“rationaliser la feuille de triche” Réponses codées

rationaliser la feuille de triche

Install & Import
streamlit run first_app.py

# Import convention
>>> import streamlit as st
Command line
$ streamlit --help
$ streamlit run your_script.py
$ streamlit hello
$ streamlit config show
$ streamlit cache clear
$ streamlit docs
$ streamlit --version
Pre-release features
pip uninstall streamlit
pip install streamlit-nightly --upgrade
Learn more about beta and experimental features

Magic commands
# Magic commands implicitly
# call st.write().
'_This_ is some **Markdown***'
my_variable
'dataframe:', my_data_frame
Display text
st.text('Fixed width text')
st.markdown('_Markdown_') # see *
st.latex(r''' e^{i\pi} + 1 = 0 ''')
st.write('Most objects') # df, err, func, keras!
st.write(['st', 'is <', 3]) # see *
st.title('My title')
st.header('My header')
st.subheader('My sub')
st.code('for i in range(8): foo()')
* optional kwarg unsafe_allow_html = True
Display data
st.dataframe(my_dataframe)
st.table(data.iloc[0:10])
st.json({'foo':'bar','fu':'ba'})
st.metric('My metric', 42, 2)
Display media
st.image('./header.png')
st.audio(data)
st.video(data)
Add widgets to sidebar
# Just add it after st.sidebar:
>>> a = st.sidebar.radio('Select one:', [1, 2])

# Or use "with" notation:
>>> with st.sidebar:
>>>   st.radio('Select one:', [1, 2])
Columns
# Two equal columns:
>>> col1, col2 = st.columns(2)
>>> col1.write("This is column 1")
>>> col2.write("This is column 2")

# Three different columns:
>>> col1, col2, col3 = st.columns([3, 1, 1])
# col1 is larger.

# You can also use "with" notation:
>>> with col1:
>>>   st.radio('Select one:', [1, 2])
Control flow
st.stop()

>>> with st.form(key='my_form'):
>>>   username = st.text_input('Username')
>>>   password = st.text_input('Password')
>>>   st.form_submit_button('Login')
Display interactive widgets
st.button('Click me')
st.checkbox('I agree')
st.radio('Pick one', ['cats', 'dogs'])
st.selectbox('Pick one', ['cats', 'dogs'])
st.multiselect('Buy', ['milk', 'apples', 'potatoes'])
st.slider('Pick a number', 0, 100)
st.select_slider('Pick a size', ['S', 'M', 'L'])
st.text_input('First name')
st.number_input('Pick a number', 0, 10)
st.text_area('Text to translate')
st.date_input('Your birthday')
st.time_input('Meeting time')
st.file_uploader('Upload a photo')
st.download_button('Download file', data)
st.color_picker('Pick a color')

# Use widgets' returned values in variables:
>>> for i in range(int(st.number_input('Num:'))):
>>>   foo()
>>> if st.sidebar.selectbox('I:',['f']) == 'f':
>>>   b()
>>> my_slider_val = st.slider('Quinn Mallory', 1, 88)
>>> st.write(slider_val)
Mutate data
# Add rows to a dataframe after
# showing it.
>>> element = st.dataframe(df1)
>>> element.add_rows(df2)

# Add rows to a chart after
# showing it.
>>> element = st.line_chart(df1)
>>> element.add_rows(df2)
Display code
>>> with st.echo():
>>>   st.write('Code will be executed and printed')
Placeholders, help, and options
# Replace any single element.
>>> element = st.empty()
>>> element.line_chart(...)
>>> element.text_input(...)  # Replaces previous.

# Insert out of order.
>>> elements = st.container()
>>> elements.line_chart(...)
>>> st.write("Hello")
>>> elements.text_input(...)  # Appears above "Hello".

st.help(pandas.DataFrame)
st.get_option(key)
st.set_option(key, value)
st.set_page_config(layout='wide')
Optimize performance
Legacy caching
>>> @st.cache
... def foo(bar):
...   # Do something expensive in here...
...   return data
>>> # Executes foo
>>> d1 = foo(ref1)
>>> # Does not execute foo
>>> # Returns cached item by reference, d1 == d2
>>> d2 = foo(ref1)
>>> # Different arg, so function foo executes
>>> d3 = foo(ref2)
Cache data objects
# E.g. Dataframe computation, storing downloaded data, etc.
>>> @st.experimental_memo
... def foo(bar):
...   # Do something expensive and return data
...   return data
# Executes foo
>>> d1 = foo(ref1)
# Does not execute foo
# Returns cached item by value, d1 == d2
>>> d2 = foo(ref1)
# Different arg, so function foo executes
>>> d3 = foo(ref2)
Cache non-data objects
# E.g. TensorFlow session, database connection, etc.
>>> @st.experimental_singleton
... def foo(bar):
...   # Create and return a non-data object
...   return session
# Executes foo
>>> s1 = foo(ref1)
# Does not execute foo
# Returns cached item by reference, d1 == d2
>>> s2 = foo(ref1)
# Different arg, so function foo executes
>>> s3 = foo(ref2)
Display progress and status
>>> with st.spinner(text='In progress'):
>>>   time.sleep(5)
>>>   st.success('Done')

st.progress(progress_variable_1_to_100)
st.balloons()
st.error('Error message')
st.warning('Warning message')
st.info('Info message')
st.success('Success message')
st.exception(e)