notebookmd-guide

notebookmd API Reference Guide

This is the complete API reference for the notebookmd library. Use this when you need to generate Markdown reports, data analysis, dashboards, or structured documents.

Installation

pip install notebookmd              # Core (zero deps)
pip install "notebookmd[pandas]"    # + tables, DataFrames, CSV
pip install "notebookmd[plotting]"  # + matplotlib charts
pip install "notebookmd[all]"       # Everything

Factory

from notebookmd import nb, NotebookConfig

cfg = NotebookConfig(
    max_table_rows=30,       # Default: 30
    float_format="{:.4f}",   # Default: "{:.4f}"
)
n = nb("output/report.md", title="Report Title", cfg=cfg)

Text Elements

n.title("Title")                           # # Title
n.header("Header", divider=False)          # ## Header (+ --- if divider=True)
n.subheader("Sub", divider=False)          # ### Sub
n.caption("Caption text")                  # _Caption text_
n.text("Preformatted text")                # ```text\nPreformatted text\n```
n.latex(r"\sum_{i=1}^{n} x_i")            # $$\sum_{i=1}^{n} x_i$$
n.md("**Bold** and _italic_")             # Raw markdown passthrough
n.code("print('hello')", lang="python")   # ```python\nprint('hello')\n```
n.divider()                                # ---
n.write("Any text or value")              # Auto-formatted
n.note("Important note")                  # > **Note:** Important note

Data Display

# Single metric with delta
n.metric("Revenue", "$1.2M", delta="+12%")
n.metric("Churn", "2.1%", delta="-0.3%", delta_color="inverse")

# Multiple metrics in a row
n.metric_row([
    {"label": "Revenue", "value": "$1.2M", "delta": "+12%"},
    {"label": "Profit", "value": "$340K", "delta": "+8%"},
    {"label": "Users", "value": "3,400", "delta": "+200"},
])

# DataFrames and tables
n.table(df, name="Table Title", max_rows=30)
n.dataframe(df, name="DataFrame Title")
n.summary(df, title="Auto Summary")  # shape, nulls, numeric stats

# Key-value dictionaries
n.kv({"Key1": "Value1", "Key2": "Value2"}, title="Metrics")

# JSON display
n.json({"key": "value", "nested": {"a": 1}}, expanded=True)