Jcharis/Streamlit_DataScience_Apps: Streamlit Data Science and ML Apps in Python · GitHub

Name		Name	Last commit message	Last commit date
Build_LLM_ChatBots_with_Chainlit		Build_LLM_ChatBots_with_Chainlit
CSS_Shape_Generator_app		CSS_Shape_Generator_app
Contraceptive_Method_Choice_Predictor		Contraceptive_Method_Choice_Predictor
Deploying_Streamlit_Apps_To_GCP		Deploying_Streamlit_Apps_To_GCP
EDA_app_with_Streamlit_Components		EDA_app_with_Streamlit_Components
Fake_Data_Generator_App		Fake_Data_Generator_App
File_Downloader_App		File_Downloader_App
File_Uploads_App		File_Uploads_App
How_to_Create_A_Login_n_SignUp_Section_in_Streamlit		How_to_Create_A_Login_n_SignUp_Section_in_Streamlit
Iris_EDA_Web_App		Iris_EDA_Web_App
Job_Search_App_with_Streamlit_Forms_n_GithubAPI		Job_Search_App_with_Streamlit_Forms_n_GithubAPI
Load_Testing_Streamlit_Apps		Load_Testing_Streamlit_Apps
Movie_Directory_App_with_Layouts		Movie_Directory_App_with_Layouts
NLP_App_with_Streamlit_Python		NLP_App_with_Streamlit_Python
NLP_app_with_Spacy_Streamlit		NLP_app_with_Spacy_Streamlit
Q&A_About_Streamlit_Python		Q&A_About_Streamlit_Python
Securing_Login_Page_Against_SQL_Injection		Securing_Login_Page_Against_SQL_Injection
Simple_CRuD_Blog_App_with_Streamlit		Simple_CRuD_Blog_App_with_Streamlit
Streamlit_Python_Crash_Course		Streamlit_Python_Crash_Course
TextClassifierRiverMLApp		TextClassifierRiverMLApp
Using_PyGWalker_With_Streamlit		Using_PyGWalker_With_Streamlit
Working_with_Streamlit_Forms		Working_with_Streamlit_Forms
common_ml_datasets_explorer_app		common_ml_datasets_explorer_app
course_recommendation_sys_app		course_recommendation_sys_app
email_extractor_app		email_extractor_app
face_detection_app		face_detection_app
gender_classifier_mlapp_with_streamlit		gender_classifier_mlapp_with_streamlit
how_to_add_session__state-settings-App		how_to_add_session__state-settings-App
news_classifier_nlp-app		news_classifier_nlp-app
sentiment_analysis_emoji_app_with_streamlit		sentiment_analysis_emoji_app_with_streamlit
sqlplayground_app		sqlplayground_app
README.md		README.md

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README

Streamlit_DataScience_Apps

Streamlit Data Science and ML Apps in Python

How to Deploy Streamlit Apps to Heroku

1. Create An Account Heroku by signing up.

2. Install Heroku CLI

3. Create Your Github Repository for your app

4. Build your app

5. Login to Heroku From the CLI

heroku Login

6. Create Your 3 Required Files(setup.sh,Procfile,requirements.txt)

Place the code below in their respective files

Code for setup.sh

mkdir -p ~/.streamlit/

echo "\
[general]\n\
email = \"your-email@domain.com\"\n\
" > ~/.streamlit/credentials.toml

echo "\
[server]\n\
headless = true\n\
enableCORS=false\n\
port = $PORT\n\
" > ~/.streamlit/config.toml

Code for setup.sh (Alternate with no credentials.toml)

mkdir -p ~/.streamlit/

echo "\
[server]\n\
headless = true\n\
port = $PORT\n\
enableCORS = false\n\
\n\
" > ~/.streamlit/config.toml

Code For Procfile

web: sh setup.sh && streamlit run your_app.py

7. Create App with CLI

heroku create name-of-your-app

8. Commit and Push Your Code to Github

git add your app 
git commit -m "your comment description"
git push

9. Push To Heroku to Deploy

git push heroku master

Credits:

gabe_maldonado

Streamlit team

Thanks For Your Time

####By

Jesse E.Agbe(JCharis)
Jesus Saves@JCharisTech

About

Streamlit Data Science and ML Apps in Python

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Streamlit_DataScience_Apps

How to Deploy Streamlit Apps to Heroku

1. Create An Account Heroku by signing up.

2. Install Heroku CLI

3. Create Your Github Repository for your app

4. Build your app

5. Login to Heroku From the CLI

6. Create Your 3 Required Files(setup.sh,Procfile,requirements.txt)

Code for setup.sh

Code for setup.sh (Alternate with no credentials.toml)

Code For Procfile

7. Create App with CLI

8. Commit and Push Your Code to Github

9. Push To Heroku to Deploy

Credits:

Thanks For Your Time

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Streamlit_DataScience_Apps

How to Deploy Streamlit Apps to Heroku

1. Create An Account Heroku by signing up.

2. Install Heroku CLI

3. Create Your Github Repository for your app

4. Build your app

5. Login to Heroku From the CLI

6. Create Your 3 Required Files(setup.sh,Procfile,requirements.txt)

Code for setup.sh

Code for setup.sh (Alternate with no credentials.toml)

Code For Procfile

7. Create App with CLI

8. Commit and Push Your Code to Github

9. Push To Heroku to Deploy

Credits:

Thanks For Your Time

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