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Merge pull request #20 from sofiamonsalve/cloudApp
PR to Julia's :)
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.gitignore

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# Database files
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src/*.sql
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.streamlit/secrets.toml
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src/names.dmp
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src/taxonomy_names.csv
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src/filtered_names.json
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.venv/
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__pycache__/
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# Server files
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Data/
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#Data/
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IntermediateFiles/
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# ========================================================================
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src/__pycache__/
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src/__pycache__/*
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# Ignore our secrets
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# secrets.toml
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poetry.lock
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pyproject.toml
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app/templates/yaml_templates/

.streamlit/README.md

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In this folder we have the `secrets.toml` file with the necessary credentials for connecting to our db.

.streamlit/config.toml

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[server]
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enableXsrfProtection=false
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[theme]
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primaryColor="#088395"
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backgroundColor="#ffffff"
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secondaryBackgroundColor="#caeaea"
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textColor="#071952"
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.streamlit/pages.toml

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[[pages]]
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path = "app.py"
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name = "Home"
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icon = ":house:"
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[[pages]]
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path = "pages/Database_Search.py"
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name = "Search"
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icon = ":mag:"
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[[pages]]
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path = "pages/Visualization_Dashboard.py"
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name = "Dashboard"
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icon = ":chart_with_upwards_trend:"
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[[pages]]
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path = "pages/Upload_Data.py"
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name = "Upload data"
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icon = ":outbox_tray:"
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[[pages]]
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path = "pages/Help.py"
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name = "Help"
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icon = ":question:"
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[[pages]]
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path = "pages/About_Us.py"
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name = "About us"
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icon = ":lab_coat:"

README.md

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# bacterial_growth
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# How to run the app
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This is a branch dedicated for the streamlit cloud.
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It has
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# Environment set up
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First, you need to set up the environment that contain all the packages that will be used by the program. To do so, run the following commands:
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````
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cd envs/
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conda env create -f environment.yml
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````
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Hello

__init__.py

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#import os
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#import sys
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#current_dir = os.path.dirname(os.path.realpath(__file__))[:-3]
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#relative_path_to_src = os.path.join(current_dir, 'src')
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#sys.path.append(relative_path_to_src)
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#from constants import *
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app.py

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import streamlit as st
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from streamlit_extras.app_logo import add_logo
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from st_pages import show_pages_from_config
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from streamlit_extras.badges import badge
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# Preload CSS file
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@st.cache_resource
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def load_css():
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with open("style.css") as css:
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return css.read()
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st.set_page_config(page_title="µGrowthDB", page_icon="🔍", layout='wide')
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add_logo("figs/logo_sidebar3.png", height=100)
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st.markdown(f'<style>{load_css()}</style>', unsafe_allow_html=True)
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st.image('figs/logo.png')
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st.write('')
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st.write('')
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st.write('')
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st.write('')
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st.markdown("![badge](https://img.shields.io/badge/status-under%20development-orange?style=for-the-badge)")
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st.subheader("**Welcome to µGrowthDB**")
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st.markdown(
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"""
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µGrowthDB is a relational database that provides a structure to store different types of microbial growth data.
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Our main objective is to serve as a comprehensive resource for researchers interested in studying the growth dynamics of microbial species.
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By providing access to growth projects and studies uploaded by other researchers.µ
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""")
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st.page_link("pages/Database_Search.py", label=":blue[**Search Growth Studies**]", help="Click on to start a search")
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st.markdown(
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"""
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Users can search for experimental data collected from microbial growth studies. The search can be filtered by different experimental conditions and characteristicas like
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Project name, Study name, microbial strains, metabolites, culture media and pH.
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All the data at µGrowthDB is publically available for everyone. To further analyze and compare different datasets we offer the feature of downloading several datasets at once.
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""")
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st.page_link("pages/Upload_Data.py", label=":blue[**Upload your Microbial Growth Project and Studies**]", help="Click on to start a sharing")
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st.markdown(
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"""
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At µGrowthDB, we recognize the invaluable contributions of researchers in advancing our understanding of microbial dynamics. Sharing growth data publicly
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plays a crucial role in increasing scientific progress and collaboration within the research community. We allow reasearcher to upload their experimental data by following five steps
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that allow us to keep an adquate quality control over the data.
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""")
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st.page_link("pages/Visualization_Dashboard.py", label=":blue[**Visualize Growth Data:**]", help="Click on to plot data")
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st.markdown(
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"""
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Users can visualize all the different microbial growth experiments with its corresponding measured techniques in the database, this means plotting accurate growth curves accross different conditions.
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""")
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st.write('')
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st.write('')
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show_pages_from_config()

app/.streamlit/secrets.toml

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[connections.BacterialGrowth]
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dialect = "mysql"
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host = "localhost"
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port = 3306
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database = "BacterialGrowth"
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username = "root"
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password = "Amartemucho123-"
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Defined:
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- 1
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- 1
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- 0
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- 0
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Description:
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- .nan
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- .nan
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- attached
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- attached
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Member_ID:
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- member_1
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- member_2
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- member_3
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- member_4
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Member_Name:
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- Bacteroides thetaiotaomicron VPI-5482
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- Roseburia intestinalis L1-82
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- Bacteroides thetaiotaomicron
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- Roseburia intestinalis
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NCBI_ID:
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- 226186
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- 536231
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- 226186
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- 536231
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Experiment_ID: []
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NEW_Community_ID: []
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NEW_Compartment_ID: []
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OLD_Community_ID: []
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OLD_Compartment_ID: []
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Perturbation_Description: []
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Perturbation_EndTime: []
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Perturbation_ID: []
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Perturbation_MaximumValue: []
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Perturbation_MinimumValue: []
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Perturbation_StartTime: []

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