Spaces:
Running
Running
James McCool
commited on
Commit
·
b647ce4
1
Parent(s):
6a6dae7
Added lineups page
Browse files
app.py
CHANGED
@@ -36,15 +36,22 @@ def init_conn():
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"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
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"client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/gspread-connection%40sheets-api-connect-378620.iam.gserviceaccount.com"
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}
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NBA_Data = st.secrets['NBA_Data']
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gc = gspread.service_account_from_dict(credentials)
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gc2 = gspread.service_account_from_dict(credentials2)
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return gc, gc2, NBA_Data
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gcservice_account, gcservice_account2, NBA_Data = init_conn()
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@st.cache_data(ttl=300)
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def load_overall_stats():
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@@ -102,10 +109,41 @@ def load_overall_stats():
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return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
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def convert_df_to_csv(df):
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return df.to_csv().encode('utf-8')
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dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
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t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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tab1, tab2 = st.tabs(['Range of Outcomes', 'Uploads and Info'])
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@@ -117,11 +155,13 @@ with tab1:
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with col1:
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st.info(t_stamp)
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if st.button("Load/Reset Data", key='reset1'):
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site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
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if site_var2 == 'Draftkings':
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site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
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@@ -167,17 +207,69 @@ with tab1:
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)
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with tab2:
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col1, col2 = st.columns([1, 5])
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with col1:
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with col2:
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if
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"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
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"client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/gspread-connection%40sheets-api-connect-378620.iam.gserviceaccount.com"
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}
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uri = st.secrets['mongo_uri']
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client = pymongo.MongoClient(uri, retryWrites=True, serverSelectionTimeoutMS=500000)
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db = client["NBA_DFS"]
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NBA_Data = st.secrets['NBA_Data']
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gc = gspread.service_account_from_dict(credentials)
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gc2 = gspread.service_account_from_dict(credentials2)
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return gc, gc2, db, NBA_Data
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gcservice_account, gcservice_account2, db, NBA_Data = init_conn()
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dk_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']
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fd_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']
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@st.cache_data(ttl=300)
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def load_overall_stats():
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return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
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@st.cache_data(ttl = 300)
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def init_DK_lineups():
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collection = db["DK_NBA_seed_frame"]
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cursor = collection.find()
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raw_display = pd.DataFrame(list(cursor))
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raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
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DK_seed = raw_display.head(10000).to_numpy()
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return DK_seed
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@st.cache_data(ttl = 300)
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def init_FD_lineups():
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collection = db["FD_NBA_seed_frame"]
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cursor = collection.find()
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raw_display = pd.DataFrame(list(cursor))
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raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
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FD_seed = raw_display.head(10000).to_numpy()
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return FD_seed
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def convert_df_to_csv(df):
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return df.to_csv().encode('utf-8')
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@st.cache_data
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def convert_df(array):
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array = pd.DataFrame(array, columns=column_names)
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return array.to_csv().encode('utf-8')
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dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
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dk_lineups = init_DK_lineups()
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fd_lineups = init_FD_lineups()
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t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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tab1, tab2 = st.tabs(['Range of Outcomes', 'Uploads and Info'])
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with col1:
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st.info(t_stamp)
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if st.button("Load/Reset Data", key='reset1'):
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st.cache_data.clear()
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dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
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dk_lineups = init_DK_lineups()
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fd_lineups = init_FD_lineups()
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t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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for key in st.session_state.keys():
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del st.session_state[key]
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site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
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if site_var2 == 'Draftkings':
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site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
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)
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with tab2:
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col1, col2 = st.columns([1, 7])
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with col1:
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if st.button("Load/Reset Data", key='reset1'):
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st.cache_data.clear()
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dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
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dk_lineups = init_DK_lineups()
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fd_lineups = init_FD_lineups()
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t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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for key in st.session_state.keys():
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del st.session_state[key]
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slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Just the Main Slate'))
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site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
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if site_var1 == 'Draftkings':
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raw_baselines = dk_raw
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column_names = dk_columns
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player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
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if player_var1 == 'Specific Teams':
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player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
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elif player_var1 == 'Full Slate':
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player_var2 = dk_raw.Player.values.tolist()
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elif site_var1 == 'Fanduel':
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raw_baselines = fd_raw
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column_names = fd_columns
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player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
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if player_var1 == 'Specific Teams':
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player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
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elif player_var1 == 'Full Slate':
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player_var2 = dk_raw.Player.values.tolist()
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if st.button("Prepare data export", key='data_export'):
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data_export = st.session_state.working_seed.copy()
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st.download_button(
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label="Export optimals set",
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data=convert_df(data_export),
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file_name='NBA_optimals_export.csv',
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mime='text/csv',
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)
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with col2:
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if st.button("Load Lineups", key='load_data'):
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if site_var1 == 'Draftkings':
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if 'working_seed' in st.session_state:
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st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 9], player_var2)]
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st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
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elif 'working_seed' not in st.session_state:
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st.session_state.working_seed = dk_lineups.copy()
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st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 9], player_var2)]
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st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
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elif site_var1 == 'Fanduel':
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if 'working_seed' in st.session_state:
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st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 10], player_var2)]
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st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
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elif 'working_seed' not in st.session_state:
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st.session_state.working_seed = fd_lineups.copy()
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st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 10], player_var2)]
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st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
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with st.container():
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if 'data_export_display' in st.session_state:
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st.dataframe(st.session_state.data_export_display.style.format(precision=2), use_container_width = True)
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