Python 报告生成器 | 自动化创建专业数据报告与图表 | 支持 PDF/HTML 输出

report-generator by dkyazzentwatwa/chatgpt-skills

124 周安装量

37 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill report-generator

数据可视化自动化文档生成

🇨🇳中文介绍

报告生成器

创建专业的、数据驱动的报告，包含图表、表格和叙述性文本。适用于业务报告、分析仪表板、状态更新和自动化报告流水线。

快速开始

from scripts.report_gen import ReportGenerator

# 创建简单报告
report = ReportGenerator("月度销售报告")
report.add_text("本报告总结了 2024 年第四季度的销售表现。")
report.add_table(sales_data, title="按区域划分的销售额")
report.add_chart(sales_data, chart_type="bar", title="月度收入")
report.add_text("关键发现：收入环比增长 25%。")
report.generate().save("sales_report.pdf")

# 从模板创建
report = ReportGenerator.from_template("executive_summary")
report.set_data(data_dict)
report.generate().save("exec_summary.pdf")

功能特性

多种输出格式 : PDF, HTML
丰富内容 : 文本、表格、图表、图像、页眉
图表类型 : 柱状图、折线图、饼图、散点图、面积图、热力图
表格格式化 : 自动样式、条件格式化
模板 : 预置的报告模板
品牌化 : 徽标、颜色、字体、页眉/页脚
章节 : 目录、页码、附录
数据集成 : CSV、DataFrame、字典输入

API 参考

初始化

# 新建报告
report = ReportGenerator("报告标题")
report = ReportGenerator("报告标题", subtitle="2024 年第四季度分析")

# 从模板创建
report = ReportGenerator.from_template("quarterly_review")

# 带配置
report = ReportGenerator("标题", config={
    "page_size": "letter",
    "orientation": "portrait",
    "margins": {"top": 1, "bottom": 1, "left": 0.75, "right": 0.75}
})

广告位招租

在这里展示您的产品或服务

触达数万 AI 开发者，精准高效

联系我们

相关 Skills

FlyClaw：零登录航班聚合查询工具，Python实现多源航班信息与价格搜索

4,000,000 周安装

Azure RBAC 权限管理工具：查找最小角色、创建自定义角色与自动化分配

129,699 周安装

GitHub Actions 官方文档查询助手 - 精准解答 CI/CD 工作流问题

36,800 周安装

Skills CLI 使用指南：AI Agent 技能包管理器安装与管理教程

36,300 周安装

# 标题和副标题
report.set_title("2024 年度报告")
report.set_subtitle("财务表现分析")

# 作者和日期
report.set_author("分析团队")
report.set_date("2024 年 12 月")
report.set_date_auto()  # 使用当天日期

# 组织
report.set_organization("Acme 公司")
report.set_logo("logo.png")

# 简单段落
report.add_text("这是一段分析文本。")

# 带样式的文本
report.add_text("重要发现！", style="highlight")
report.add_text("关键指标：42%", style="metric")

# 标题
report.add_heading("执行摘要", level=1)
report.add_heading("收入分析", level=2)
report.add_heading("按区域", level=3)

# 项目符号列表
report.add_bullets([
    "收入同比增长 25%",
    "客户获取量增长 15%",
    "流失率降至 3%"
])

# 编号列表
report.add_numbered_list([
    "拓展欧洲市场",
    "推出移动应用程序",
    "实施 AI 驱动分析"
])

# 从 DataFrame
import pandas as pd
df = pd.DataFrame({
    'Region': ['North', 'South', 'East', 'West'],
    'Revenue': [100000, 85000, 92000, 78000],
    'Growth': ['12%', '8%', '15%', '5%']
})
report.add_table(df, title="区域表现")

# 从字典/列表
data = [
    {'Product': 'A', 'Sales': 1000, 'Profit': 200},
    {'Product': 'B', 'Sales': 1500, 'Profit': 350}
]
report.add_table(data, title="产品摘要")

# 带样式
report.add_table(df, title="销售数据",
    highlight_max=['Revenue'],       # 高亮最大值
    highlight_min=['Growth'],        # 高亮最小值
    currency_cols=['Revenue'],       # 格式化为货币
    percent_cols=['Growth'],         # 格式化为百分比
    align={'Region': 'left', 'Revenue': 'right'}
)

# 柱状图
report.add_chart(
    data=df,
    chart_type="bar",
    x="Region",
    y="Revenue",
    title="按区域划分的收入"
)

# 折线图
report.add_chart(
    data=time_series_df,
    chart_type="line",
    x="Month",
    y=["Sales", "Forecast"],
    title="销售趋势"
)

# 饼图
report.add_chart(
    data=category_df,
    chart_type="pie",
    values="Amount",
    labels="Category",
    title="预算分配"
)

# 图表选项
report.add_chart(
    data=df,
    chart_type="bar",
    x="Region",
    y="Revenue",
    title="收入分析",
    color="#3498db",
    width=6,           # 英寸
    height=4,
    show_values=True,
    show_legend=True
)

# 添加图像
report.add_image("screenshot.png", caption="仪表板视图")
report.add_image("diagram.png", width=5, caption="架构图")

# 分页符
report.add_page_break()

# 水平线
report.add_divider()

# 间距
report.add_spacer(height=0.5)  # 英寸

# 提示框
report.add_callout(
    "关键洞察：实施新入职流程后，客户留存率提高了 20%。",
    style="info"  # info, warning, success, error
)

# 引用
report.add_quote(
    "数据是新的石油。",
    attribution="Clive Humby"
)

# 开始新章节
report.start_section("财务分析")

# 向章节添加内容
report.add_text("...")
report.add_table(...)

# 结束章节
report.end_section()

# 目录（自动生成）
report.enable_toc()

# 附录
report.start_appendix()
report.add_heading("原始数据", level=2)
report.add_table(raw_data)

# 徽标和组织
report.set_logo("logo.png", width=150)
report.set_organization("Acme 公司")

# 颜色
report.set_colors(
    primary="#1e40af",      # 标题、强调色
    secondary="#6b7280",    # 次要文本
    background="#ffffff"    # 背景
)

# 字体
report.set_fonts(
    heading="Helvetica-Bold",
    body="Helvetica"
)

# 页眉和页脚
report.set_header("机密 - 内部使用")
report.set_footer("第 {page} 页，共 {total} 页")

# 水印
report.set_watermark("草稿")

# 可用模板
report = ReportGenerator.from_template("executive_summary")
report = ReportGenerator.from_template("quarterly_review")
report = ReportGenerator.from_template("project_status")
report = ReportGenerator.from_template("analytics_dashboard")

# 带数据的模板
report = ReportGenerator.from_template("monthly_metrics")
report.set_data({
    "period": "2024 年 12 月",
    "revenue": 1500000,
    "growth": 0.15,
    "customers": 5000,
    "charts": {"revenue_trend": trend_df}
})
report.generate()

# 生成报告
report.generate()

# 保存为 PDF
report.save("report.pdf")

# 保存为 HTML
report.save("report.html")

# 获取字节
pdf_bytes = report.to_bytes()
html_string = report.to_html()

标题页
关键指标亮点
摘要要点
图表部分
建议

表现概览
财务指标
与上一季度对比
目标进度
下季度展望

项目概览
时间线/里程碑
风险和问题
团队更新
后续步骤

KPI 卡片
多个图表
趋势分析
数据表
洞察

# 从 JSON 配置生成
python report_gen.py --config report_config.json --output report.pdf

# 使用模板
python report_gen.py --template executive_summary --data data.json --output summary.pdf

# 从 CSV 快速生成报告
python report_gen.py --csv data.csv --title "数据报告" --output report.pdf

参数	描述	默认值
`--config`	报告配置 JSON	-
`--template`	模板名称	-
`--data`	数据 JSON 文件	-
`--csv`	CSV 数据文件	-
`--title`	报告标题	`Report`
`--output`	输出文件路径	`report.pdf`
`--format`	输出格式 (pdf/html)	`pdf`

report = ReportGenerator("第四季度销售报告")
report.set_subtitle("2024 年 10 月 - 12 月")
report.set_organization("销售部门")
report.set_logo("company_logo.png")

report.add_heading("执行摘要", level=1)
report.add_text(
    "2024 年第四季度所有区域均表现出色，"
    "总收入达到 420 万美元，较第三季度增长 23%。"
)

report.add_callout(
    "总收入：420 万美元（环比增长 23%）",
    style="success"
)

report.add_heading("区域表现", level=2)
report.add_chart(regional_data, "bar", x="Region", y="Revenue",
                 title="按区域划分的收入")
report.add_table(regional_data, title="详细指标")

report.add_heading("趋势", level=2)
report.add_chart(monthly_data, "line", x="Month", y="Revenue",
                 title="月度收入趋势")

report.add_heading("建议", level=1)
report.add_bullets([
    "增加对高增长的东部区域的投资",
    "解决西部区域表现下滑的问题",
    "启动第一季度促销活动"
])

report.generate().save("q4_sales_report.pdf")

report = ReportGenerator("营销分析")
report.set_date_auto()

# KPI 摘要
report.add_heading("关键指标", level=1)
kpis = [
    ["访客数", "125,000", "+15%"],
    ["转化数", "3,750", "+22%"],
    ["收入", "$187,500", "+18%"],
    ["CAC", "$45", "-8%"]
]
report.add_table(kpis, headers=["指标", "数值", "变化"])

# 流量来源
report.add_heading("流量来源", level=2)
report.add_chart(traffic_df, "pie", values="Sessions", labels="Source",
                 title="流量分布")

# 转化漏斗
report.add_heading("转化漏斗", level=2)
report.add_chart(funnel_df, "bar", x="Stage", y="Users",
                 title="漏斗分析", horizontal=True)

# 趋势分析
report.add_heading("趋势", level=2)
report.add_chart(daily_df, "line", x="Date", y=["Visitors", "Conversions"],
                 title="每日表现")

report.generate().save("marketing_dashboard.pdf")

reportlab>=4.0.0
Pillow>=10.0.0
pandas>=2.0.0
matplotlib>=3.7.0

PDF 中的图表渲染为静态图像
复杂布局可能需要手动调整
大数据集可能影响性能
HTML 输出具有基本样式（无交互式图表）

2026 年 1 月 24 日

🇺🇸English

Report Generator

Create professional, data-driven reports with charts, tables, and narrative text. Perfect for business reports, analytics dashboards, status updates, and automated reporting pipelines.

Quick Start

from scripts.report_gen import ReportGenerator

# Create a simple report
report = ReportGenerator("Monthly Sales Report")
report.add_text("This report summarizes sales performance for Q4 2024.")
report.add_table(sales_data, title="Sales by Region")
report.add_chart(sales_data, chart_type="bar", title="Revenue by Month")
report.add_text("Key findings: Revenue increased 25% quarter-over-quarter.")
report.generate().save("sales_report.pdf")

# From template
report = ReportGenerator.from_template("executive_summary")
report.set_data(data_dict)
report.generate().save("exec_summary.pdf")

Features

Multiple Output Formats : PDF, HTML
Rich Content : Text, tables, charts, images, headers
Chart Types : Bar, line, pie, scatter, area, heatmap
Table Formatting : Auto-styling, conditional formatting
Templates : Pre-built report templates
Branding : Logo, colors, fonts, headers/footers
Sections : Table of contents, page numbers, appendices
Data Integration : CSV, DataFrame, dict inputs

API Reference

Initialization

# New report
report = ReportGenerator("Report Title")
report = ReportGenerator("Report Title", subtitle="Q4 2024 Analysis")

# From template
report = ReportGenerator.from_template("quarterly_review")

# With config
report = ReportGenerator("Title", config={
    "page_size": "letter",
    "orientation": "portrait",
    "margins": {"top": 1, "bottom": 1, "left": 0.75, "right": 0.75}
})

Report Metadata

# Title and subtitle
report.set_title("Annual Report 2024")
report.set_subtitle("Financial Performance Analysis")

# Author and date
report.set_author("Analytics Team")
report.set_date("December 2024")
report.set_date_auto()  # Use today

# Organization
report.set_organization("Acme Corporation")
report.set_logo("logo.png")

Adding Content

Text Content

# Simple paragraph
report.add_text("This is a paragraph of analysis text.")

# Styled text
report.add_text("Important finding!", style="highlight")
report.add_text("Key metric: 42%", style="metric")

# Headers
report.add_heading("Executive Summary", level=1)
report.add_heading("Revenue Analysis", level=2)
report.add_heading("By Region", level=3)

# Bullet points
report.add_bullets([
    "Revenue increased 25% YoY",
    "Customer acquisition up 15%",
    "Churn rate decreased to 3%"
])

# Numbered list
report.add_numbered_list([
    "Expand to European markets",
    "Launch mobile application",
    "Implement AI-driven analytics"
])

Tables

# From DataFrame
import pandas as pd
df = pd.DataFrame({
    'Region': ['North', 'South', 'East', 'West'],
    'Revenue': [100000, 85000, 92000, 78000],
    'Growth': ['12%', '8%', '15%', '5%']
})
report.add_table(df, title="Regional Performance")

# From dict/list
data = [
    {'Product': 'A', 'Sales': 1000, 'Profit': 200},
    {'Product': 'B', 'Sales': 1500, 'Profit': 350}
]
report.add_table(data, title="Product Summary")

# With styling
report.add_table(df, title="Sales Data",
    highlight_max=['Revenue'],       # Highlight max values
    highlight_min=['Growth'],        # Highlight min values
    currency_cols=['Revenue'],       # Format as currency
    percent_cols=['Growth'],         # Format as percent
    align={'Region': 'left', 'Revenue': 'right'}
)

Charts

# Bar chart
report.add_chart(
    data=df,
    chart_type="bar",
    x="Region",
    y="Revenue",
    title="Revenue by Region"
)

# Line chart
report.add_chart(
    data=time_series_df,
    chart_type="line",
    x="Month",
    y=["Sales", "Forecast"],
    title="Sales Trend"
)

# Pie chart
report.add_chart(
    data=category_df,
    chart_type="pie",
    values="Amount",
    labels="Category",
    title="Budget Allocation"
)

# Chart options
report.add_chart(
    data=df,
    chart_type="bar",
    x="Region",
    y="Revenue",
    title="Revenue Analysis",
    color="#3498db",
    width=6,           # inches
    height=4,
    show_values=True,
    show_legend=True
)

Images

# Add image
report.add_image("screenshot.png", caption="Dashboard View")
report.add_image("diagram.png", width=5, caption="Architecture Diagram")

Special Elements

# Page break
report.add_page_break()

# Horizontal line
report.add_divider()

# Spacer
report.add_spacer(height=0.5)  # inches

# Callout box
report.add_callout(
    "Key Insight: Customer retention improved 20% after implementing the new onboarding flow.",
    style="info"  # info, warning, success, error
)

# Quote
report.add_quote(
    "Data is the new oil.",
    attribution="Clive Humby"
)

Sections and Structure

# Start a new section
report.start_section("Financial Analysis")

# Add content to section
report.add_text("...")
report.add_table(...)

# End section
report.end_section()

# Table of contents (auto-generated)
report.enable_toc()

# Appendix
report.start_appendix()
report.add_heading("Raw Data", level=2)
report.add_table(raw_data)

Branding and Styling

# Logo and organization
report.set_logo("logo.png", width=150)
report.set_organization("Acme Corp")

# Colors
report.set_colors(
    primary="#1e40af",      # Headers, accents
    secondary="#6b7280",    # Secondary text
    background="#ffffff"    # Background
)

# Fonts
report.set_fonts(
    heading="Helvetica-Bold",
    body="Helvetica"
)

# Header and footer
report.set_header("Confidential - Internal Use Only")
report.set_footer("Page {page} of {total}")

# Watermark
report.set_watermark("DRAFT")

Templates

# Available templates
report = ReportGenerator.from_template("executive_summary")
report = ReportGenerator.from_template("quarterly_review")
report = ReportGenerator.from_template("project_status")
report = ReportGenerator.from_template("analytics_dashboard")

# Template with data
report = ReportGenerator.from_template("monthly_metrics")
report.set_data({
    "period": "December 2024",
    "revenue": 1500000,
    "growth": 0.15,
    "customers": 5000,
    "charts": {"revenue_trend": trend_df}
})
report.generate()

Generation and Export

# Generate report
report.generate()

# Save as PDF
report.save("report.pdf")

# Save as HTML
report.save("report.html")

# Get bytes
pdf_bytes = report.to_bytes()
html_string = report.to_html()

Templates

Executive Summary

Title page
Key metrics highlights
Summary bullets
Charts section
Recommendations

Quarterly Review

Performance overview
Financial metrics
Comparison to previous quarter
Goals progress
Next quarter outlook

Project Status

Project overview
Timeline/milestones
Risks and issues
Team updates
Next steps

Analytics Dashboard

KPI cards
Multiple charts
Trend analysis
Data tables
Insights

CLI Usage

# Generate from JSON config
python report_gen.py --config report_config.json --output report.pdf

# With template
python report_gen.py --template executive_summary --data data.json --output summary.pdf

# Quick report from CSV
python report_gen.py --csv data.csv --title "Data Report" --output report.pdf

CLI Arguments

Argument	Description	Default
`--config`	Report configuration JSON	-
`--template`	Template name	-
`--data`	Data JSON file	-
`--csv`	CSV data file	-
`--title`	Report title	`Report`

Examples

Sales Report

report = ReportGenerator("Q4 Sales Report")
report.set_subtitle("October - December 2024")
report.set_organization("Sales Department")
report.set_logo("company_logo.png")

report.add_heading("Executive Summary", level=1)
report.add_text(
    "Q4 2024 showed strong performance across all regions, "
    "with total revenue reaching $4.2M, a 23% increase over Q3."
)

report.add_callout(
    "Total Revenue: $4.2M (+23% QoQ)",
    style="success"
)

report.add_heading("Regional Performance", level=2)
report.add_chart(regional_data, "bar", x="Region", y="Revenue",
                 title="Revenue by Region")
report.add_table(regional_data, title="Detailed Metrics")

report.add_heading("Trends", level=2)
report.add_chart(monthly_data, "line", x="Month", y="Revenue",
                 title="Monthly Revenue Trend")

report.add_heading("Recommendations", level=1)
report.add_bullets([
    "Increase investment in high-growth East region",
    "Address declining West region performance",
    "Launch Q1 promotional campaign"
])

report.generate().save("q4_sales_report.pdf")

Analytics Dashboard

report = ReportGenerator("Marketing Analytics")
report.set_date_auto()

# KPI Summary
report.add_heading("Key Metrics", level=1)
kpis = [
    ["Visitors", "125,000", "+15%"],
    ["Conversions", "3,750", "+22%"],
    ["Revenue", "$187,500", "+18%"],
    ["CAC", "$45", "-8%"]
]
report.add_table(kpis, headers=["Metric", "Value", "Change"])

# Traffic Sources
report.add_heading("Traffic Sources", level=2)
report.add_chart(traffic_df, "pie", values="Sessions", labels="Source",
                 title="Traffic Distribution")

# Conversion Funnel
report.add_heading("Conversion Funnel", level=2)
report.add_chart(funnel_df, "bar", x="Stage", y="Users",
                 title="Funnel Analysis", horizontal=True)

# Trend Analysis
report.add_heading("Trends", level=2)
report.add_chart(daily_df, "line", x="Date", y=["Visitors", "Conversions"],
                 title="Daily Performance")

report.generate().save("marketing_dashboard.pdf")

Dependencies

reportlab>=4.0.0
Pillow>=10.0.0
pandas>=2.0.0
matplotlib>=3.7.0

Limitations

Charts rendered as static images in PDF
Complex layouts may need manual adjustment
Large datasets may impact performance
HTML output has basic styling (no interactive charts)

Weekly Installs

124

Repository

dkyazzentwatwa/…t-skills

GitHub Stars

First Seen

Jan 24, 2026

Security Audits

Gen Agent Trust HubPass SocketPass SnykPass

Installed on

opencode108

gemini-cli106

codex100

github-copilot97

cursor97

amp88

通过 LiteLLM 代理让 Claude Code 对接 GitHub Copilot 运行 | 高级变通方案指南

36,300 周安装

Python 报告生成器 | 自动化创建专业数据报告与图表 | 支持 PDF/HTML 输出

🇨🇳中文介绍

报告生成器

快速开始

功能特性

API 参考

初始化

相关 Skills

报告元数据

添加内容

文本内容

表格

图表

图像

特殊元素

章节和结构

品牌和样式

模板

生成和导出

模板

执行摘要

季度回顾

项目状态

分析仪表板

CLI 使用

CLI 参数

示例

销售报告

分析仪表板

依赖项

限制

🇺🇸English

Report Generator

Quick Start

Features

API Reference

Initialization

Report Metadata

Adding Content

Text Content

Tables

Charts

Images

Special Elements

Sections and Structure

Branding and Styling

Templates

Generation and Export

Templates

Executive Summary

Quarterly Review

Project Status

Analytics Dashboard

CLI Usage

CLI Arguments

Examples

Sales Report

Analytics Dashboard

Dependencies

Limitations

最新 Skills