Philipp/aki_prj23_transparenzregister
Philipp/aki_prj23_transparenzregister
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Extracted Data-Extraction Metrhods into separate Files

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This commit is contained in:
Tim 2023-09-26 21:03:35 +02:00
parent e81b5fb518
commit 21c9e99ae3
2 changed files with 7 additions and 70 deletions
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27
src/aki_prj23_transparenzregister/ui/networkx_dash.py
View File

@ -109,22 +109,6 @@ def networkGraph(company_id: int) -> go.Figure:
# figure
return go.Figure(data=[edge_trace, node_trace], layout=layout)
# Dash App
# app = Dash(__name__)
# app.title = "Dash Networkx"
# app.layout = html.Div(
# [
# html.I("Write your EDGE_VAR"),
# html.Br(),
# dcc.Input(id="EGDE_VAR", type="text", value="K", debounce=True),
# dcc.Graph(id="my-graph"),
# ]
# )
def networkx_component(company_id: int):
layout = html.Div(
@ -135,14 +119,3 @@ def networkx_component(company_id: int):
)
return layout
# callback(
# Output("my-graph", "figure", allow_duplicate=True),
# [Input("EGDE_VAR", "value")],
# prevent_initial_call=True,
# )
# def update_output() -> None:
# return networkGraph()
# if __name__ == "__main__":
# app.run(debug=True)

50
src/aki_prj23_transparenzregister/ui/pages/home.py
View File

@ -4,9 +4,10 @@ from dash import html
import pandas as pd
import networkx as nx
import plotly.graph_objects as go
from dash import Dash, Input, Output, dcc, html, callback
from dash import Dash, Input, Output, dcc, html, callback, dash_table
from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider
from aki_prj23_transparenzregister.utils.sql import connector, entities
from aki_prj23_transparenzregister.utils.networkx.networkx_data import find_top_companies, find_all_company_relations
dash.register_page(
@ -20,36 +21,7 @@ dash.register_page(
"/personendetails/",
],
)
def find_all_company_relations() -> pd.DataFrame:
session = connector.get_session(JsonFileConfigProvider("./secrets.json"))
query_companies = session.query(entities.Company) #.all()
query_relations = session.query(entities.CompanyRelation) # .all()
companies_df: pd.DataFrame = pd.read_sql(str(query_companies), session.bind) # type: ignore
companies_relations_df: pd.DataFrame = pd.read_sql(str(query_relations), session.bind) # type: ignore
# print(companies_relations_df)
companies_relations_df = companies_relations_df[["relation_id","company_relation_company2_id"]]
# print(companies_relations_df)
company_name = []
connected_company_name = []
companies_relations_df = companies_relations_df.head()
# print(companies_relations_df)
for _, row in companies_relations_df.iterrows():
# print(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0])
# print("TEst")
company_name.append(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0])
connected_company_name.append(companies_df.loc[companies_df["company_id"] == row["company_relation_company2_id"]]["company_name"].values[0])
# print(connected_company_name)
# print(company_name)
companies_relations_df["company_name"] = company_name
companies_relations_df["connected_company_name"] = connected_company_name
# print("Test")
# print(companies_relations_df)
return companies_relations_df
# Plotly figure
def networkGraph(EGDE_VAR: None) -> go.Figure:
@ -58,10 +30,6 @@ def networkGraph(EGDE_VAR: None) -> go.Figure:
edges = []
for index, row in find_all_company_relations().iterrows():
edges.append([row["company_name"], row["connected_company_name"]])
# print(row["company_name"], row["connected_company_name"])
# print(edges)
# edges = df[["relation_id","company_relation_company2_id"]]
# edges = [[EGDE_VAR, "B"], ["B", "C"], ["B", "D"]]
network_graph = nx.Graph()
network_graph.add_edges_from(edges)
pos = nx.spring_layout(network_graph)
@ -154,14 +122,7 @@ def networkGraph(EGDE_VAR: None) -> go.Figure:
# figure
return go.Figure(data=[edge_trace, node_trace], layout=layout)
# Dash App
# app = Dash(__name__)
# app.title = "Dash Networkx"
df = find_top_companies()
layout = html.Div(
children = html.Div(
@ -169,12 +130,14 @@ layout = html.Div(
html.Div(
className="top_companytable_style",
children=[
html.I("Write your EDGE_VAR")
html.I("Write your EDGE_VAR"),
dash_table.DataTable(df.to_dict('records'), [{"name": i, "id": i} for i in df.columns])
]
),
html.Div(
className="networkx_style",
children=[
dcc.Dropdown(['eigenvector', 'degree', 'betweeness', 'closeness'], 'eigenvector', id='demo-dropdown'),
html.I("Write your EDGE_VAR"),
html.Br(),
# dcc.Dropdown(['eigenvector', 'degree', 'betweeness', 'closeness'], 'eigenvector', id='metric-dropdown'),
@ -193,4 +156,5 @@ layout = html.Div(
[Input("EGDE_VAR", "value")],
)
def update_output(EGDE_VAR: None) -> None:
find_top_companies()
return networkGraph(EGDE_VAR)