treuille

import matplotlib.pyplot as plt
import numpy as np
import streamlit as st
import time

fig, ax = plt.subplots()

max_x = 5
max_rand = 10

treuille

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([

treuille

import streamlit as st
import pandas as pd
import numpy as np

def display_dataframe_quickly(df, max_rows=5000, **st_dataframe_kwargs):
    """Display a subset of a DataFrame or Numpy Array to speed up app renders.
    
    Parameters
    ----------
    df : DataFrame | ndarray

treuille

import streamlit as st
from io import BytesIO
import matplotlib.pyplot as plt

def render_latex(formula, fontsize=12, dpi=300):
    """Renders LaTeX formula into Streamlit."""
    fig = plt.figure()
    text = fig.text(0, 0, '$%s$' % formula, fontsize=fontsize)

    fig.savefig(BytesIO(), dpi=dpi)  # triggers rendering

treuille

import streamlit as st
import pandas as pd
import numpy as np

n_points = 1000
sf_lat, sf_lon = 37.76, -122.4
map_data = pd.DataFrame({
    'lat': np.random.randn(n_points) / 50 + sf_lat,
    'lon': np.random.randn(n_points) / 50 + sf_lon,
    'colorR': np.random.uniform(size=n_points, high=255.0),

treuille

import streamlit as st
import functools


def partial_cache(func=None, **cache_kwargs):
    """Like st.cache, but if the function returns None, then nothing is cached.

    Parameters
    ----------
    func : Callable

treuille

import streamlit as st
import itertools

def paginator(label, items, items_per_page=10, on_sidebar=True):
    """Lets the user paginate a set of items.

    Parameters
    ----------
    label : str
        The label to display over the pagination widget.

treuille

import streamlit as st
import pandas as pd

DATA_BUCKET = "http://s3-us-west-2.amazonaws.com/streamlit-demo-data/"
DATA_URL = DATA_BUCKET + "uber-raw-data-sep14.csv.gz"
read_and_cache_csv = st.cache(pd.read_csv)
data = read_and_cache_csv(DATA_URL, nrows=100000)
st.write('Data', data)

treuille

import streamlit as st
import pandas as pd

with st.echo():
    @st.cache(ignore_hash=True)
    def load_cached():
        csv = pd.read_csv("http://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", nrows=100000)
        return csv

    df = load_cached()

treuille

# -*- coding: utf-8 -*-
# Copyright 2018-2019 Streamlit Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software