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@@ -20,12 +20,8 @@ from pptx.dml.color import RGBColor
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from pptx.enum.text import PP_ALIGN
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from pptx.enum.shapes import MSO_SHAPE
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-from data_loader import (
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- load_daily, load_weekly, load_monthly, load_date_range,
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- load_generic_excel,
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-)
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+from data_loader import load_generic_excel
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from metrics_calculator import (
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- calc_daily_metrics, calc_weekly_metrics, calc_monthly_metrics, generate_deep_insights,
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calc_generic_metrics, calc_generic_trend, calc_generic_distribution,
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calc_generic_ranking, generate_generic_insights,
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)
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@@ -892,6 +888,8 @@ def _add_goal_cards(slide, goals, start_y=Emu(1524000), fonts=None, colors=None)
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def _add_summary_text(slide, text, left=Emu(1016000), top=Emu(5435600), width=Emu(14224000), height=Emu(1270000), fonts=None, colors=None):
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+ colors = colors or {}
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+ C_TEXT = colors.get('text', RGBColor(0x33, 0x33, 0x33))
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box = slide.shapes.add_textbox(left, top, width, height)
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tf = box.text_frame
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tf.word_wrap = True
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@@ -900,276 +898,7 @@ def _add_summary_text(slide, text, left=Emu(1016000), top=Emu(5435600), width=Em
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p.font.size = Pt(12)
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p.font.color.rgb = C_TEXT
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p.font.name = '微软雅黑'
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- p.line_spacing = 1.3# ==============================================================================# STRUCTURED INSIGHT GENERATORS# ==============================================================================def _insight_trend_structured(trend_dates, trend_vals, metrics, period_name='近10天'):
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- colors = colors or {}
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- C_TEXT = colors.get('text', RGBColor(0x33, 0x33, 0x33))
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- """Generate structured multi-paragraph trend insight."""
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- items = []
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- if not trend_vals or len(trend_vals) < 2:
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- items.append({'title': '数据概览', 'content': f'{period_name}订单数据平稳，暂无明显波动。'})
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- return items
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-
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- peak = max(trend_vals)
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- peak_idx = trend_vals.index(peak)
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- low = min(trend_vals)
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- low_idx = trend_vals.index(low)
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- last = trend_vals[-1]
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- first = trend_vals[0]
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- total = sum(trend_vals)
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- avg = total / len(trend_vals)
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-
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- # Paragraph 1: Order scale
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- curr_orders = metrics.get('tracking_orders', last)
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- prev_orders = metrics.get('prev_tracking_orders', 0)
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- order_chg = _pct_val(curr_orders, prev_orders)
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- curr_qty = metrics.get('total_qty', 0)
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- prev_qty = metrics.get('prev_total_qty', 0)
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- qty_chg = _pct_val(curr_qty, prev_qty)
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- avg_size = metrics.get('avg_order_size', 0)
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- prev_avg_size = metrics.get('prev_avg_order_size', 0)
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-
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- scale_text = f'今日订单量{curr_orders}单'
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- if prev_orders > 0:
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- diff = curr_orders - prev_orders
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- scale_text += f'，较昨日{"增加" if diff >= 0 else "减少"}{abs(diff)}单'
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- if curr_qty > 0:
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- scale_text += f'，订单总数量{curr_qty:,}台'
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- if prev_qty > 0:
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- qdiff = curr_qty - prev_qty
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- scale_text += f'，较昨日{"增加" if qdiff >= 0 else "减少"}{abs(qdiff)}台'
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- if avg_size > 0:
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- scale_text += f'，单笔订单平均规模{avg_size:.0f}台'
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- if prev_avg_size > 0:
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- adiff = avg_size - prev_avg_size
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- if abs(adiff) >= 1:
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- scale_text += f'（{"上升" if adiff >= 0 else "下降"}{abs(adiff):.0f}台）'
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- items.append({'title': '订单规模分析', 'content': scale_text})
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-
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- # Paragraph 2: Peak fluctuation
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- peak_text = ''
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- if peak == last:
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- peak_text = f'今日达到峰值{peak}单，为{period_name}最高水平。'
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- elif low == last:
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- peak_text = f'今日回落至{last}单，为{period_name}最低水平。'
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- else:
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- peak_text = f'峰值出现在{trend_dates[peak_idx]}（{peak}单），低谷在{trend_dates[low_idx]}（{low}单）。'
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- # Describe recovery pattern
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- if len(trend_vals) >= 3:
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- recent = trend_vals[-3:]
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- if recent[-1] > recent[-2] and recent[-2] < recent[0]:
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- peak_text += f'连续回落后今日回升至{last}单，呈现反弹态势。'
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- elif recent[-1] < recent[-2]:
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- peak_text += f'近期呈回落趋势，需关注后续走势。'
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- items.append({'title': '峰值波动', 'content': peak_text})
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-
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- # Paragraph 3: Activity / update
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- updated = metrics.get('updated_orders', 0)
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- prev_updated = metrics.get('prev_updated_orders', 0)
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- if updated > 0 or prev_updated > 0:
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- act_text = f'今日进度更新{updated}单'
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- if prev_updated > 0:
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- udiff = updated - prev_updated
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- upct = _pct_val(updated, prev_updated)
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- act_text += f'，较昨日{"增加" if udiff >= 0 else "减少"}{abs(udiff)}单（{upct:+.1f}%）'
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- if abs(upct) > 20:
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- act_text += '，团队活跃度波动较大。' if abs(upct) > 30 else '，团队活跃度有所变化。'
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- else:
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- act_text += '，团队活跃度保持平稳。'
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- else:
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- act_text += '。'
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- items.append({'title': '活跃度分析', 'content': act_text})
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-
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- return items
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-
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-
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-def _insight_status_structured(status_dist, prev_status_dist=None):
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- """Generate structured status distribution insight."""
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- items = []
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- total = sum(status_dist.values())
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- if not total:
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- items.append({'title': '状态概览', 'content': '暂无订单状态数据。'})
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- return items
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-
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- max_status = max(status_dist.items(), key=lambda x: x[1])
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- max_pct = max_status[1] / total * 100
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-
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- # Production share (C+D)
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- prod = status_dist.get('已付订金待生产', 0) + status_dist.get('已生产待付尾款', 0)
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- prod_pct = prod / total * 100
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-
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- status_text = f'{max_status[0]}占比最高（{max_status[1]}单，{max_pct:.1f}%）'
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- if prod_pct > 0:
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- status_text += f'。生产端（已付订金+已生产）合计{prod}单（{prod_pct:.1f}%）'
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- if prod_pct > 30:
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- status_text += '，生产推进力度加大。'
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- else:
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- status_text += '。'
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- items.append({'title': '状态分布特征', 'content': status_text})
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-
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- # WoW change
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- if prev_status_dist:
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- changes = []
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- for name, curr in status_dist.items():
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- prev = prev_status_dist.get(name, 0)
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- if prev > 0:
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- chg = _pct_val(curr, prev)
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- if abs(chg) > 5:
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- changes.append(f'{name}{chg:+.1f}%')
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- if changes:
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- items.append({'title': '状态变化（vs 昨日）', 'content': ' | '.join(changes[:4])})
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-
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- return items
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-
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-
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-def _insight_region_structured(region_dist):
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- """Generate structured regional insight with top countries."""
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- items = []
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- if not region_dist:
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- items.append({'title': '区域概览', 'content': '暂无区域分布数据。'})
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- return items
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-
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- sorted_regions = sorted(region_dist.items(), key=lambda x: -x[1]['qty'])
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- top3 = sorted_regions[:3]
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- total = sum(v['qty'] for v in region_dist.values())
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- top3_pct = sum(v['qty'] for _, v in top3) / total * 100 if total else 0
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-
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- top_names = [k for k, _ in top3]
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- items.append({'title': '核心市场', 'content': f'{"、".join(top_names)}三大核心市场合计占比{top3_pct:.1f}%，是海外订单的核心增长引擎。'})
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-
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- # Each region detail
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- for name, data in sorted_regions[:5]:
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- top_c = data.get('top_countries', [])
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- top_c_str = '/'.join([c['country'] for c in top_c[:3]]) if top_c else ''
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- change = data.get('change_pct', 0)
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- if change is None:
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- chg_str = ''
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- elif change > 0:
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- chg_str = f'（+{change:.1f}%）'
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- elif change < 0:
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- chg_str = f'（{change:.1f}%）'
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- else:
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- chg_str = ''
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- content = f'{data["pct"]:.1f}% | {data["qty"]:,}台'
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- if top_c_str:
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- content += f' | {top_c_str}为主力'
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- if change != 0:
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- content += f' {chg_str}'
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- if change < 0:
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- content += ' | 需关注'
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- items.append({'title': name, 'content': content})
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-
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- return items
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-
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-
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-def _insight_team_structured(team, total_qty=0, per_capita=0, countries_covered=0):
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- """Generate structured team performance insight."""
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- items = []
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- if not team:
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- items.append({'title': '团队概览', 'content': '暂无团队绩效数据。'})
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- return items
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-
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- n_members = len(team)
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- avg = per_capita or _safe_div(sum(v.get('orders', 0) for v in team.values()), n_members)
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- top = max(team.items(), key=lambda x: x[1].get('orders', 0))
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-
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- overview = f'团队共{n_members}人，'
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- if countries_covered:
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- overview += f'覆盖{countries_covered}国，'
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- overview += f'人均追踪{avg:.0f}单。'
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- items.append({'title': '团队概况', 'content': overview})
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-
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- # Top performers
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- sorted_team = sorted(team.items(), key=lambda x: -x[1].get('orders', 0))
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- for name, data in sorted_team[:2]:
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- orders = data.get('orders', 0)
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- qty = data.get('qty', 0)
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- comment = '增长主力' if orders > avg * 1.3 else '稳健跟进'
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- content = f'{name} {orders}单'
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- if qty:
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- content += f'/{qty:,}台'
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- content += f' - {comment}'
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- items.append({'title': '领跑者点评', 'content': content})
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-
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- # Find laggard
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- low = min(team.items(), key=lambda x: x[1].get('orders', 0))
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- if low[1].get('orders', 0) < avg * 0.7:
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- items.append({'title': '关注提醒', 'content': f'{low[0]}订单量低于团队均值，建议关注产能提升空间。'})
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-
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- return items
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-
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-
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-def _insight_stage_structured(stage_analysis, funnel):
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- """Generate structured monthly stage funnel insight."""
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- items = []
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- early = stage_analysis.get('early', {})
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- mid = stage_analysis.get('mid', {})
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- late = stage_analysis.get('late', {})
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-
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- a_b = early.get('orders', 0)
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- items.append({
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- 'title': '前期Pipeline充足',
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- 'content': f'合同拟定中(A) + 已锁定待付订金(B)共{a_b}单，占总量的{early.get("pct", 0):.1f}%，后续转化空间充足。'
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- })
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-
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- c_d = mid.get('orders', 0)
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- items.append({
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- 'title': '中期生产推进',
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- 'content': f'已付订金待生产(C) + 已生产待付尾款(D)共{c_d}单，占总量的{mid.get("pct", 0):.1f}%。'
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- })
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-
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- e_f = late.get('orders', 0)
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- items.append({
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- 'title': '后期交付待加速',
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- 'content': f'已付尾款待发运(E) + 已发运(F)仅{e_f}单，占总量的{late.get("pct", 0):.1f}%。'
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- })
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-
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- if early.get('pct', 0) > 40:
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- items.append({
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- 'title': '⚠ 风险提示',
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- 'content': f'近半数订单仍停留在合同拟定阶段，需关注A→B的转化效率，加速合同确认和订金回收。'
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- })
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-
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- return items
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-
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-
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-def _insight_top_countries_structured(top_countries_change, total_qty, top_n=6):
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- """Generate structured TOP countries insight."""
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- items = []
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- if not top_countries_change:
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- items.append({'title': '国家概览', 'content': '暂无国家分布数据。'})
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- return items
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-
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- sorted_items = sorted(top_countries_change.items(), key=lambda x: -x[1]['qty'])
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- top_list = sorted_items[:top_n]
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- total_top = sum(v['qty'] for _, v in top_list)
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- pct = total_top / total_qty * 100 if total_qty else 0
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-
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- items.append({'title': '集中度分析', 'content': f'Top {top_n}目的国合计覆盖{total_top:,}台，占总量的{pct:.1f}%，重点市场集中度高。'})
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-
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- for i, (country, data) in enumerate(top_list, 1):
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- chg = data.get('change_pct', 0)
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- comment = ''
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- if chg is None:
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- comment = '新增市场，潜力可期'
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- chg_str = ''
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- elif chg > 30:
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- comment = '本周增长最快市场之一'
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- chg_str = f'（{chg:+.1f}%）'
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- elif chg > 10:
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- comment = '持续增长'
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- chg_str = f'（{chg:+.1f}%）'
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- elif chg < -10:
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- comment = '虽有下滑但仍高位' if data['qty'] > total_qty * 0.05 else '需关注'
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- chg_str = f'（{chg:.1f}%）'
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- elif chg < 0:
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- comment = '小幅回落'
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- chg_str = f'（{chg:.1f}%）'
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- else:
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- comment = 'steady增长' if i <= 3 else '新兴市场，潜力可期'
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- chg_str = f'（{chg:+.1f}%）' if chg != 0 else ''
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- items.append({'title': f'{i}. {country} {data["qty"]:,}台{chg_str}', 'content': comment})
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-
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- return items
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+ p.line_spacing = 1.3
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# ==============================================================================
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@@ -2246,16 +1975,7 @@ def _build_forecast_page(prs, config, df, profile, metrics, colors, content_top,
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series_name='预测/目标值', color=colors.get('accent', C_ACCENT),
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category_axis_title='预测项', value_axis_title='数值')
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- is_monthly = (
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- getattr(config, 'period_type', None) == PeriodType.MONTHLY or
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- str(getattr(config, 'period_type', '')).lower() == 'monthly'
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- )
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- has_order_monthly_plan = bool(metrics.get('next_month_goals') or metrics.get('forecast_next'))
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- if is_monthly and has_order_monthly_plan:
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- insight_items = generate_deep_insights('monthly', 'monthly_plan', metrics)
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- else:
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- insight_items = []
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- insight_items = _generic_forecast_insights(page_def, forecast_items, profile, metrics) if not insight_items else insight_items
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+ insight_items = _generic_forecast_insights(page_def, forecast_items, profile, metrics)
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insight_items = _ensure_min_insight_items(insight_items, profile, metrics, context_label='预测页')
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_add_structured_insight(slide, insight_items,
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Emu(text_zone.x), Emu(text_zone.y),
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@@ -2263,973 +1983,17 @@ def _build_forecast_page(prs, config, df, profile, metrics, colors, content_top,
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# ==============================================================================
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-# DAILY REPORT
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-# ==============================================================================
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-
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-def build_daily_report(data_file: str, date: datetime, output_path: str,
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- department='海外事业部', source='海外订单日报系统'):
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- master_path = get_master_template('daily')
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- prs = Presentation(master_path)
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- content_top = _detect_content_top(prs.slides[1])
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-
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- df = load_daily(data_file, date)
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- prev_date = date - timedelta(days=1)
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- try:
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- prev_df = load_daily(data_file, prev_date)
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- except Exception:
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- prev_df = None
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-
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- metrics = calc_daily_metrics(df, prev_df)
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- prev_metrics = calc_daily_metrics(prev_df, None) if prev_df is not None else {}
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- date_str = date.strftime('%Y年%m月%d日')
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- period_str = date.strftime('%Y年%m月%d日')
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-
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- # ---- Page 1: Cover ----
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- slide = _duplicate_slide(prs, prs.slides[0])
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- _replace_all_placeholders(slide, {
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- '{report_title}': '海外订单数据日报',
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- '{report_type}': '数据日报',
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- '{date}': date_str,
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- '{department}': department,
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- '{period}': period_str,
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- '{gen_time}': datetime.now().strftime('%Y-%m-%d %H:%M'),
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- }, fonts)
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- _add_footer_if_missing(slide, f'数据来源：{source} | 1/8', colors=colors)
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- cover_kpis = [
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- ('在跟订单', metrics['tracking_orders'], '单',
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- _pct_str(metrics['tracking_orders'], metrics.get('prev_tracking_orders', 0))),
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- ('订单总数量', f"{metrics['total_qty']:,}", '台',
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- _pct_str(metrics['total_qty'], metrics.get('prev_total_qty', 0))),
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- ('今日已更新', metrics['updated_orders'], '单',
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- _pct_str(metrics['updated_orders'], metrics.get('prev_updated_orders', 0))),
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- ('支持需求', metrics['support_requests'], '项', '需跨部门协调'),
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- ]
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- for i, (lbl, val, unit, chg) in enumerate(cover_kpis, 1):
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- _replace_placeholder(slide, f'{{kpi{i}_label}}', lbl)
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- _replace_placeholder(slide, f'{{kpi{i}_value}}', str(val))
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-
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- # ---- Page 2: KPI Overview ----
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- s2 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s2, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': '今日核心指标概览',
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- '{source}': source,
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- '{period}': '2/8',
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- '{page_num}': '',
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- })
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- kpis = [
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- {'label': '在跟订单总数', 'value': metrics['tracking_orders'], 'unit': '单',
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- 'change': _pct_str(metrics['tracking_orders'], metrics.get('prev_tracking_orders', 0)),
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- 'sub': '日均跟踪'},
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- {'label': '订单总数量', 'value': f"{metrics['total_qty']:,}", 'unit': '台',
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- 'change': _pct_str(metrics['total_qty'], metrics.get('prev_total_qty', 0)),
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- 'sub': '规模稳定'},
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- {'label': '今日已更新', 'value': metrics['updated_orders'], 'unit': '单',
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- 'change': _pct_str(metrics['updated_orders'], metrics.get('prev_updated_orders', 0)),
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- 'sub': '团队活跃'},
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- {'label': '下月预测交付', 'value': metrics['forecast_next'], 'unit': '台',
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- 'change': _pct_str(metrics['forecast_next'], metrics.get('prev_forecast_next', 0)),
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- 'sub': '交付预期'},
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- {'label': '支持需求总数', 'value': metrics['support_requests'], 'unit': '项',
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- 'change': '需跨部门协调', 'sub': '建议集中处理'},
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- {'label': '已发运订单', 'value': metrics['shipped_orders'], 'unit': '单',
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- 'change': f'共{metrics.get("shipped_orders", 0) * 8}台 | {metrics["shipped_orders"] - metrics.get("prev_shipped_orders", 0)}单 vs 昨日',
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- 'sub': '交付稳步推进'},
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- ]
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- _add_kpi_cards(s2, kpis, start_y=Emu(content_top))
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-
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- # ---- Page 3: 10-Day Trend ----
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- s3 = _duplicate_slide(prs, prs.slides[1])
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- trend_dates = []
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- trend_vals = []
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- for d_offset in range(-9, 1):
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- d = date + timedelta(days=d_offset)
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- try:
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- tdf = load_daily(data_file, d)
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- trend_dates.append(d.strftime('%m/%d'))
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- trend_vals.append(len(tdf))
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- except Exception:
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- pass
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-
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- # Generate conclusion title
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- trend_conclusion = '近10天订单趋势'
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- if len(trend_vals) >= 2:
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- if trend_vals[-1] > trend_vals[-2]:
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- trend_conclusion = '近10天订单趋势：订单规模回升'
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- elif trend_vals[-1] < trend_vals[-2]:
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- trend_conclusion = '近10天订单趋势：订单量继续回落'
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- peak = max(trend_vals)
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- if trend_vals[-1] == peak:
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- trend_conclusion = '近10天订单趋势：今日达到峰值'
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-
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- _replace_all_placeholders(s3, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': trend_conclusion,
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- '{source}': source,
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- '{period}': '3/8',
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- '{page_num}': '',
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- })
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- if len(trend_dates) >= 2:
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- add_column_chart(s3, trend_dates, trend_vals,
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- Emu(762000), Emu(content_top), Emu(8890000), Emu(5334000),
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- series_name='订单量', color=C_ACCENT,
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- category_axis_title='日期', value_axis_title='订单数')
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- insight_items = generate_deep_insights('daily', 'trend', metrics,
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- prev_metrics=prev_metrics,
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- trend_dates=trend_dates,
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- trend_vals=trend_vals)
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- _add_structured_insight(s3, insight_items,
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- Emu(9906000), Emu(content_top), Emu(4826000), Emu(5334000))
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-
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- # ---- Page 4: Status Distribution ----
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- s4 = _duplicate_slide(prs, prs.slides[1])
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- status_names = list(metrics['status_dist'].keys())
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- status_vals = list(metrics['status_dist'].values())
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- total_status = sum(status_vals)
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- prod_share = metrics.get('production_share', 0)
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- status_title = '订单状态分布'
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- if prod_share > 0:
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- status_title = f'订单状态分布：生产端占比提升至{prod_share:.1f}%'
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-
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- _replace_all_placeholders(s4, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': status_title,
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- '{source}': source,
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- '{period}': '4/8',
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- '{page_num}': '',
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- })
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- if status_names and total_status > 0:
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- # Left donut chart: 55% width
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- add_doughnut_chart(s4, status_names, status_vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- show_legend=True, show_data_labels=True, show_percent=True,
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- ring_ratio=0.6)
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- # Right side: status change + deep insights (no table to save space for dense text)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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-
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- prev_status = prev_metrics.get('status_dist', {})
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- # Status change text: "合同拟定中 -30.8% ↓ | 已付订金待生产 +55.6% ↑"
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- changes = []
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- for name, curr in metrics['status_dist'].items():
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- prev = prev_status.get(name, 0)
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- if prev > 0:
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- chg = _pct_val(curr, prev)
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- if chg is not None:
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- arrow = '↑' if chg >= 0 else '↓'
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- changes.append(f'{name} {_format_pct(chg)}{arrow}')
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- if changes:
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- change_text = ' | '.join(changes[:4])
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- _add_text_block(s4, '状态变化（vs 昨日）', change_text,
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- text_left, Emu(content_top), text_w, Emu(609600),
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- title_size=Pt(12), body_size=Pt(10))
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-
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- # Deep insight fills remaining right-side space
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- insight_items = generate_deep_insights('daily', 'status', metrics,
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- prev_status_dist=prev_status)
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- insight_top = Emu(int(content_top) + 685800)
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- insight_height = Emu(5334000 - 685800)
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- _add_structured_insight(s4, insight_items,
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- text_left, insight_top, text_w, insight_height, colors=colors)
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-
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- # ---- Page 5: Owner Distribution ----
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- s5 = _duplicate_slide(prs, prs.slides[1])
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- owner_names = list(metrics['owner_dist'].keys())[:8]
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- owner_vals = list(metrics['owner_dist'].values())[:8]
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- top_owner = owner_names[0] if owner_names else ''
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- second_owner = owner_names[1] if len(owner_names) > 1 else ''
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- owner_title = '负责人订单分布'
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- if top_owner and second_owner:
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- owner_title = f'负责人订单分布：{top_owner}、{second_owner}领跑'
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-
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- _replace_all_placeholders(s5, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': owner_title,
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- '{source}': source,
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- '{period}': '5/8',
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- '{page_num}': '',
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- })
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- if owner_names:
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_horizontal_bar_chart(s5, owner_names, owner_vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- series_name='订单笔数', color=C_ACCENT, reverse_order=True,
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- value_axis_title='订单笔数')
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- # Deep insight: owner distribution analysis
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- prev_owner_dist = prev_metrics.get('owner_dist', {}) if prev_metrics else {}
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- insight_items = generate_deep_insights('daily', 'owner', metrics,
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- prev_owner_dist=prev_owner_dist)
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- _add_structured_insight(s5, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # ---- Page 6: Country TOP8 ----
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- s6 = _duplicate_slide(prs, prs.slides[1])
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- countries = list(metrics['country_top8'].keys())[:8]
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- country_vals = list(metrics['country_top8'].values())[:8]
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- top_country = countries[0] if countries else ''
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- country_title = '目的国家TOP8'
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- if top_country:
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- country_title = f'目的国家TOP8：{top_country}订单量领先'
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-
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- _replace_all_placeholders(s6, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': country_title,
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- '{source}': source,
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- '{period}': '6/8',
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- '{page_num}': '',
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- })
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- if countries:
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_horizontal_bar_chart(s6, countries, country_vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- series_name='订单量(台)', color=C_ACCENT, reverse_order=True,
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- value_axis_title='订单量（台）')
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- # Deep insight: country top8 analysis
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- insight_items = generate_deep_insights('daily', 'country', metrics)
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- _add_structured_insight(s6, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # ---- Page 7: Support Analysis ----
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- s7 = _duplicate_slide(prs, prs.slides[1])
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- alerts = metrics['alerts']
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- alert_title = '异常告警'
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- if alerts:
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- severe = [a for a in alerts if a.get('level') == '严重']
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- if severe:
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- alert_title = f'异常告警：{severe[0]["title"]}'
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- else:
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- alert_title = f'异常告警：{alerts[0]["title"]}'
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-
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- _replace_all_placeholders(s7, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': alert_title,
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- '{source}': source,
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- '{period}': '7/8',
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- '{page_num}': '',
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- })
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-
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- # Unified left-chart + right-insight layout
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- sc = metrics.get('support_categories', {})
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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-
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- if sc:
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- sc_names = list(sc.keys())
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- sc_vals = list(sc.values())
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- add_doughnut_chart(s7, sc_names, sc_vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- show_legend=True, show_data_labels=True, show_percent=True,
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- ring_ratio=0.6)
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-
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- # Deep insight: alerts & support analysis
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- insight_items = generate_deep_insights('daily', 'alert', metrics)
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- _add_structured_insight(s7, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # ---- Page 8: Key Points ----
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- s8 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s8, {
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- '{report_title}': '海外订单数据日报',
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- '{date}': date_str,
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- '{page_title}': '明日工作重点',
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- '{source}': source,
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- '{period}': '8/8',
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- '{page_num}': '',
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- })
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-
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- # Left chart: overdue orders horizontal bar (or support categories fallback)
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- overdue = metrics.get('overdue_orders', [])
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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-
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- if overdue:
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- o_countries = [o['country'] for o in overdue[:8]]
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- o_days = [o['days'] for o in overdue[:8]]
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- add_horizontal_bar_chart(s8, o_countries, o_days,
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- series_name='超期天数', color=C_ORANGE, reverse_order=True,
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- value_axis_title='天数')
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- elif metrics.get('support_categories'):
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- sc = metrics['support_categories']
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- add_horizontal_bar_chart(s8, list(sc.keys()), list(sc.values()),
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- series_name='需求数', color=C_ACCENT, reverse_order=True,
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- value_axis_title='数量')
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-
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- # Deep insight: tomorrow's action items
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- action_items = generate_deep_insights('daily', 'action', metrics)
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- _add_structured_insight(s8, action_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- for slide in prs.slides:
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- _ensure_word_wrap_all(slide)
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- _delete_template_slides(prs)
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- prs.save(output_path)
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- print(f"Daily report saved: {output_path}")
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-
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-
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-
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-# ==============================================================================
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-# WEEKLY REPORT
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-# ==============================================================================
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-
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-def build_weekly_report(data_file: str, year: int, week: int, output_path: str,
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- department='海外事业部', source='海外订单日报系统'):
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- master_path = get_master_template('weekly')
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- prs = Presentation(master_path)
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- content_top = _detect_content_top(prs.slides[1])
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-
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- df, prev_df = load_weekly(data_file, year, week)
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- metrics = calc_weekly_metrics(df, prev_df)
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-
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- period_str = f"{year}年第{week}周"
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- date_range_str = f"{df['_data_date'].min().strftime('%m/%d')} - {df['_data_date'].max().strftime('%m/%d')}"
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-
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- # Page 1: Cover
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- slide = _duplicate_slide(prs, prs.slides[0])
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- _replace_all_placeholders(slide, {
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- '{report_title}': '海外订单数据周报',
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- '{report_type}': 'Weekly Overseas Order Data Report',
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- '{date}': period_str,
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- '{department}': department,
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- '{period}': date_range_str,
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- '{gen_time}': datetime.now().strftime('%Y-%m-%d %H:%M'),
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- }, fonts)
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- _add_footer_if_missing(slide, f'数据来源：{source} | 1/9', colors=colors)
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- # Fix {kpi4_label} {kpi4_value} with actual metric (下月预测交付)
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- cover_kpis = [
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- ('跟踪订单笔数', f"{metrics['tracking_orders']:,}", '笔',
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- _pct_str(metrics['tracking_orders'], metrics.get('prev_tracking_orders', 0))),
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- ('订单总数量', f"{metrics['total_qty']:,}", '台',
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- _pct_str(metrics['total_qty'], metrics.get('prev_total_qty', 0))),
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- ('覆盖目的国', f"{metrics['countries']}", '个', '全球布局持续深化'),
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- ('下月预测交付', f"{metrics['forecast_next']:,}", '台',
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- _pct_str(metrics['forecast_next'], metrics.get('prev_forecast_next', 0))),
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- ]
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- for i, (lbl, val, unit, chg) in enumerate(cover_kpis, 1):
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- _replace_placeholder(slide, f'{{kpi{i}_label}}', lbl)
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- _replace_placeholder(slide, f'{{kpi{i}_value}}', str(val))
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-
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- nav_labels = ['周汇总', '趋势图', '环比分析', '区域排行', '问题建议', '下周计划']
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-
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- # Page 2: Weekly Summary (KPI cards)
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- s2 = _duplicate_slide(prs, prs.slides[1])
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- t_chg = _pct_val(metrics['tracking_orders'], metrics.get('prev_tracking_orders', 0))
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- q_chg = _pct_val(metrics['total_qty'], metrics.get('prev_total_qty', 0))
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- t_chg_str = _format_pct(t_chg)
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- q_chg_str = _format_pct(q_chg)
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- _replace_all_placeholders(s2, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': f"周汇总：跟踪订单环比{t_chg_str}，订单总量增长{q_chg_str}",
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- '{source}': source,
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- '{period}': '2/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s2, nav_labels, active_index=0, slide_width=prs.slide_width, colors=colors)
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- kpis = [
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- {'label': '跟踪订单笔数', 'value': f"{metrics['tracking_orders']:,}", 'unit': '笔',
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- 'change': f'{t_chg_str} vs W1 ({metrics.get("prev_tracking_orders", 0)}笔)' if t_chg is not None else ('新增' if metrics['tracking_orders'] > 0 else '—'),
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- 'sub': f'日均{metrics["avg_daily_orders"]:.0f}笔'},
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- {'label': '订单总数量', 'value': f"{metrics['total_qty']:,}", 'unit': '台',
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- 'change': f'{q_chg_str} vs W1 ({metrics.get("prev_total_qty", 0):,})' if q_chg is not None else ('新增' if metrics['total_qty'] > 0 else '—'),
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- 'sub': f'日均{metrics["avg_daily_qty"]:.0f}台'},
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- {'label': '已发运订单', 'value': metrics['shipped_orders'], 'unit': '笔',
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- 'change': _pct_str(metrics['shipped_orders'], metrics.get('prev_shipped_orders', 0)),
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- 'sub': '环比大幅提升'},
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- {'label': '覆盖目的国', 'value': metrics['countries'], 'unit': '个',
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- 'change': '持平', 'sub': '全球布局持续深化'},
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- {'label': '进度更新订单', 'value': metrics['updated_orders'], 'unit': '笔',
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- 'change': _pct_str(metrics['updated_orders'], metrics.get('prev_updated_orders', 0)),
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- 'sub': '推进效率提升'},
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- {'label': '下月预测交付', 'value': f"{metrics['forecast_next']:,}", 'unit': '台',
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- 'change': _pct_str(metrics['forecast_next'], metrics.get('prev_forecast_next', 0)),
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- 'sub': '交付预期大幅上调'},
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- ]
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- _add_kpi_cards(s2, kpis, start_y=Emu(content_top))
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-
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- # Page 3: 7-Day Trend
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- s3 = _duplicate_slide(prs, prs.slides[1])
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- trend = metrics.get('daily_trend', {})
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- trend_title = '7日趋势：订单总量稳步上升'
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- if trend:
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- dates = list(trend.keys())
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- vals = list(trend.values())
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- if vals:
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- peak = max(vals)
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- peak_date = dates[vals.index(peak)]
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- if vals[-1] >= vals[0]:
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- trend_title = f'7日趋势：订单总量稳步上升，峰值出现在{peak_date}'
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- else:
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- trend_title = f'7日趋势：订单量有所波动，峰值出现在{peak_date}'
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- _replace_all_placeholders(s3, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': trend_title,
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- '{source}': source,
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- '{period}': '3/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s3, nav_labels, active_index=1, slide_width=prs.slide_width, colors=colors)
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- trend = metrics.get('daily_trend', {})
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- if trend:
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- dates = list(trend.keys())
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- vals = list(trend.values())
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_line_chart(s3, dates, vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- series_name='订单量', color=C_ACCENT,
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- category_axis_title='日期（MM/DD）', value_axis_title='订单数')
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- peak = max(vals) if vals else 0
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- peak_date = dates[vals.index(peak)] if vals else ''
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- avg = sum(vals) // len(vals) if vals else 0
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- prev_avg = metrics.get('prev_avg_daily_orders', 0)
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- above_days = metrics.get('days_above_prev_avg', 0)
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- total_days = len(vals)
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-
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- # Deep insight: weekly trend analysis
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- insight_items = generate_deep_insights('weekly', 'weekly_trend', metrics,
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- trend_dates=dates, trend_vals=vals)
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- _add_structured_insight(s3, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # Page 4: WoW Analysis
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- s4 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s4, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': '环比分析：各阶段全面增长，已发运环节增幅最大',
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- '{source}': source,
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- '{period}': '4/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s4, nav_labels, active_index=2, slide_width=prs.slide_width, colors=colors)
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- sw_data = metrics.get('status_wow', {})
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- if sw_data:
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- names = list(sw_data.keys())
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- current_vals = [v['current'] for v in sw_data.values()]
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- previous_vals = [v['previous'] for v in sw_data.values()]
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- # Replace None with 0 for chart data to avoid crashes
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- changes = [v['change_pct'] if v['change_pct'] is not None else 0 for v in sw_data.values()]
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-
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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-
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- # Grouped bar chart: 本期 vs 上期
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- add_grouped_bar_chart(s4, names,
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- [('本期', current_vals), ('上期', previous_vals)],
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- colors=[C_ACCENT, C_SECONDARY],
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- show_legend=True, show_data_labels=True,
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- category_axis_title='订单状态', value_axis_title='订单数')
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-
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- # WoW增幅 labels below chart
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- wow_label_items = []
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- for k, v in sw_data.items():
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- pct_str = _format_pct(v['change_pct'])
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- arrow = '↑' if v['change_pct'] is not None and v['change_pct'] >= 0 else '↓' if v['change_pct'] is not None else ''
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- wow_label_items.append(f'{k} {pct_str}{arrow}')
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- _add_text_block(s4, '环比增幅', ' | '.join(wow_label_items, colors=colors),
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- Emu(762000), Emu(6604000), chart_w, Emu(609600),
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- title_size=Pt(11), body_size=Pt(10))
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-
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- # Deep insight: WoW analysis
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- insight_items = generate_deep_insights('weekly', 'weekly_wow', metrics)
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- _add_structured_insight(s4, insight_items,
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- text_left, Emu(content_top), text_w, Emu(4826000))
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-
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- # Page 5: Region Distribution
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- s5 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s5, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': '区域分布：中东增速领跑，欧洲为唯一下滑区域',
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- '{source}': source,
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- '{period}': '5/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s5, nav_labels, active_index=3, slide_width=prs.slide_width, colors=colors)
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- rdist = metrics.get('region_dist', {})
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- if rdist:
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- regions = list(rdist.keys())
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- qtys = [v['qty'] for v in rdist.values()]
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_doughnut_chart(s5, regions, qtys,
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- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
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- show_legend=True, show_data_labels=True, show_percent=True,
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- ring_ratio=0.6)
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- # Deep insight: regional analysis
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- insight_items = generate_deep_insights('weekly', 'weekly_region', metrics)
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- _add_structured_insight(s5, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # Page 6: TOP Countries
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- s6 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s6, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': 'TOP国家排行：科威特344台居首，TOP15贡献70%+总量',
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- '{source}': source,
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- '{period}': '6/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s6, nav_labels, active_index=3, slide_width=prs.slide_width, colors=colors)
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- topc_change = metrics.get('top_countries_change', {})
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- if topc_change:
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- countries = list(topc_change.keys())[:10]
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- vals = [v['qty'] for v in list(topc_change.values())[:10]]
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_horizontal_bar_chart(s6, countries, vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- series_name='订单量(台)', color=C_ACCENT, reverse_order=True,
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- value_axis_title='订单量（台）')
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- # Deep insight: top countries analysis
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- insight_items = generate_deep_insights('weekly', 'weekly_country', metrics)
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- _add_structured_insight(s6, insight_items,
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- text_left, Emu(content_top), text_w, Emu(4826000))
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-
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- # Page 7: Team Tracking
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- s7 = _duplicate_slide(prs, prs.slides[1])
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- team = metrics.get('team', {})
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- n_members = len(team.get('owners', {})) if team else 0
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- n_growers = sum(1 for v in metrics.get('team_wow', {}).values() if v.get('change', 0) > 0)
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- team_title = f'团队追踪：{n_members}人团队全面覆盖，{n_growers}人实现增长'
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- _replace_all_placeholders(s7, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': team_title,
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- '{source}': source,
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- '{period}': '7/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s7, nav_labels, active_index=4, slide_width=prs.slide_width, colors=colors)
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- team = metrics.get('team', {})
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- owners = team.get('owners', {})
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- if owners:
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- names = list(owners.keys())
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- vals = list(owners.values())
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- add_horizontal_bar_chart(s7, names, vals,
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- series_name='订单笔数', color=C_ACCENT, reverse_order=True,
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- value_axis_title='订单笔数')
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- # Deep insight: team tracking
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- insight_items = generate_deep_insights('weekly', 'weekly_team', metrics)
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- _add_structured_insight(s7, insight_items,
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- text_left, Emu(content_top), text_w, Emu(4826000))
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-
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- # Page 8: Issues
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- s8 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s8, {
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- '{report_title}': '海外订单数据周报',
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- '{date}': period_str,
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- '{page_title}': '问题识别：系统数据匹配问题为本周首要障碍',
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- '{source}': source,
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- '{period}': '8/9',
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- '{page_num}': '',
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- })
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- _add_nav_tabs(s8, nav_labels, active_index=4, slide_width=prs.slide_width, colors=colors)
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- # Left chart: support request categories
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- sc = metrics.get('support_categories', {})
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- chart_w = Emu(int(prs.slide_width) * 0.55)
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- text_left = Emu(int(prs.slide_width) * 0.62)
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- text_w = Emu(int(prs.slide_width) * 0.36)
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- if sc:
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- add_horizontal_bar_chart(s8, list(sc.keys()), list(sc.values()),
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- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
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- series_name='需求数', color=C_ORANGE, reverse_order=True,
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- value_axis_title='数量')
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- # Right: deep insight
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- insight_items = generate_deep_insights('weekly', 'weekly_issue', metrics)
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- _add_structured_insight(s8, insight_items,
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- text_left, Emu(content_top), text_w, Emu(5334000))
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-
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- # Page 9: Next Week Plan
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- s9 = _duplicate_slide(prs, prs.slides[1])
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- _replace_all_placeholders(s9, {
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- '{report_title}': '海外订单数据周报',
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|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '下周计划：聚焦发运交付，冲刺交付目标',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '9/9',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s9, nav_labels, active_index=5, slide_width=prs.slide_width, colors=colors)
|
|
|
-
|
|
|
- # Left chart: goals as column chart
|
|
|
- goals = metrics.get('next_week_goals', [])
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- if goals:
|
|
|
- goal_names = [g['title'].split('：')[0] for g in goals[:4]]
|
|
|
- goal_nums = [g.get('number', 0) for g in goals[:4]]
|
|
|
- add_column_chart(s9, goal_names, goal_nums,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
|
|
|
- series_name='目标数量', color=C_ACCENT,
|
|
|
- category_axis_title='目标', value_axis_title='数量')
|
|
|
-
|
|
|
- # Deep insight: next week plan
|
|
|
- insight_items = generate_deep_insights('weekly', 'weekly_plan', metrics)
|
|
|
- _add_structured_insight(s9, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(5334000))
|
|
|
-
|
|
|
- for slide in prs.slides:
|
|
|
- _ensure_word_wrap_all(slide)
|
|
|
- _delete_template_slides(prs)
|
|
|
- prs.save(output_path)
|
|
|
- print(f"Weekly report saved: {output_path}")
|
|
|
-
|
|
|
-
|
|
|
-
|
|
|
-
|
|
|
-
|
|
|
-
|
|
|
-# ==============================================================================
|
|
|
-# MONTHLY REPORT
|
|
|
-# ==============================================================================
|
|
|
-
|
|
|
-def build_monthly_report(data_file: str, year: int, month: int, output_path: str,
|
|
|
- department='海外事业部', source='海外订单日报系统'):
|
|
|
- master_path = get_master_template('monthly')
|
|
|
- prs = Presentation(master_path)
|
|
|
- content_top = _detect_content_top(prs.slides[1])
|
|
|
-
|
|
|
- df, prev_df, yoy_df = load_monthly(data_file, year, month)
|
|
|
- metrics = calc_monthly_metrics(df, prev_df, yoy_df)
|
|
|
-
|
|
|
- period_str = f"{year}年{month}月"
|
|
|
-
|
|
|
- # Page 1: Cover
|
|
|
- slide = _duplicate_slide(prs, prs.slides[0])
|
|
|
- _replace_all_placeholders(slide, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{report_type}': 'Monthly Overseas Order Data Report',
|
|
|
- '{date}': period_str,
|
|
|
- '{department}': department,
|
|
|
- '{period}': period_str,
|
|
|
- '{gen_time}': datetime.now().strftime('%Y-%m-%d %H:%M'),
|
|
|
- }, fonts)
|
|
|
- _add_footer_if_missing(slide, f'数据来源：{source} | 1/11', colors=colors)
|
|
|
- cover_kpis = [
|
|
|
- ('合同总数', f"{metrics['total_contracts']:,}"),
|
|
|
- ('车辆总数', f"{metrics['total_qty']:,}"),
|
|
|
- ('目的国家', f"{metrics['countries']}+"),
|
|
|
- ('负责团队', '9人'),
|
|
|
- ]
|
|
|
- for i, (lbl, val) in enumerate(cover_kpis, 1):
|
|
|
- _replace_placeholder(slide, f'{{kpi{i}_label}}', lbl)
|
|
|
- _replace_placeholder(slide, f'{{kpi{i}_value}}', val)
|
|
|
-
|
|
|
- # Page 2: TOC
|
|
|
- s_toc = _duplicate_slide(prs, prs.slides[2])
|
|
|
- _add_footer_if_missing(s_toc, f'数据来源：{source} | 2/11', colors=colors)
|
|
|
- _replace_all_placeholders(s_toc, {
|
|
|
- '{chapter1_title}': '月度总览',
|
|
|
- '{chapter1_desc}': '核心KPI一览：合同总数、车辆规模、新签与发运表现',
|
|
|
- '{chapter2_title}': '订单状态分析',
|
|
|
- '{chapter2_desc}': '订单阶段漏斗：从合同拟定到发运的全流程追踪',
|
|
|
- '{chapter3_title}': '区域与趋势',
|
|
|
- '{chapter3_desc}': '区域分布、国家排名与30日追踪趋势',
|
|
|
- '{chapter4_title}': '团队与展望',
|
|
|
- '{chapter4_desc}': '团队绩效、支持需求与下月工作规划',
|
|
|
- })
|
|
|
-
|
|
|
- nav_labels = ['月度总览', '订单状态', '区域趋势', '团队展望']
|
|
|
-
|
|
|
- # Page 3: Monthly Overview
|
|
|
- s3 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s3, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': f"{month}月核心指标：累计追踪{metrics['total_contracts']:,}单，覆盖{metrics['total_qty']:,}台车辆",
|
|
|
- '{source}': source,
|
|
|
- '{period}': '3/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s3, nav_labels, active_index=0, slide_width=prs.slide_width, colors=colors)
|
|
|
- kpis = [
|
|
|
- {'label': '合同总数', 'value': f"{metrics['total_contracts']:,}", 'unit': '单',
|
|
|
- 'change': f'日均{metrics["avg_daily_orders"]:.0f}单', 'sub': '覆盖全月'},
|
|
|
- {'label': '车辆总数', 'value': f"{metrics['total_qty']:,}", 'unit': '台',
|
|
|
- 'change': f"{metrics['shipped_qty']:,}台已发运", 'sub': '交付持续推进'},
|
|
|
- {'label': f'{month}月新签', 'value': metrics['new_contracts'], 'unit': '单',
|
|
|
- 'change': f"{metrics['new_qty']:,}台", 'sub': '新签势头良好'},
|
|
|
- {'label': '已发运', 'value': metrics['shipped_orders'], 'unit': '单',
|
|
|
- 'change': f"{metrics['shipped_qty']:,}台", 'sub': '交付稳步推进'},
|
|
|
- {'label': '目的国', 'value': f"{metrics['countries']}+", 'unit': '个',
|
|
|
- 'change': '全球市场布局', 'sub': '持续深化'},
|
|
|
- {'label': '待处理需求', 'value': metrics['support_count'], 'unit': '单',
|
|
|
- 'change': f"{metrics['support_pct']}%订单涉及", 'sub': '需跨部门协调'},
|
|
|
- ]
|
|
|
- _add_kpi_cards(s3, kpis, start_y=Emu(content_top))
|
|
|
-
|
|
|
- # Monthly overview: KPI cards only, no bottom insight text to avoid overlap with cards
|
|
|
-
|
|
|
- # Page 4: Status Funnel
|
|
|
- s4 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s4, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '订单阶段漏斗：合同拟定与生产中订单占主导地位',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '4/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s4, nav_labels, active_index=1, slide_width=prs.slide_width, colors=colors)
|
|
|
- funnel = metrics.get('status_funnel', {})
|
|
|
- if funnel:
|
|
|
- names = list(funnel.keys())
|
|
|
- orders = [v['orders'] for v in funnel.values()]
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- add_funnel_chart(s4, names, orders,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
|
|
|
- show_data_labels=True, show_percent=True)
|
|
|
- # Deep insight: monthly funnel
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_funnel', metrics)
|
|
|
- _add_structured_insight(s4, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(5334000))
|
|
|
-
|
|
|
- # Page 5: Region Distribution
|
|
|
- s5 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s5, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '区域分布：拉美、东南亚、非洲三大市场并驾齐驱',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '5/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s5, nav_labels, active_index=2, slide_width=prs.slide_width, colors=colors)
|
|
|
- rdist = metrics.get('region_dist', {})
|
|
|
- if rdist:
|
|
|
- regions = list(rdist.keys())
|
|
|
- qtys = [v['qty'] for v in rdist.values()]
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- add_doughnut_chart(s5, regions, qtys,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
|
|
|
- show_legend=True, show_data_labels=True, show_percent=True,
|
|
|
- ring_ratio=0.6)
|
|
|
- # Deep insight: monthly region
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_region', metrics)
|
|
|
- _add_structured_insight(s5, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(5334000))
|
|
|
-
|
|
|
- # Page 6: TOP10 Countries
|
|
|
- s6 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- top10 = metrics.get('top_countries', {})
|
|
|
- top_country = list(top10.keys())[0] if top10 else ''
|
|
|
- top_qty = list(top10.values())[0]['qty'] if top10 else 0
|
|
|
- top10_title = f'Top 10目的国：{top_country}{top_qty:,}台领跑' if top_country else 'Top 10目的国：重点市场领跑'
|
|
|
- _replace_all_placeholders(s6, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': top10_title,
|
|
|
- '{source}': source,
|
|
|
- '{period}': '6/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s6, nav_labels, active_index=2, slide_width=prs.slide_width, colors=colors)
|
|
|
- top10 = metrics.get('top_countries', {})
|
|
|
- if top10:
|
|
|
- countries = list(top10.keys())
|
|
|
- qtys = [v['qty'] for v in top10.values()]
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- add_horizontal_bar_chart(s6, countries, qtys,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
|
|
|
- series_name='订单量(台)', color=C_ACCENT, reverse_order=True,
|
|
|
- value_axis_title='订单量（台）')
|
|
|
- # Deep insight: monthly top countries
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_country', metrics)
|
|
|
- _add_structured_insight(s6, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(4826000))
|
|
|
-
|
|
|
- # Page 7: 30-Day Trend
|
|
|
- s7 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s7, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '30日追踪趋势：下旬订单活跃度显著提升',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '7/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s7, nav_labels, active_index=2, slide_width=prs.slide_width, colors=colors)
|
|
|
- trend = metrics.get('daily_trend', {})
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- if trend:
|
|
|
- dates = list(trend.keys())
|
|
|
- vals = list(trend.values())
|
|
|
- add_line_chart(s7, dates, vals,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(5334000),
|
|
|
- series_name='订单量', color=C_ACCENT,
|
|
|
- category_axis_title='日期（MM/DD）', value_axis_title='订单数')
|
|
|
- tbp = metrics.get('trend_by_period', {})
|
|
|
- late_change = tbp.get('late_change_pct', 0)
|
|
|
- late_change_str = _format_pct(late_change, with_sign=True) if late_change is not None else '—'
|
|
|
-
|
|
|
- # Deep insight: monthly trend
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_trend', metrics)
|
|
|
- _add_structured_insight(s7, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(5334000))
|
|
|
-
|
|
|
- # Page 8: Team Performance
|
|
|
- s8 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s8, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '团队绩效：9位负责人均匀分布，多人领跑',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '8/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s8, nav_labels, active_index=3, slide_width=prs.slide_width, colors=colors)
|
|
|
- team = metrics.get('team', {})
|
|
|
- if team:
|
|
|
- names = list(team.keys())
|
|
|
- orders = [v['orders'] for v in team.values()]
|
|
|
- qtys = [v['qty'] for v in team.values()]
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- # Horizontal bar chart for orders + secondary series for qty
|
|
|
- add_grouped_bar_chart(s8, names,
|
|
|
- [('订单数', orders), ('车辆数', qtys)],
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
|
|
|
- colors=[C_ACCENT, C_ORANGE],
|
|
|
- show_legend=True, show_data_labels=True,
|
|
|
- category_axis_title='负责人', value_axis_title='数量')
|
|
|
- # Deep insight: monthly team
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_team', metrics)
|
|
|
- _add_structured_insight(s8, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(4826000))
|
|
|
-
|
|
|
- # Page 9: Support Analysis
|
|
|
- s9 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s9, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': '支持需求分析：财务、售后、法务为三大核心诉求',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '9/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s9, nav_labels, active_index=3, slide_width=prs.slide_width, colors=colors)
|
|
|
- sc = metrics.get('support_categories', {})
|
|
|
- if sc:
|
|
|
- cats = list(sc.keys())
|
|
|
- vals = list(sc.values())
|
|
|
- add_horizontal_bar_chart(s9, cats, vals,
|
|
|
- Emu(762000), Emu(content_top), Emu(8636000), Emu(5334000),
|
|
|
- series_name='需求数', color=C_ACCENT, reverse_order=True,
|
|
|
- value_axis_title='需求数')
|
|
|
- top_cat = max(sc.items(), key=lambda x: x[1])
|
|
|
- # Deep insight: monthly support
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_support', metrics)
|
|
|
- _add_structured_insight(s9, insight_items,
|
|
|
- Emu(9779000), Emu(content_top), Emu(5715000), Emu(5334000))
|
|
|
-
|
|
|
- # Page 10: Next Month Plan
|
|
|
- s10 = _duplicate_slide(prs, prs.slides[1])
|
|
|
- _replace_all_placeholders(s10, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{page_title}': f'{month+1 if month < 12 else 1}月展望：预测交付{metrics["forecast_next"]}台，重点关注交付转化',
|
|
|
- '{source}': source,
|
|
|
- '{period}': '10/11',
|
|
|
- '{page_num}': '',
|
|
|
- })
|
|
|
- _add_nav_tabs(s10, nav_labels, active_index=3, slide_width=prs.slide_width, colors=colors)
|
|
|
-
|
|
|
- # Left chart: next month goals as column chart
|
|
|
- goals = metrics.get('next_month_goals', [])
|
|
|
- chart_w = Emu(int(prs.slide_width) * 0.55)
|
|
|
- text_left = Emu(int(prs.slide_width) * 0.62)
|
|
|
- text_w = Emu(int(prs.slide_width) * 0.36)
|
|
|
- if goals:
|
|
|
- goal_names = [g['title'].split('：')[0] for g in goals[:5]]
|
|
|
- goal_nums = [g.get('number', 0) for g in goals[:5]]
|
|
|
- add_column_chart(s10, goal_names, goal_nums,
|
|
|
- Emu(762000), Emu(content_top), chart_w, Emu(4826000),
|
|
|
- series_name='目标数量', color=C_ACCENT,
|
|
|
- category_axis_title='目标', value_axis_title='数量')
|
|
|
-
|
|
|
- # Deep insight: monthly plan
|
|
|
- insight_items = generate_deep_insights('monthly', 'monthly_plan', metrics)
|
|
|
- _add_structured_insight(s10, insight_items,
|
|
|
- text_left, Emu(content_top), text_w, Emu(5334000))
|
|
|
-
|
|
|
- # Page 11: End
|
|
|
- s_end = _duplicate_slide(prs, prs.slides[3])
|
|
|
- _add_footer_if_missing(s_end, f'数据来源：{source} | 11/11', colors=colors)
|
|
|
- _replace_all_placeholders(s_end, {
|
|
|
- '{report_title}': '海外订单月度数据报告',
|
|
|
- '{date}': period_str,
|
|
|
- '{department}': department,
|
|
|
- })
|
|
|
- end_kpis = [
|
|
|
- ('合同总数', f"{metrics['total_contracts']:,}"),
|
|
|
- ('车辆总数', f"{metrics['total_qty']:,}"),
|
|
|
- ('目的国家', f"{metrics['countries']}+"),
|
|
|
- ('团队', '9人'),
|
|
|
- ]
|
|
|
- for i, (lbl, val) in enumerate(end_kpis, 1):
|
|
|
- _replace_placeholder(s_end, f'{{kpi{i}_label}}', lbl)
|
|
|
- _replace_placeholder(s_end, f'{{kpi{i}_value}}', val)
|
|
|
-
|
|
|
- for slide in prs.slides:
|
|
|
- _ensure_word_wrap_all(slide)
|
|
|
- _delete_template_slides(prs)
|
|
|
- prs.save(output_path)
|
|
|
- print(f"Monthly report saved: {output_path}")
|
|
|
-
|
|
|
-
|
|
|
-# ==============================================================================
|
|
|
# CLI
|
|
|
# ==============================================================================
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
import sys
|
|
|
- if len(sys.argv) >= 4:
|
|
|
- cmd = sys.argv[1]
|
|
|
- data_file = sys.argv[2]
|
|
|
- output = sys.argv[3]
|
|
|
- if cmd == 'daily':
|
|
|
- d = datetime.strptime(sys.argv[4], '%Y-%m-%d')
|
|
|
- build_daily_report(data_file, d, output)
|
|
|
- elif cmd == 'weekly':
|
|
|
- build_weekly_report(data_file, int(sys.argv[4]), int(sys.argv[5]), output)
|
|
|
- elif cmd == 'monthly':
|
|
|
- build_monthly_report(data_file, int(sys.argv[4]), int(sys.argv[5]), output)
|
|
|
+ if len(sys.argv) >= 3:
|
|
|
+ from report_config import load_report_config
|
|
|
+ data_file = sys.argv[1]
|
|
|
+ config_file = sys.argv[2]
|
|
|
+ output = sys.argv[3] if len(sys.argv) >= 4 else 'output.pptx'
|
|
|
+ config = load_report_config(config_file)
|
|
|
+ quality_assured_build(data_file, config, output)
|
|
|
+ else:
|
|
|
+ print("Usage: python ppt_builder.py <data_file> <config_file> [output_path]")
|
