htmltable enables structured data extraction from HTML tables and URLs and requires almost no external dependencies. Tested with Go 1.18.x and 1.19.x.
go get github.com/nfx/go-htmltableYou can retrieve a slice of header-annotated types using the NewSlice* contructors:
type Ticker struct {
Symbol string `header:"Symbol"`
Security string `header:"Security"`
CIK string `header:"CIK"`
}
url := "https://en.wikipedia.org/wiki/List_of_S%26P_500_companies"
out, _ := htmltable.NewSliceFromURL[Ticker](url)
fmt.Println(out[0].Symbol)
fmt.Println(out[0].Security)
// Output:
// MMM
// 3MAn error would be thrown if there's no matching page with the specified columns:
page, _ := htmltable.NewFromURL("https://en.wikipedia.org/wiki/List_of_S%26P_500_companies")
_, err := page.FindWithColumns("invalid", "column", "names")
fmt.Println(err)
// Output:
// cannot find table with columns: invalid, column, namesAnd you can use more low-level API to work with extracted data:
page, _ := htmltable.NewFromString(`<body>
<h1>foo</h2>
<table>
<tr><td>a</td><td>b</td></tr>
<tr><td> 1 </td><td>2</td></tr>
<tr><td>3 </td><td>4 </td></tr>
</table>
<h1>bar</h2>
<table>
<tr><th>b</th><th>c</th><th>d</th></tr>
<tr><td>1</td><td>2</td><td>5</td></tr>
<tr><td>3</td><td>4</td><td>6</td></tr>
</table>
</body>`)
fmt.Printf("found %d tables\n", page.Len())
_ = page.Each2("c", "d", func(c, d string) error {
fmt.Printf("c:%s d:%s\n", c, d)
return nil
})
// Output:
// found 2 tables
// c:2 d:5
// c:4 d:6Complex tables with row and col spans are natively supported as well. You can annotate string, int, and bool fields. Any bool field value is true if it is equal in lowercase to one of yes, y, true, t.
type AM4 struct {
Model string `header:"Model"`
ReleaseDate string `header:"Release date"`
PCIeSupport string `header:"PCIesupport[a]"`
MultiGpuCrossFire bool `header:"Multi-GPU CrossFire"`
MultiGpuSLI bool `header:"Multi-GPU SLI"`
USBSupport string `header:"USBsupport[b]"`
SATAPorts int `header:"Storage features SATAports"`
RAID string `header:"Storage features RAID"`
AMDStoreMI bool `header:"Storage features AMD StoreMI"`
Overclocking string `header:"Processoroverclocking"`
TDP string `header:"TDP"`
SupportExcavator string `header:"CPU support[14] Excavator"`
SupportZen string `header:"CPU support[14] Zen"`
SupportZenPlus string `header:"CPU support[14] Zen+"`
SupportZen2 string `header:"CPU support[14] Zen 2"`
SupportZen3 string `header:"CPU support[14] Zen 3"`
Architecture string `header:"Architecture"`
}
am4Chipsets, _ := htmltable.NewSliceFromURL[AM4]("https://en.wikipedia.org/wiki/List_of_AMD_chipsets")
fmt.Println(am4Chipsets[2].Model)
fmt.Println(am4Chipsets[2].SupportZen2)
// Output:
// X370
// Varies[c]And the last note: you're encouraged to plug your own structured logger:
htmltable.Logger = func(_ context.Context, msg string, fields ...any) {
fmt.Printf("[INFO] %s %v\n", msg, fields)
}
htmltable.NewFromURL("https://en.wikipedia.org/wiki/List_of_S%26P_500_companies")
// Output:
// [INFO] found table [columns [Symbol Security SEC filings GICSSector GICS Sub-Industry Headquarters Location Date first added CIK Founded] count 504]
// [INFO] found table [columns [Date Added Ticker Added Security Removed Ticker Removed Security Reason] count 308]This library aims to be something like pandas.read_html or table_extract Rust crate, but more idiomatic for Go.