def expander(self, label: str, expanded: bool = False):
"""Insert a multi-element container that can be expanded/collapsed.
Inserts a container into your app that can be used to hold multiple elements
and can be expanded or collapsed by the user. When collapsed, all that is
visible is the provided label.
To add elements to the returned container, you can use "with" notation
(preferred) or just call methods directly on the returned object. See
examples below.
.. warning::
Currently, you may not put expanders inside another expander.
Parameters
----------
label : str
A string to use as the header for the expander.
expanded : bool
If True, initializes the expander in "expanded" state. Defaults to
False (collapsed).
Examples
--------
>>> st.line_chart({"data": [1, 5, 2, 6, 2, 1]})
>>>
>>> with st.expander("See explanation"):
... st.write(\"\"\"
... The chart above shows some numbers I picked for you.
... I rolled actual dice for these, so they're *guaranteed* to
... be random.
... \"\"\")
... st.image("https://static.streamlit.io/examples/dice.jpg")
.. output ::
https://static.streamlit.io/0.66.0-2BLtg/index.html?id=7v2tgefVbW278gemvYrRny
height: 750px
"""
if label is None:
raise StreamlitAPIException("A label is required for an expander")
expandable_proto = BlockProto.Expandable()
expandable_proto.expanded = expanded
expandable_proto.label = label
block_proto = BlockProto()
block_proto.allow_empty = True
block_proto.expandable.CopyFrom(expandable_proto)
return self.dg._block(block_proto=block_proto)
def columns(self, spec: SpecType):
"""Insert containers laid out as side-by-side columns.
Inserts a number of multi-element containers laid out side-by-side and
returns a list of container objects.
To add elements to the returned containers, you can use "with" notation
(preferred) or just call methods directly on the returned object. See
examples below.
.. warning::
Currently, you may not put columns inside another column.
Parameters
----------
spec : int or list of numbers
If an int
Specifies the number of columns to insert, and all columns
have equal width.
If a list of numbers
Creates a column for each number, and each
column's width is proportional to the number provided. Numbers can
be ints or floats, but they must be positive.
For example, `st.columns([3, 1, 2])` creates 3 columns where
the first column is 3 times the width of the second, and the last
column is 2 times that width.
Returns
-------
list of containers
A list of container objects.
Examples
--------
You can use `with` notation to insert any element into a column:
>>> col1, col2, col3 = st.columns(3)
>>>
>>> with col1:
... st.header("A cat")
... st.image("https://static.streamlit.io/examples/cat.jpg")
...
>>> with col2:
... st.header("A dog")
... st.image("https://static.streamlit.io/examples/dog.jpg")
...
>>> with col3:
... st.header("An owl")
... st.image("https://static.streamlit.io/examples/owl.jpg")
.. output ::
https://static.streamlit.io/0.66.0-Wnid/index.html?id=VW45Va5XmSKed2ayzf7vYa
height: 550px
Or you can just call methods directly in the returned objects:
>>> col1, col2 = st.columns([3, 1])
>>> data = np.random.randn(10, 1)
>>>
>>> col1.subheader("A wide column with a chart")
>>> col1.line_chart(data)
>>>
>>> col2.subheader("A narrow column with the data")
>>> col2.write(data)
.. output ::
https://static.streamlit.io/0.66.0-Wnid/index.html?id=XSQ6VkonfGcT2AyNYMZN83
height: 400px
"""
weights = spec
weights_exception = StreamlitAPIException(
"The input argument to st.columns must be either a " +
"positive integer or a list of positive numeric weights. " +
"See [documentation](https://docs.streamlit.io/en/stable/api.html#streamlit.columns) "
+ "for more information.")
if isinstance(weights, int):
# If the user provided a single number, expand into equal weights.
# E.g. (1,) * 3 => (1, 1, 1)
# NOTE: A negative/zero spec will expand into an empty tuple.
weights = (1, ) * weights
if len(weights) == 0 or any(weight <= 0 for weight in weights):
raise weights_exception
def column_proto(weight):
col_proto = BlockProto()
col_proto.column.weight = weight
col_proto.allow_empty = True
return col_proto
horiz_proto = BlockProto()
horiz_proto.horizontal.total_weight = sum(weights)
row = self.dg._block(horiz_proto)
return [row._block(column_proto(w)) for w in weights]
def column_proto(weight):
col_proto = BlockProto()
col_proto.column.weight = weight
col_proto.allow_empty = True
return col_proto
def column_proto(normalized_weight):
col_proto = BlockProto()
col_proto.column.weight = normalized_weight
col_proto.allow_empty = True
return col_proto