4d8d5b4e6a
- Created a new Blueprint for main routes in `routes/__init__.py`. - Implemented inventory listing and item management in `routes/inventory.py`. - Added user listing and detail views in `routes/user.py`. - Developed worklog listing and entry views in `routes/worklog.py`. - Introduced search functionality across inventory, users, and worklogs in `routes/search.py`. - Established settings management for brands, items, rooms, and functions in `routes/settings.py`. - Enhanced helper functions for rendering headers and managing data in `routes/helpers.py`. - Updated index route to display active worklogs and inventory conditions in `routes/index.py`.
86 lines
No EOL
2.4 KiB
Python
86 lines
No EOL
2.4 KiB
Python
from flask import render_template
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import pandas as pd
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from . import main
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from .helpers import worklog_headers
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from .. import db
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from ..models import WorkLog, Inventory
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from ..utils.load import eager_load_worklog_relationships, eager_load_inventory_relationships
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@main.route("/")
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def index():
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worklog_query = eager_load_worklog_relationships(
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db.session.query(WorkLog)
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).filter(
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(WorkLog.complete == False)
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)
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active_worklogs = worklog_query.all()
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active_count = len(active_worklogs)
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active_worklog_headers = {
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k: v for k, v in worklog_headers.items()
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if k not in ['End Time', 'Quick Analysis?', 'Complete?', 'Follow Up?']
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}
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inventory_query = eager_load_inventory_relationships(
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db.session.query(Inventory)
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)
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results = inventory_query.all()
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data = [{
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'id': item.id,
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'condition': item.condition
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} for item in results]
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df = pd.DataFrame(data)
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# Count items per condition
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expected_conditions = [
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'Deployed','Inoperable', 'Partially Inoperable',
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'Unverified', 'Working'
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]
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print(df)
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if 'condition' in df.columns:
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pivot = df['condition'].value_counts().reindex(expected_conditions, fill_value=0)
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else:
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pivot = pd.Series([0] * len(expected_conditions), index=expected_conditions)
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# Convert pandas/numpy int64s to plain old Python ints
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pivot = pivot.astype(int)
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labels = list(pivot.index)
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data = [int(x) for x in pivot.values]
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datasets = [{
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'type': 'pie',
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'labels': labels,
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'values': data,
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'name': 'Inventory Conditions'
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}]
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active_worklog_rows = []
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for log in active_worklogs:
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# Create a dictionary of {column name: cell dict}
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cells_by_key = {k: fn(log) for k, fn in worklog_headers.items()}
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# Use original, full header set for logic
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highlight = cells_by_key.get("Follow Up?", {}).get("highlight", False)
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# Use only filtered headers — and in exact order
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cells = [cells_by_key[k] for k in active_worklog_headers]
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active_worklog_rows.append({
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"id": log.id,
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"cells": cells,
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"highlight": highlight
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})
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return render_template(
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"index.html",
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active_count=active_count,
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active_worklog_headers=active_worklog_headers,
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active_worklog_rows=active_worklog_rows,
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labels=labels,
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datasets=datasets
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) |