ui.input_file
ui.input_file(id,
label,*,
=False,
multiple=None,
accept=None,
width='Browse...',
button_label='No file selected',
placeholder=None,
capture )
Create a file upload control that can be used to upload one or more files.
Parameters
id : str
-
An input id.
label : TagChild
-
An input label.
multiple : bool = False
-
Whether the user should be allowed to select and upload multiple files at once.
accept : Optional[str |
list
[str]] = None-
Unique file type specifier(s) which give the browser a hint as to the type of file the server expects. Many browsers use this to prevent the user from selecting an invalid file. Examples of valid values include a case insensitive extension (e.g.
.csv
or.rds
), a valid MIME type (e.g.text/plain
orapplication/pdf
) or one ofaudio/*
,video/*
, orimage/*
meaning any audio, video, or image type, respectively. width : Optional[str] = None
-
The CSS width, e.g. â400pxâ, or â100%â
button_label : str = 'BrowseâŚ'
-
The label used on the button.
placeholder : str = 'No file selected'
-
The text to show on the input before a file has been uploaded.
capture : Optional[Literal[âenvironmentâ, âuserâ]] = None
-
On mobile devices, this can be used to open the deviceâs camera for input. If âenvironmentâ, it will open the rear-facing camera. If âuserâ, it will open the front-facing camera. By default, it will accept either still photos or video. To accept only still photos, use
accept="image/*"
; to accept only video, useaccept="video/*"
.
Returns
: Tag
-
A UI element.
Notes
A list of dictionaries (one for each file upload) with the following keys:
name
: The filename provided by the web browser. This is not the path to read to get at the actual data that was uploaded (see âdatapathâ).size
: The size of the uploaded data, in bytes.type
: The MIME type reported by the browser (for example, âtext/plainâ), or empty string if the browser didnât know.datapath
: The path to a temp file that contains the data that was uploaded. This file may be deleted if the user performs another upload operation.
See Also
Examples
#| standalone: true
#| components: [editor, viewer]
#| layout: vertical
#| viewerHeight: 400
## file: app.py
import pandas as pd
from shiny import App, Inputs, Outputs, Session, reactive, render, ui
from shiny.types import FileInfo
app_ui = ui.page_fluid(
ui.input_file("file1", "Choose CSV File", accept=[".csv"], multiple=False),
ui.input_checkbox_group(
"stats",
"Summary Stats",
choices=["Row Count", "Column Count", "Column Names"],
selected=["Row Count", "Column Count", "Column Names"],
),
ui.output_table("summary"),
)
def server(input: Inputs, output: Outputs, session: Session):
@reactive.calc
def parsed_file():
file: list[FileInfo] | None = input.file1()
if file is None:
return pd.DataFrame()
return pd.read_csv( # pyright: ignore[reportUnknownMemberType]
file[0]["datapath"]
)
@render.table
def summary():
df = parsed_file()
if df.empty:
return pd.DataFrame()
# Get the row count, column count, and column names of the DataFrame
row_count = df.shape[0]
column_count = df.shape[1]
names = df.columns.tolist()
column_names = ", ".join(str(name) for name in names)
# Create a new DataFrame to display the information
info_df = pd.DataFrame(
{
"Row Count": [row_count],
"Column Count": [column_count],
"Column Names": [column_names],
}
)
# input.stats() is a list of strings; subset the columns based on the selected
# checkboxes
return info_df.loc[:, input.stats()]
app = App(app_ui, server)