DataFrame index as leading columns). Dark mode follows the host page (prefers-color-scheme; JupyterLab dark themes included) unlesstheme="light"/"dark"forces it. - Clickable rows/cells (
selectable=True): a body click fires a bubblingcsvgrid:cellclickDOM event whosedetailcarries the clicked cell and the whole row keyed by column name (raw + formatted) with the original row index — wire it to HTMX/JS for drill-down.select_mode('row'/'cell'/'none') controls the highlight;hidden_columns=[…]ships a key column in the payload without displaying it. No Python callback —to_htmlstays a pure string emitter.
to_html(df, name="transactions", selectable=True,
select_mode="row", hidden_columns=["trans_id"])
Dates are emitted ISO (yyyy-mm-dd, with hh:mm only when a column has
non-midnight times); integral float columns are emitted as integers so
the grid's integer/year rules apply.
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