"""
st.markdown(hide_menu_style, unsafe_allow_html=True)
api_backend = api_endpoint_ip + options_file.api_backend_loc
url_hyperlink = '''
<a href= "{}" > <p style="text-align:right"> Documentação </p></a>
'''.format(options_file.documentation_url_solver_apv)
st.markdown(url_hyperlink, unsafe_allow_html=True)
session_state = SessionState.get(run_id=0,
overwrite_button_pressed=0,
save_button_pressed_flag=0,
part_ref_group='',
total_value_optimized=0,
df_solution=pd.DataFrame(),
dtss_goal=0,
max_part_number=9999,
minimum_cost_or_pvp=0,
sel_group='',
sel_local='')
sel_parameters = [
session_state.sel_local, session_state.sel_group, session_state.dtss_goal,
session_state.max_part_number, session_state.minimum_cost_or_pvp
]
sel_parameters_desc = [
'sel_local', 'sel_group', 'dtss_goal', 'max_part_number',
'minimum_cost_or_pvp'
]
'Model_Code': 'Modelo',
'Colour_Ext': 'Cor Exterior',
'Colour_Int': 'Cor Interior',
'Motor_Desc': 'Motorização',
'Quantity': 'Quantidade',
}
hide_menu_style = """
<style>
#MainMenu {visibility: hidden;}
</style>
"""
st.markdown(hide_menu_style, unsafe_allow_html=True)
session_state = sessionstate.get(overwrite_button_pressed=0,
save_button_pressed_flag=0,
locals='-',
model='')
def main():
current_date, _ = level_1_e_deployment.time_tags(format_date='%Y%m%d')
data = get_data(options_file)
# saved_suggestions_dict, saved_suggestions_df = get_suggestions_dict(options_file)
parameters_values, parameter_restriction_vectors = [], []
max_number_of_cars_sold = max(
data[column_translate['Number_Cars_Sold_Local_Fase2_Level_1']])
sel_locals = st.sidebar.multiselect(
'Concessões:',
import modules.level_1_a_data_acquisition as level_1_a_data_acquisition
import modules.SessionState as SessionState
import modules.level_1_e_deployment as level_1_e_deployment
from modules.level_0_performance_report import log_record, error_upload
from plotly import graph_objs as go
st.set_page_config(page_title='Correspondência de Gamas - Importador')
hide_menu_style = """
<style>
#MainMenu {visibility: hidden;}
</style>
"""
st.markdown(hide_menu_style, unsafe_allow_html=True)
session_state = SessionState.get(run_id=0, sel_brand='-', sel_model='-', draws_gama_morta=pd.DataFrame(), high_confidence_matches=pd.DataFrame(), not_high_confidence_matches=pd.DataFrame(), sel_df='-', df_sim=pd.DataFrame(), sel_table='-', validate_button_pressed=0, unmatched_data_filtered=pd.DataFrame())
"""
# Correspondência Gamas - Importador
Correspondência entre Gamas Mortas e Vivas
"""
url_hyperlink = '''
<a href= "{}" > <p style="text-align:right"> Manual de Utilizador </p></a>
'''.format(options_file.documentation_url_gamas_match_app)
st.markdown(url_hyperlink, unsafe_allow_html=True)
def main():
data = get_data(options_file)
unmatched_data = get_data_non_cached(options_file, 0)
import streamlit as st
import pandas as pd
import re
from datetime import datetime
from modules import SessionState
from modules.decorate import (html_decorate_text, tags_underlining,
bolded_tagged_sentenced, html_decorate_tag_list)
from modules.levenstein_search import levenshtein_extraction
from modules.mutimodule_functions import create_highlighted_markdown_text
from modules.in_out import (load_language, load_parameters,
load_report_and_classification)
from modules.transformations import (update_classified_dataset, extract_info,
crisis_type_correspondance,
defaut_value_listing)
state = SessionState.get(key=0)
# FUNCTION DEFINITIONS
def extract_defaut_values(selected_patient, classified_dataset):
# Extract previously input fields
defaut_values_df = classified_dataset[classified_dataset["Patient_name"] ==
selected_patient]
default_epilepsy_type, default_tags, default_laterality, default_thesaurus, default_free_notes = defaut_value_listing(
defaut_values_df)
return default_epilepsy_type, default_tags, default_laterality, default_thesaurus, default_free_notes
def update_last_patient_classified(last_patient_classified_df,
selected_patient):
from traceback import format_exc
base_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', ''))
sys.path.insert(1, base_path)
import level_2_pa_servicedesk_2244_options as options_file
import modules.level_1_a_data_acquisition as level_1_a_data_acquisition
import modules.level_1_e_deployment as level_1_e_deployment
from modules.level_0_performance_report import log_record, error_upload
import modules.SessionState as SessionState
from plotly import graph_objs as go
st.set_page_config(page_title='Classificação de Pedidos - Service Desk Rigor', layout="wide")
st.markdown("<h1 style='text-align: center;'>Classificação Pedidos Service Desk</h1>", unsafe_allow_html=True)
st.markdown("<h3 style='text-align: center;'>Classificação Manual de Pedidos do Service Desk</h3>", unsafe_allow_html=True)
session_state = SessionState.get(run_id=0, save_button_pressed_flag=0, overwrite_button_pressed_flag=0, update_final_table_button_pressed_flag=0, first_run=1)
truncate_query = '''
DELETE
FROM [BI_RCG].[dbo].[{}]
WHERE Request_Num = '{}'
'''
# Updates BI_SDK_Fact_Requests_Month_Detail with the new labels from BI_SDK_Fact_DW_Requests_Manual_Classification
update_query = '''
UPDATE dbo.{}
SET Label = Class.Label
FROM dbo.{} AS Fact
INNER JOIN {} AS Class ON Class.Request_Num = Fact.Request_Num
'''
st.markdown(url_hyperlink, unsafe_allow_html=True)
placeholder_dw_date = st.empty()
placeholder_sales_plan_date = st.empty()
placeholder_proposal_date = st.empty()
placeholder_margins_date = st.empty()
session_state = SessionState.get(
first_run_flag=0,
run_id=0,
run_id_scores=0,
save_button_pressed_flag=0,
model='',
brand='',
daysinstock_score_weight=score_weights[
'Avg_DaysInStock_Global_normalized'],
sel_margin_score_weight=score_weights['TotalGrossMarginPerc_normalized'],
sel_margin_ratio_score_weight=score_weights['MarginRatio_normalized'],
sel_qty_sold_score_weight=score_weights['Sum_Qty_CHS_normalized'],
sel_proposals_score_weight=score_weights['Proposals_VDC_normalized'],
sel_oc_stock_diff_score_weight=score_weights['Stock_OC_Diff_normalized'],
sel_co2_nedc_score_weight=score_weights['NEDC_normalized'],
sel_configurator_count_score_weight=score_weights[
'Configurator_Count_normalized'])
temp_cols = [
'Avg_DaysInStock_Global', 'Avg_DaysInStock_Global_normalized',
'#Veículos Vendidos', 'Sum_Qty_CHS_normalized', 'Proposals_VDC',
'Proposals_VDC_normalized', 'Margin_HP', 'TotalGrossMarginPerc',
'TotalGrossMarginPerc_normalized', 'MarginRatio', 'MarginRatio_normalized',
'OC', 'Stock_VDC', 'Stock_OC_Diff', 'Stock_OC_Diff_normalized', 'NEDC',
st.markdown("<h1 style='text-align: center;'>Aplicação de Apoio à Classificação de Famílias de Peças - DGO</h1>", unsafe_allow_html=True)
url_hyperlink = '''
<a href= "{}" > <p style="text-align:right"> Manual de Utilizador </p></a>
'''.format(options_file.documentation_url_app)
st.markdown(url_hyperlink, unsafe_allow_html=True)
hide_menu_style = """
<style>
#MainMenu {visibility: hidden;}
</style>
"""
st.markdown(hide_menu_style, unsafe_allow_html=True)
session_state = SessionState.get(sel_all_refs_flag=True, sel_family_desc='-', run_id=0, sel_model_class='-', data_filtered_sel=pd.DataFrame(), data_filtered_sim=pd.DataFrame(), sel_text='', sel_text_option='', data_text_filtered_sel=pd.DataFrame(), data_text_filtered_sim=pd.DataFrame(), data=pd.DataFrame(columns=['Part_Ref', 'Part_Description', 'Part_Cost', 'Part_PVP', 'Product_Group_DW_desc', 'Classification_desc', 'Classification_Prob']))
def main():
df_product_group = get_data_product_group_sql(options_file.others_families_dict, options_file)
cm_family_lvl_1 = get_data_sql(options_file, options_file.sql_info['database_final'], options_file.sql_info['matrix_lvl_1'])
cm_family_lvl_2 = get_data_sql(options_file, options_file.sql_info['database_final'], options_file.sql_info['matrix_lvl_2'])
cm_family_dict_lvl_1 = cm_replacements(cm_family_lvl_1)
cm_family_dict_lvl_2 = cm_replacements(cm_family_lvl_2)
family_dict_sorted = family_dict_sorting(cm_family_dict_lvl_1, cm_family_dict_lvl_2)
st.sidebar.title('Objetivo:')
sel_page = st.sidebar.radio('', ['Análise de Classificações', 'Correções às Famílias Atuais', 'Exportação de Classificações'], index=0)
if sel_page == 'Correções às Famílias Atuais':
data_original = get_dataset_sql(options_file.others_families_dict, options_file, options_file.classified_app_query)