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Merged in feature/streamlit_hardcoding_test (pull request #197)

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Feature/streamlit hardcoding test

Approved-by: Umang Mistry
This commit is contained in:
Michael McGuinness
2024-09-27 14:33:58 +00:00
parent 5d566a098a bff3fa801c
commit ba39f0ed1f
3 changed files with 55 additions and 51 deletions
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streamlit/interface_0.py
+4 -4
View File
@@ -78,17 +78,17 @@ try:
util.setup_page(REDIRECT_URI)
except Exception as e:
st.write(f"SSO Failed = {e}")
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'}
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'} # RECOMMENDATION - Remove Line after development.
try:
c1.write(f"User: **{st.session_state.user_info['displayName']}**")
user_mail = st.session_state.user_info['mail']
except KeyError as e:
except KeyError as e: # RECOMMENDATION - Not Working as Expected. Unreachable Code because the above Exception handles everything
st.write("Session Expired.")
auth_url = security.get_auth_url(REDIRECT_URI)
st.markdown(f"<a href='{auth_url}' target='_self'>Sign In</a>", unsafe_allow_html=True)
st.stop()
s3_client = boto3.client('s3',
s3_client = boto3.client('s3', # RECOMMENDATION - We can make use of AWS Access Key for enabling this in local testing. Will help a lot.
region_name="us-east-2",
)
@@ -190,7 +190,7 @@ with buttons[1]:
st.session_state.landing_zone = 'contracts-landing-zone'
# RECOMMENDATION - Rethink about how to best manage cache
# @st.cache_data
# def convert_df(df):
# return df.to_csv(index=False).encode('utf-8')
streamlit/interface_1.py
+1 -1
View File
@@ -49,7 +49,7 @@ try:
util.setup_page(REDIRECT_URI)
except:
st.write("SSO Failed")
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'}
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'} # RECOMMENDATION - Remove after dev phase
try:
c1.write(f"User: **{st.session_state.user_info['displayName']}**")
user_mail = st.session_state.user_info['mail']
streamlit/interface_2.py
+50 -46
View File
@@ -28,6 +28,7 @@ from util import logger
(REDIRECT_URI, create_batch_url, doczy_pipeline) = util.load_page_details(2)
user_list = USER_LIST
st.set_page_config(layout = "wide")
# Sidebar contents
with st.sidebar:
@@ -57,10 +58,10 @@ st.markdown(hide_img_fs, unsafe_allow_html=True)
_,c1= st.columns([5,1])
try:
util.setup_page(REDIRECT_URI)
util.setup_page(REDIRECT_URI) # RECOMMENDATION - Not secure enough
except:
st.write("SSO Failed")
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'}
st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'} # RECOMMENDATION - Remove after dev phase
try:
c1.write(f"User: **{st.session_state.user_info['displayName']}**")
user_mail = st.session_state.user_info['mail']
@@ -79,11 +80,11 @@ except:
st.write("Conn failed, unable to fetch data from training data table in Snowflake")
try:
query = 'select * from "PROMPT_CONFIG"'
query = 'select * from "PROMPT_CONFIG"' # RECOMMENDATION - Move query somewhere else
cur.execute(query)
fields = pd.DataFrame.from_records(iter(cur), columns=[x[0] for x in cur.description])
fields.rename(columns={'FIELD_DESC': 'Field Name'}, inplace = True)
fields.rename(columns={'FIELD_DESC': 'Field Name'}, inplace = True) # RECOMMENDATION - Package into less hardcoded function or handle in DB
fields.rename(columns={'PROMPT': 'Interrogation Question?'}, inplace = True)
fields.rename(columns={'GROUP_ID': 'PRIORITY'}, inplace = True)
fields.rename(columns={'FIELD_NAME': 'SF_DB_COL_NAME'}, inplace = True)
@@ -147,49 +148,52 @@ if client:
with field_row[0]:
st.write("**Field Group**")
with field_row[1]:
field_group = st.selectbox('Field Group',('Unique Key', 'Pricing Before Carveouts', 'Contract Related'),
label_visibility = "collapsed", index = None)
# field_group = st.selectbox('Field Group',('Unique Key', 'Contract Related', 'Pricing Before Carveouts - I'
# , 'Pricing Before Carveouts - II', 'Carveout Indicator, Code Type and Code #s - I'
# , 'Carveout Indicator, Code Type and Code #s - II', 'Carveout Indicator, Code Type and Code #s - III'
# , 'Optimize Carving Indic.', 'Carveout Method - I', 'Carveout Method - II', 'Provider'
# , 'Timeline'), label_visibility = "collapsed", index = None)
field_group = st.selectbox('Field Group',('Unique Key', 'Contract Related', 'Pricing Before Carveouts - I' # RECOMMENDATION - Get from a separate list or snowflake
, 'Pricing Before Carveouts - II', 'Carveout Indicator, Code Type and Code #s - I'
, 'Carveout Indicator, Code Type and Code #s - II', 'Carveout Indicator, Code Type and Code #s - III'
, 'Optimize Carving Indic.', 'Carveout Method - I', 'Carveout Method - II', 'Provider'
, 'Timeline'), label_visibility = "collapsed")
# if field_group == 'Unique Key':
# fields = fields[fields['PRIORITY'] == 'A']
# elif field_group == 'Contract Related':
# fields = fields[fields['PRIORITY'] == 'C']
# elif field_group == 'Pricing Before Carveouts - I':
# fields = fields[fields['PRIORITY'] == 'B']
# fields = np.array_split(fields, 2)[0]
# elif field_group == 'Pricing Before Carveouts - II':
# fields = fields[fields['PRIORITY'] == 'B']
# fields = np.array_split(fields, 2)[1]
# elif field_group == 'Carveout Indicator, Code Type and Code #s - I':
# fields = fields[fields['PRIORITY'] == 'F']
# fields = np.array_split(fields, 3)[0]
# elif field_group == 'Carveout Indicator, Code Type and Code #s - II':
# fields = fields[fields['PRIORITY'] == 'F']
# fields = np.array_split(fields, 3)[1]
# elif field_group == 'Carveout Indicator, Code Type and Code #s - III':
# fields = fields[fields['PRIORITY'] == 'F']
# fields = np.array_split(fields, 3)[2]
# elif field_group == 'Carveout Methodology - I':
# fields = fields[fields['PRIORITY'] == 'G']
# fields = np.array_split(fields, 4)[0]
# elif field_group == 'Carveout Methodology - II':
# fields = fields[fields['PRIORITY'] == 'G']
# fields = np.array_split(fields, 4)[1]
# elif field_group == 'Carveout Method - III':
# fields = fields[fields['PRIORITY'] == 'G']
# fields = np.array_split(fields, 4)[2]
# elif field_group == 'Carveout Method - IV':
# fields = fields[fields['PRIORITY'] == 'G']
# fields = np.array_split(fields, 4)[3]
# elif field_group == 'Provider':
# fields = fields[fields['PRIORITY'] == 'D']
# elif field_group == 'Timeline':
# fields = fields[fields['PRIORITY'] == 'E']
if field_group == 'Unique Key': # RECOMMENDATION - Use a Dictionary for this mapping
fields = fields[fields['PRIORITY'] == 'A']
elif field_group == 'Contract Related':
fields = fields[fields['PRIORITY'] == 'C']
elif field_group == 'Pricing Before Carveouts - I':
fields = fields[fields['PRIORITY'] == 'B']
fields = np.array_split(fields, 2)[0]
elif field_group == 'Pricing Before Carveouts - II':
fields = fields[fields['PRIORITY'] == 'B']
fields = np.array_split(fields, 2)[1]
elif field_group == 'Carveout Indicator, Code Type and Code #s - I':
fields = fields[fields['PRIORITY'] == 'F']
fields = np.array_split(fields, 3)[0]
elif field_group == 'Carveout Indicator, Code Type and Code #s - II':
fields = fields[fields['PRIORITY'] == 'F']
fields = np.array_split(fields, 3)[1]
elif field_group == 'Carveout Indicator, Code Type and Code #s - III':
fields = fields[fields['PRIORITY'] == 'F']
fields = np.array_split(fields, 3)[2]
elif field_group == 'Carveout Methodology - I':
fields = fields[fields['PRIORITY'] == 'G']
fields = np.array_split(fields, 4)[0]
elif field_group == 'Carveout Methodology - II':
fields = fields[fields['PRIORITY'] == 'G']
fields = np.array_split(fields, 4)[1]
elif field_group == 'Carveout Method - III':
fields = fields[fields['PRIORITY'] == 'G']
fields = np.array_split(fields, 4)[2]
elif field_group == 'Carveout Method - IV':
fields = fields[fields['PRIORITY'] == 'G']
fields = np.array_split(fields, 4)[3]
elif field_group == 'Provider':
fields = fields[fields['PRIORITY'] == 'D']
elif field_group == 'Timeline':
fields = fields[fields['PRIORITY'] == 'E']
if st.button("Show Results"):
query = 'select * from "DOCZY_PIPELINE_RAW_OUTPUT"' # RECOMMENDATION - Move query somewhere else
cur.execute(query)
df2 = pd.DataFrame.from_records(iter(cur), columns=[x[0] for x in cur.description])
button_cols = st.columns([1,2,6])
with button_cols[0]: