STREAMLIT Archives - icodebroker

[PYTHON/STREAMLIT] write 함수 : DataFrame 객체를 사용해 대화형 테이블 만들기

■ write 함수에서 DataFrame 객체를 사용해 대화형 테이블를 만드는 방법을 보여준다. ▶ main.py


import streamlit as st
import pandas    as pd

@st.cache_data
def loadData(url, rowCount):
    dataFrame = pd.read_csv(url, nrows = rowCount)
    changeToLowerCaseString = lambda x: str(x).lower()
    dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)
    dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])
    return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

st.subheader("Raw data")

st.write(dataFrame)

import streamlit as st

import pandas as pd

@st.cache_data

def loadData(url, rowCount):

dataFrame = pd.read_csv(url, nrows = rowCount)

changeToLowerCaseString = lambda x: str(x).lower()

dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)

dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])

return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

st.subheader("Raw data")

st.write(dataFrame)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을

[PYTHON/STREAMLIT] 단일 페이지 앱 만들기

■ 단일 페이지 앱을 만드는 방법을 보여준다. ▶ main.py


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

@st.cache_data
def loadData(url, rowCount):
    dataFrame = pd.read_csv(url, nrows = rowCount)
    changeToLowerCaseString = lambda x: str(x).lower()
    dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)
    dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])
    return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

if st.checkbox("Show raw data"):
    st.subheader("Raw data")
    st.write(dataFrame)

st.subheader("Number of pickups by hour")

histogramArrayTuple = np.histogram(dataFrame["date/time"].dt.hour, bins = 24, range = (0, 24))

histogramValueNDArray = histogramArrayTuple[0]

st.bar_chart(histogramValueNDArray)

hour = st.slider("hour", 0, 23, 17)

filteredDataFrame = dataFrame[dataFrame["date/time"].dt.hour == hour]

st.subheader("Map of all pickups at %s:00" % hour)

st.map(filteredDataFrame)

import streamlit as st

import pandas as pd

import numpy as np

@st.cache_data

def loadData(url, rowCount):

dataFrame = pd.read_csv(url, nrows = rowCount)

changeToLowerCaseString = lambda x: str(x).lower()

dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)

dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])

return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

if st.checkbox("Show raw data"):

st.subheader("Raw data")

st.write(dataFrame)

st.subheader("Number of pickups by hour")

histogramArrayTuple = np.histogram(dataFrame["date/time"].dt.hour, bins = 24, range = (0, 24))

histogramValueNDArray = histogramArrayTuple[0]

st.bar_chart(histogramValueNDArray)

hour = st.slider("hour", 0, 23, 17)

filteredDataFrame = dataFrame[dataFrame["date/time"].dt.hour == hour]

st.subheader("Map of all pickups at %s:00" % hour)

st.map(filteredDataFrame)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] map 함수 : slider 객체의 선택 값으로 필터링 데이터로 지도 그리기

■ map 함수에서 slider 객체의 선택 값으로 필터링한 데이터로 지도를 그리는 방법을 보여준다. ▶ main.py


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

@st.cache_data
def loadData(url, rowCount):
    dataFrame = pd.read_csv(url, nrows = rowCount)
    changeToLowerCaseString = lambda x: str(x).lower()
    dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)
    dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])
    return dataFrame

st.title("Uber pickups in NYC")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

hour = st.slider("hour", 0, 23, 17)

filteredDataFrame = dataFrame[dataFrame["date/time"].dt.hour == hour]

st.subheader("Map of all pickups at %s:00" % hour)

st.map(filteredDataFrame)

import streamlit as st

import pandas as pd

import numpy as np

@st.cache_data

def loadData(url, rowCount):

dataFrame = pd.read_csv(url, nrows = rowCount)

changeToLowerCaseString = lambda x: str(x).lower()

dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)

dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])

return dataFrame

st.title("Uber pickups in NYC")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

hour = st.slider("hour", 0, 23, 17)

filteredDataFrame = dataFrame[dataFrame["date/time"].dt.hour == hour]

st.subheader("Map of all pickups at %s:00" % hour)

st.map(filteredDataFrame)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install

[PYTHON/STREAMLIT] bar_chart 함수 : 히스토그램 차트 그리기

■ bar_chart 함수를 사용해 히스토그램 차트를 그리는 방법을 보여준다. ▶ main.py


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

@st.cache_data
def loadData(url, rowCount):
    dataFrame = pd.read_csv(url, nrows = rowCount)
    changeToLowerCaseString = lambda x: str(x).lower()
    dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)
    dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])
    return dataFrame

st.title("Uber pickups in NYC")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

st.subheader("Number of pickups by hour")

histogramArrayTuple = np.histogram(dataFrame["date/time"].dt.hour, bins = 24, range = (0, 24))

histogramValueNDArray = histogramArrayTuple[0]

st.bar_chart(histogramValueNDArray)

import streamlit as st

import pandas as pd

import numpy as np

@st.cache_data

def loadData(url, rowCount):

dataFrame = pd.read_csv(url, nrows = rowCount)

changeToLowerCaseString = lambda x: str(x).lower()

dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)

dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])

return dataFrame

st.title("Uber pickups in NYC")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

st.subheader("Number of pickups by hour")

histogramArrayTuple = np.histogram(dataFrame["date/time"].dt.hour, bins = 24, range = (0, 24))

histogramValueNDArray = histogramArrayTuple[0]

st.bar_chart(histogramValueNDArray)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] @cache_data 데코레이터 : 함수에서 반환 데이터 캐시하기

■ @cache_data 데코레이터를 사용해 함수에서 반환 데이터를 캐시하는 방법을 보여준다. ▶ main.py


import streamlit as st
import pandas    as pd

@st.cache_data
def loadData(url, rowCount):
    dataFrame = pd.read_csv(url, nrows = rowCount)
    changeToLowerCaseString = lambda x: str(x).lower()
    dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)
    dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])
    return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

st.subheader("Raw data")

st.write(dataFrame)

import streamlit as st

import pandas as pd

@st.cache_data

def loadData(url, rowCount):

dataFrame = pd.read_csv(url, nrows = rowCount)

changeToLowerCaseString = lambda x: str(x).lower()

dataFrame.rename(changeToLowerCaseString, axis = "columns", inplace = True)

dataFrame["date/time"] = pd.to_datetime(dataFrame["date/time"])

return dataFrame

st.title("Uber pickups in NYC")

loadingDataText = st.text("Loading data...")

dataFrame = loadData("https://s3-us-west-2.amazonaws.com/streamlit-demo-data/uber-raw-data-sep14.csv.gz", 10000)

loadingDataText.text("Done! (using st.cache_data)")

st.subheader("Raw data")

st.write(dataFrame)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] subheader 함수 : 서브 헤더 문자열 표시하기

■ subheader 함수를 사용해 서브 헤더 문자열을 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.title("Uber pickups in NYC")

st.subheader("Number of pickups by hour")

import streamlit as st

st.title("Uber pickups in NYC")

st.subheader("Number of pickups by hour")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] title 함수 : 제목 문자열 표시하기

■ title 함수를 사용해 제목 문자열을 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.title("Uber pickups in NYC")

import streamlit as st

st.title("Uber pickups in NYC")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] image 함수 : 이미지 표시하기

■ image 함수를 사용해 이미지를 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.image("./blueberries.jpg")

import streamlit as st

st.image("./blueberries.jpg")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다. blueberries.jpg

[PYTHON/STREAMLIT] sidebar 변수 : markdown 함수를 사용해 마크다운 문자열 표시하기

■ sidebar 변수에서 markdown 함수를 사용해 마크다운 문자열을 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.markdown("# Main page 🎈")

st.sidebar.markdown("# Main page 🎈")

import streamlit as st

st.markdown("# Main page 🎈")

st.sidebar.markdown("# Main page 🎈")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을

[PYTHON/STREAMLIT] markdown 함수 : 마크다운 문자열 표시하기

■ markdown 함수를 사용해 마크다운 문자열을 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.markdown("# Main page 🎈")

import streamlit as st

st.markdown("# Main page 🎈")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] 멀티 페이지 앱 만들기

■ 멀티 페이지 앱을 만드는 방법을 보여준다. ▶ main.py


import streamlit as st

st.markdown("# Main page 🎈")

st.sidebar.markdown("# Main page 🎈")

import streamlit as st

st.markdown("# Main page 🎈")

st.sidebar.markdown("# Main page 🎈")

▶ ./pages/page1.py


import streamlit as st

st.markdown("# Page 1 ❄️")

st.sidebar.markdown("# Page 1 ❄️")

import streamlit as st

st.markdown("# Page 1 ❄️")

st.sidebar.markdown("# Page 1 ❄️")

▶ ./pages/page2.py


import streamlit as st

st.markdown("# Page 2 🎉")

st.sidebar.markdown("# Page 2 🎉")

import streamlit as st

st.markdown("# Page 2 🎉")

st.sidebar.markdown("# Page 2 🎉")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install

[PYTHON/STREAMLIT] connection 함수 : 데이터베이스 연결 만들기

■ connection 함수를 사용해 POSTGRESQL 데이터베이스 연결을 만드는 방법을 보여준다. ▶ ./.streamlit/secrets.toml


[connections.posgreSQL]
    type="sql"
    dialect="postgresql"
    username="user1"
    password="password1"
    host="127.0.0.1"
    port=5432
    database="test"

[connections.posgreSQL]

type="sql"

dialect="postgresql"

username="user1"

password="password1"

host="127.0.0.1"

port=5432

database="test"

※ postgreSQL : 연결명 ※ postgresql : 데이터베이스 타입

[PYTHON/STREAMLIT] SqlConnection 클래스 : query 메소드를 사용해 데이터 조회하기

■ SqlConnection 클래스의 query 메소드를 사용해 데이터를 조회하는 방법을 보여준다. ▶ ./.streamlit/secrets.toml


[connections.posgreSQL]
    type="sql"
    dialect="postgresql"
    username="user1"
    password="password1"
    host="127.0.0.1"
    port=5432
    database="test"

[connections.posgreSQL]

type="sql"

dialect="postgresql"

username="user1"

password="password1"

host="127.0.0.1"

port=5432

database="test"

※ postgreSQL : 연결명 ※ postgresql : 데이터베이스 타입

[PYTHON/STREAMLIT] scatter_chart 함수 : SCATTER 차트 그리기

■ scatter_chart 함수를 사용해 SCATTER 차트를 그리는 방법을 보여준다. ▶ main.py


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

if "df" not in st.session_state:
    st.session_state.dataFrame = pd.DataFrame(np.random.randn(20, 2), columns = ["x", "y"])

st.header("Choose a datapoint color")

color = st.color_picker("Color", "#FF0000")

st.divider()

st.scatter_chart(st.session_state.dataFrame, x = "x", y = "y", color = color)

import streamlit as st

import pandas as pd

import numpy as np

if "df" not in st.session_state:

st.session_state.dataFrame = pd.DataFrame(np.random.randn(20, 2), columns = ["x", "y"])

st.header("Choose a datapoint color")

color = st.color_picker("Color", "#FF0000")

st.divider()

st.scatter_chart(st.session_state.dataFrame, x = "x", y = "y", color = color)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] divider 함수 : 분리선 추가하기

■ divider 함수를 사용해 분리선을 추가하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.header("Choose a datapoint color")

st.divider()

color = st.color_picker("Color", "#ff0000")

import streamlit as st

st.header("Choose a datapoint color")

st.divider()

color = st.color_picker("Color", "#ff0000")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] color_picker 함수 : 색상 선택하기

■ color_picker 함수를 사용해 색상을 선택하는 방법을 보여준다. ▶ main.py


import streamlit as st

color = st.color_picker("색상", "#ff0000")

import streamlit as st

color = st.color_picker("색상", "#ff0000")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] header 함수 : 헤더 문자열 표시하기

■ header 함수를 사용해 헤더 문자열을 표시하는 방법을 보여준다. ▶ main.py


import streamlit as st

st.header("Choose a datapoint color")

import streamlit as st

st.header("Choose a datapoint color")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] session_state 변수 : 세션 상태 관리하기

■ session_state 변수를 사용해 세션 상태를 관리하는 방법을 보여준다. ※ session_state 변수의 타입은 streamlit.runtime.state.session_state_proxy.SessionStateProxy 클래스이다. ▶ main.py


import streamlit as st

if "counter" not in st.session_state:
    st.session_state.counter = 0

st.session_state.counter += 1

st.header(f"This page has run {st.session_state.counter} times.")

st.button("Run it again")

import streamlit as st

if "counter" not in st.session_state:

st.session_state.counter = 0

st.session_state.counter += 1

st.header(f"This page has run {st.session_state.counter} times.")

st.button("Run it again")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.2
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.2
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.2

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.2

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※

[PYTHON/STREAMLIT] text 함수 : 텍스트 만들기

■ text 함수를 사용해 텍스트를 만드는 방법을 보여준다. ▶ main.py


import streamlit as st

for i in range(5):
  st.text(f"텍스트 {i + 1}")

import streamlit as st

for i in range(5):

st.text(f"텍스트 {i + 1}")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] empty 함수 : 플레이스 홀더 만들기

■ empty 함수를 사용해 플레이스 홀더를 만드는 방법을 보여준다. ▶ main.py


import time

import streamlit as st

emptyDeltaGenerator = st.empty()

for i in range(100):
  emptyDeltaGenerator.text(f"Iteration {i + 1}")
  time.sleep(0.1)

import time

import streamlit as st

emptyDeltaGenerator = st.empty()

for i in range(100):

emptyDeltaGenerator.text(f"Iteration {i + 1}")

time.sleep(0.1)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] progress 함수 : 진행바 만들기

■ progress 함수를 사용해 진행바를 만드는 방법을 보여준다. ▶ main.py


import time

import streamlit as st

"Starting a long computation..."

emptyDeltaGenerator = st.empty()

progressDeltaGenerator = st.progress(0)

for i in range(100):
  emptyDeltaGenerator.text(f"Iteration {i + 1}")
  progressDeltaGenerator.progress(i + 1)
  time.sleep(0.1)

"...and now we\"re done!"

import time

import streamlit as st

"Starting a long computation..."

emptyDeltaGenerator = st.empty()

progressDeltaGenerator = st.progress(0)

for i in range(100):

emptyDeltaGenerator.text(f"Iteration {i + 1}")

progressDeltaGenerator.progress(i + 1)

time.sleep(0.1)

"...and now we\"re done!"

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] radio 함수 : 라디오 버튼 만들기

■ radio 함수를 사용해 라디오 버튼을 만드는 방법을 보여준다. ▶ main.py


import streamlit as st

option = st.radio(
    "Sorting hat",
    ("Gryffindor", "Ravenclaw", "Hufflepuff", "Slytherin")
)

st.write(f"You are in {option} house!")

import streamlit as st

option = st.radio(

"Sorting hat",

("Gryffindor", "Ravenclaw", "Hufflepuff", "Slytherin")

)

st.write(f"You are in {option} house!")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] button 함수 : 버튼 만들기

■ button 함수를 사용해 버튼을 만드는 방법을 보여준다. ▶ main.py


import streamlit as st

st.button("Press me!")

import streamlit as st

st.button("Press me!")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] columns 함수 : 앱 레이아웃 제어하기

■ columns 함수를 사용해 앱 레이아웃을 제어하는 방법을 보여준다. ▶ main.py


import streamlit as st

leftDeltaGenerator, rightDeltaGenerator = st.columns(2)

leftDeltaGenerator.button("Press me!")

with rightDeltaGenerator:
    option = st.radio(
        "Sorting hat",
        ("Gryffindor", "Ravenclaw", "Hufflepuff", "Slytherin")
    )

    st.write(f"You are in {option} house!")

import streamlit as st

leftDeltaGenerator, rightDeltaGenerator = st.columns(2)

leftDeltaGenerator.button("Press me!")

with rightDeltaGenerator:

option = st.radio(

"Sorting hat",

("Gryffindor", "Ravenclaw", "Hufflepuff", "Slytherin")

)

st.write(f"You are in {option} house!")

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install streamlit 명령을 실행했다.

[PYTHON/STREAMLIT] sidebar 변수 : selectbox/slider 함수를 사용해 사이드바에 선택 박스와 슬라이더 만들기

■ sidebar 변수에서 selectbox/slider 함수를 사용해 사이드바에 선택 박스와 슬라이더를 만드는 방법을 보여준다. ▶ main.py


import streamlit as st

# 사이드바에 선택 박스를 추가한다 :
option = st.sidebar.selectbox(
    "How would you like to be contacted?",
    ("Email", "Home phone", "Mobile phone")
)

st.write(option)

# 사이드바에 슬라이더를 추가한다.
value = st.sidebar.slider(
    "Select a range of values",
    0.0,
    100.0,
    (25.0, 75.0)
)

st.write(value)

import streamlit as st

# 사이드바에 선택 박스를 추가한다 :

option = st.sidebar.selectbox(

"How would you like to be contacted?",

("Email", "Home phone", "Mobile phone")

)

st.write(option)

# 사이드바에 슬라이더를 추가한다.

value = st.sidebar.slider(

"Select a range of values",

0.0,

100.0,

(25.0, 75.0)

)

st.write(value)

▶ requirements.txt


altair==5.3.0
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
gitdb==4.0.11
GitPython==3.1.43
idna==3.7
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==2.0.0
packaging==24.1
pandas==2.2.2
pillow==10.3.0
protobuf==5.27.1
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
six==1.16.0
smmap==5.0.1
streamlit==1.36.0
tenacity==8.4.1
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
watchdog==4.0.1

altair==5.3.0

attrs==23.2.0

blinker==1.8.2

cachetools==5.3.3

certifi==2024.6.2

charset-normalizer==3.3.2

click==8.1.7

gitdb==4.0.11

GitPython==3.1.43

idna==3.7

Jinja2==3.1.4

jsonschema==4.22.0

jsonschema-specifications==2023.12.1

markdown-it-py==3.0.0

MarkupSafe==2.1.5

mdurl==0.1.2

numpy==2.0.0

packaging==24.1

pandas==2.2.2

pillow==10.3.0

protobuf==5.27.1

pyarrow==16.1.0

pydeck==0.9.1

Pygments==2.18.0

python-dateutil==2.9.0.post0

pytz==2024.1

referencing==0.35.1

requests==2.32.3

rich==13.7.1

rpds-py==0.18.1

six==1.16.0

smmap==5.0.1

streamlit==1.36.0

tenacity==8.4.1

toml==0.10.2

toolz==0.12.1

tornado==6.4.1

typing_extensions==4.12.2

tzdata==2024.1

urllib3==2.2.2

watchdog==4.0.1

※ pip install