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#initial imports
import streamlit as st
st.set_page_config(layout="wide")
import numpy as np
import pandas as pd
import time
from fuzzywuzzy import process
# Bring in numpy reqs
from numpy import nan as np_nan
from numpy import where as np_where
from numpy import random as np_random
from numpy import zeros as np_zeros
from numpy import array as np_array
from pandas import concat as pd_concat
from pandas import merge as pd_merge
from pandas import DataFrame
#bring in functions
from function_hold.NBA_functions import DK_NBA_ROO_Build, FD_NBA_ROO_Build
def load_file(upload):
if upload is not None:
try:
if upload.name.endswith('.csv'):
df = pd.read_csv(upload)
elif upload.name.endswith(('.xls', '.xlsx')):
df = pd.read_excel(upload)
else:
st.error('Please upload either a CSV or Excel file')
return None
export_df = df.copy()
return export_df, df
except Exception as e:
st.error(f'Error loading file: {str(e)}')
return None
return None
tab1, tab2 = st.tabs(["Data Load", "Manage Portfolio"])
with tab1:
if st.button('Clear data', key='reset1'):
st.session_state.clear()
sport_var = st.selectbox("Select Sport", ["NBA", "NFL", "MLB"])
st.subheader("Projections File")
if sport_var == "NBA":
st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'")
elif sport_var == "NFL":
st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'")
elif sport_var == "MLB":
st.info("upload a projections file that has Data oriented in the following format: 'Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'")
# Create two columns for the uploader and template button
upload_col, template_col = st.columns([3, 1])
with upload_col:
projections_file = st.file_uploader("Upload Projections File (CSV or Excel)", type=['csv', 'xlsx', 'xls'])
with template_col:
if sport_var == "NBA":
template_df = pd.DataFrame(columns=['Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'])
elif sport_var == "NFL":
template_df = pd.DataFrame(columns=['Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'])
elif sport_var == "MLB":
template_df = pd.DataFrame(columns=['Player', 'Team', 'Opp', 'Position', 'Salary', 'Median', 'Minutes', 'Own'])
# Add download button for template
st.download_button(
label="Template",
data=template_df.to_csv(index=False),
file_name="projections_template.csv",
mime="text/csv"
)
if projections_file:
export_projections, projections = load_file(projections_file)
if projections is not None:
st.success('Projections file loaded successfully!')
st.dataframe(projections)
with tab2:
if st.button('Clear data', key='reset2'):
st.session_state.clear()
site_var = st.selectbox("Select Site", ["Draftkings", "Fanduel"])
if projections_file:
if st.button('Build ROO'):
if sport_var == "NBA":
if site_var == "Draftkings":
disp_file = DK_NBA_ROO_Build(projections)
elif site_var == "Fanduel":
disp_file = FD_NBA_ROO_Build(projections)
elif sport_var == "NFL":
if site_var == "Draftkings":
disp_file = DK_NFL_ROO_Build(projections)
elif site_var == "Fanduel":
disp_file = FD_NFL_ROO_Build(projections)
elif sport_var == "MLB":
if site_var == "Draftkings":
disp_file = DK_MLB_ROO_Build(projections)
elif site_var == "Fanduel":
disp_file = FD_MLB_ROO_Build(projections)
st.dataframe(disp_file)
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