Total
{sprint_data['total_points']:.1f}
Done
{sprint_data['completed_points']:.1f}
In Progress
{sprint_data['in_progress_points']:.1f}
Complete
{(
sprint_data['completed_points'] / sprint_data['total_points'] * 100
if sprint_data['total_points'] > 0 else 0
):.1f}%
"""
st.markdown(metrics_html, unsafe_allow_html=True)
st.progress(
sprint_data['completed_points'] / sprint_data['total_points']
if sprint_data['total_points'] > 0 else 0
)
def show_task_creation_section(filtered_df, environment):
"""Display the task creation section with detailed functional area mapping information."""
if "Functional area" in filtered_df.columns and len(filtered_df) > 0:
functional_areas = filtered_df["Functional area"].unique().tolist()
functional_area = functional_areas[0] if functional_areas else None
logger.debug(f"Found functional areas: {functional_areas}")
# Get project metadata to access allowed values
metadata = get_project_metadata("RS")
if metadata:
# Create expandable section for field structure
with st.expander("Functional Area Field Structure", expanded=False):
func_field = metadata['all_fields'].get('customfield_13100', {})
if func_field and 'allowedValues' in func_field:
st.write("Available parent-child mappings:")
for parent in func_field['allowedValues']:
if isinstance(parent, dict):
parent_value = parent.get('value', 'Unknown')
st.markdown(f"**Parent: {parent_value}**")
if 'cascadingOptions' in parent:
child_values = [child.get('value') for child in parent['cascadingOptions'] if child.get('value')]
st.write("Child options:")
for child in sorted(child_values):
st.write(f" • {child}")
st.write("")
# Display current functional area and mapping attempt
st.subheader("Functional Area Mapping")
col1, col2 = st.columns(2)
with col1:
st.markdown("**Input Functional Area:**")
st.info(functional_area)
st.markdown("**Split Parts:**")
parts = functional_area.split(' - ')
for i, part in enumerate(parts, 1):
st.write(f"{i}. {part}")
with col2:
# Try to map the functional area
parent, child = map_functional_area(functional_area, metadata)
st.markdown("**Mapped Values:**")
st.success(f"Parent: {parent}")
st.success(f"Child: {child}")
# Show normalized form
st.markdown("**Normalized Form:**")
norm_area = functional_area.lower().replace(' ', '-')
st.info(norm_area)
# Add warning if using default mapping
if parent == "R&I" and child == "Data Exchange" and functional_area.lower() != "data exchange":
st.warning("""
⚠️ Using default mapping (R&I/Data Exchange). This might not be the best match.
Please check the 'Functional Area Field Structure' above for available values.
""")
else:
logger.warning("No functional area found in data")
st.warning("No functional area information found in the data")
# Create task button
if st.button("Create Task", key="create_task_button"):
handle_task_button_click(filtered_df, environment)
def multiple_main():
# Initialize session state variables
if 'current_page' not in st.session_state:
st.session_state.current_page = "upload"
if 'task_df' not in st.session_state:
st.session_state.task_df = None
if 'selected_files' not in st.session_state:
st.session_state.selected_files = []
if 'uploaded_files' not in st.session_state:
st.session_state.uploaded_files = []
if 'filtered_scenarios_df' not in st.session_state:
st.session_state.filtered_scenarios_df = None
if 'sprint_data_initialized' not in st.session_state:
st.session_state.sprint_data_initialized = False
st.title("Multiple File Analysis")
# Initialize session state for uploaded data
if 'uploaded_data' not in st.session_state:
st.session_state.uploaded_data = None
if 'last_refresh' not in st.session_state:
st.session_state.last_refresh = None
# Check if we're in task creation mode
if st.session_state.current_page == "create_task" and st.session_state.task_df is not None:
# Add a back button
if st.button("⬅️ Back to Analysis"):
st.session_state.current_page = "analysis"
st.rerun()
return
# Show task creation section
show_task_creation_section(st.session_state.task_df, st.session_state.task_environment)
return
# Main analysis page
uploaded_files = st.file_uploader("Upload CSV or Excel files",
type=['csv', 'xlsx'],
accept_multiple_files=True)
# Process uploaded files and store in session state
if uploaded_files:
all_data = []
for file in uploaded_files:
try:
df = preprocess_uploaded_file(file)
all_data.append(df)
except Exception as e:
st.error(f"Error processing {file.name}: {str(e)}")
if all_data:
# Store the processed data in session state
st.session_state.uploaded_data = all_data
# Use data from session state for analysis
if st.session_state.uploaded_data:
# Perform analysis for uploaded data
perform_analysis(st.session_state.uploaded_data)
# Get combined data for Jira integration
combined_df = pd.concat(st.session_state.uploaded_data, ignore_index=True)
else:
st.write("Please upload at least one file.")
if __name__ == "__main__":
st.set_page_config(layout="wide")
multiple_main()