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import streamlit as st
import json
import base64
import requests
from io import StringIO
from streamlit_agraph import agraph, Node, Edge, Config
st.title('Json File Reader')
@st.cache_data
def get_json(url):
js = requests.get(url)
data = js.json()
return data
st.markdown("""Reads the Json file of Comments data extracted from Youtube API & creates graph""")
st.sidebar.header('File Upload')
your_file = st.sidebar.file_uploader(label="Upload the file here")
if your_file is not None:
bytes_data = your_file.getvalue()
json_data = json.loads(bytes_data)
else:
st.write("Reference: https://blog.streamlit.io/the-streamlit-agraph-component/")
json_data = get_json("https://raw.githubusercontent.com/insightbuilder/python_de_learners_data/main/code_script_notebooks/python_scripts/json_reader/toplevel_comment_zGAkhN1YZXM.json")
try:
length = len(json_data)
if length < 15:
indices = st.sidebar.slider("Start n End",0,length,(0,10))
else:
indices = st.sidebar.slider("Start n End",0,length,(0,int(length/15)))
selected_indices = json_data[indices[0]:indices[1]]
#st.write(selected_indices)
#creating the graph of the connection
nodes = []
edges = []
authors = []
video_id = selected_indices[0]['snippet']['videoId']
nodes.append(Node(id=video_id,lable='Youtube Video',
size = 25, symbolType='square'))
for data in selected_indices:
author = data['snippet']['topLevelComment']['snippet']['authorDisplayName'].split(' ')[0]
author_img = data['snippet']['topLevelComment']['snippet']['authorProfileImageUrl']
if author not in authors:
nodes.append(Node(id=author,
size=25,
shape="circularImage",
image=author_img) )
authors.append(author)
if 'replies' in data:
replies = data['replies']['comments']
for reply in replies:
reply_author = reply['snippet']['authorDisplayName'].split(' ')[0]
reply_author_img = reply['snippet']['authorProfileImageUrl']
if reply_author not in authors:
nodes.append(Node(id=reply_author,
size=15,
shape="circularImage",
image=reply_author_img) )
authors.append(reply_author)
edges.append( Edge(source=reply_author,
target=author,
type="CURVE_SMOOTH"))
edges.append(Edge(source=author, target=video_id,type="CURVE_SMOOTH"))
#st.write(authors)
config = Config(width=750,
height=950,
directed=True,
physics=False,
hierarchical=False,
node={'labelProperty':'label','renderLabel':True})
return_value = agraph(nodes = nodes, edges = edges, config = config)
except Exception as e:
st.write(e)
st.markdown("Provided Json is not Youtube API data. Unable to Parse")
#st.write(json_data)
"""
import streamlit as st
from py2neo import Graph, Node, Relationship
from scripts.viz import draw
# Initialize a Neo4j graph instance
graph = Graph()
graph.delete_all()
# Create nodes and relationships
nicole = Node("Person", name="Nicole", age=24)
drew = Node("Person", name="Drew", age=20)
mtdew = Node("Drink", name="Mountain Dew", calories=9000)
cokezero = Node("Drink", name="Coke Zero", calories=0)
coke = Node("Manufacturer", name="Coca Cola")
pepsi = Node("Manufacturer", name="Pepsi")
graph.create(nicole | drew | mtdew | cokezero | coke | pepsi)
graph.create(Relationship(nicole, "LIKES", cokezero))
graph.create(Relationship(nicole, "LIKES", mtdew))
graph.create(Relationship(drew, "LIKES", mtdew))
graph.create(Relationship(coke, "MAKES", cokezero))
graph.create(Relationship(pepsi, "MAKES", mtdew))
# Streamlit interface
st.title("Py2neo Application with Streamlit")
# Display graph visualization using Py2neo's draw function
st.subheader("Graph Visualization")
options = {"Person": "name", "Drink": "name", "Manufacturer": "name"}
draw(graph, options)
# Display node and relationship information
st.subheader("Node and Relationship Information")
st.write("Nodes:")
for node in [nicole, drew, mtdew, cokezero, coke, pepsi]:
st.write(f"{node.labels}: {node}")
st.write("Relationships:")
for relationship in graph.match(rel_type="LIKES"):
st.write(relationship)
st.write("Manufacturers:")
for manufacturer in graph.match(rel_type="MAKES"):
st.write(manufacturer)
import streamlit as st
import json
import base64
import requests
from io import StringIO
from streamlit_agraph import agraph, Node, Edge, Config
st.title('Json File Reader')
@st.cache_data
def get_json(url):
js = requests.get(url)
data = js.json()
return data
st.sidebar.header('File Upload')
your_file = st.sidebar.file_uploader(label="Upload the file here")
if your_file is not None:
bytes_data = your_file.getvalue()
json_data = json.loads(bytes_data)
else:
st.write("Example api file can be located here")
json_data = get_json("https://raw.githubusercontent.com/insightbuilder/python_de_learners_data/main/code_script_notebooks/python_scripts/json_reader/toplevel_comment_zGAkhN1YZXM.json")
try:
length = len(json_data)
if length < 15:
indices = st.sidebar.slider("Start n End",0,length,(0,10))
else:
indices = st.sidebar.slider("Start n End",0,length,(0,int(length/15)))
selected_indices = json_data[indices[0]:indices[1]]
#st.write(selected_indices)
#creating the graph of the connection
nodes = []
edges = []
authors = []
video_id = selected_indices[0]['snippet']['videoId']
nodes.append(Node(id=video_id,lable='Youtube Video',
size = 25, symbolType='square'))
for data in selected_indices:
author = data['snippet']['topLevelComment']['snippet']['authorDisplayName'].split(' ')[0]
author_img = data['snippet']['topLevelComment']['snippet']['authorProfileImageUrl']
if author not in authors:
nodes.append(Node(id=author,
size=25,
shape="circularImage",
image=author_img) )
authors.append(author)
if 'replies' in data:
replies = data['replies']['comments']
for reply in replies:
reply_author = reply['snippet']['authorDisplayName'].split(' ')[0]
reply_author_img = reply['snippet']['authorProfileImageUrl']
if reply_author not in authors:
nodes.append(Node(id=reply_author,
size=15,
shape="circularImage",
image=reply_author_img) )
authors.append(reply_author)
edges.append( Edge(source=reply_author,
target=author,
type="CURVE_SMOOTH"))
edges.append(Edge(source=author, target=video_id,type="CURVE_SMOOTH"))
#st.write(authors)
config = Config(width=750,
height=950,
directed=True,
physics=False,
hierarchical=False,
node={'labelProperty':'label','renderLabel':True})
return_value = agraph(nodes = nodes, edges = edges, config = config)
except Exception as e:
st.write(e)
st.markdown("Provided Json is not Youtube API data. Unable to Parse")
#st.write(json_data)
""" |