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Get started
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Create your first Streamlit app
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The easiest way to learn how to use Streamlit is to try things out yourself. As you read through this guide, test each method.
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Streamlit is more than just a way to make data apps, it’s also a community of creators that share their apps and ideas and help each other make their work better.
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For this guide we’re using small amounts of data so that we can move quickly. You can check out our Tutorial on creating a data explorer to see an example of how to load data from an API and use @st.cache to cache it.
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Check out our community forum and post a question
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- Create a new Python file named first_app.py, then open it with your IDE or text editor.
- Next, import Streamlit.
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- The first step is to create a new Python script. Let’s call it uber_pickups.py.
- Open uber_pickups.py in your favorite IDE or text editor, then add these lines:
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- Check out our community forum and post a question
- Quick help from command line with streamlit --help
- Read more documentation! Check out:
- Streamlit Cookbook for things like caching and inserting elements out of order
- API reference for examples of every Streamlit command
Code snippet
import streamlit as st
# To make things easier later, we're also importing numpy and pandas for
# working with sample data.myscript.sh
ls -l myscript.shCode header
streamlit.text
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For this guide we’re using small amounts of data so that we can move quickly. You can check out our Tutorial on creating a data explorer to see an example of how to load data from an API and use @st.cache to cache it.
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Tip
Did you know you can also pass a URL to streamlit run? This is great when combined with GitHub Gists. For example:
streamlit run
https://raw.githubusercontent.com/streamlit/demo-uber-nyc-pickups/master/streamlit_app.pyNote Block (Important)
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If the email you originally signed-up with isn’t the primary email associated with your GitHub account, just reply to your invite email telling us your primary GitHub email so we can grant access to the correct account.
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| Function signature | |
|---|---|
streamlit.text(body) | |
| Parameters | |
body (str) | The string to display |
body (str) | The string to display |
| Function signature | |
|---|---|
streamlit.markdown(body, unsafe_allow_html=False) | |
| Parameters | |
body (str) | The string to display |
body (str) | The string to display as GitHub-flavored Markdown. Syntax information can be found at: https://github.github.com/gfm. This also supports:
|
Code Highlights
import streamlit as st
import pandas as pd
import numpy as np
st.title('Uber pickups in NYC')
DATE_COLUMN = 'date/time'
DATA_URL = ('https://s3-us-west-2.amazonaws.com/'
'streamlit-demo-data/uber-raw-data-sep14.csv.gz')
@st.cacache_datache
def load_data(nrows):
data = pd.read_csv(DATA_URL, nrows=nrows)
lowercase = lambda x: str(x).lower()
data.rename(lowercase, axis='columns', inplace=True)
data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])
return data
data_load_state = st.text('Loading data...')
data = load_data(10000)
data_load_state.text("Done! (using st.cache_data)")Show Component Alongside Code
chart_data = pd.DataFrame(
p.random.randn(20, 3),
columns=['a', 'b', 'c']
)
st.altair_chart(chart_data)Was This Page Helpful Widget
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Our forums are full of helpful information and Streamlit experts.
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Join the community
Streamlit is more than just a way to make data apps, it’s also a community of creators that share their apps and ideas and help each other make their work better. Please come join us on the community forum. We love to hear your questions, ideas, and help you work through your bugs — stop by today!
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Tutorials include our Get Started guide and a few step-by-step examples to building different types of apps in Streamlit.
Tutorials include our Get Started guide and a few step-by-step examples to building different types of apps in Streamlit.