merchant

Merchant backend to process payments, run by merchants
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transactions.typ (2677B)

      1 #import "@preview/cetz:0.4.2": canvas, draw, palette
      2 #import "@preview/cetz-plot:0.1.3": plot, chart
      3 #import "@taler-merchant/common:0.0.0": format_timeframe, format_timestamp, format_round_timestamp
      4 
      5 #let form(data) = {
      6   set page(
      7     paper: "a4",
      8     margin: (left: 2cm, right: 2cm, top: 2cm, bottom: 2.5cm),
      9     footer: context [
     10       #grid(
     11         columns: (1fr, 1fr),
     12         align: (left, right),
     13         text(size: 8pt)[],
     14         text(size: 8pt)[
     15           Page #here().page() of #counter(page).final().first()
     16         ]
     17       )
     18     ]
     19   )
     20 
     21   heading(level: 1)[GNU Taler Merchant Accounting: #data.business_name]
     22 
     23   [Transaction report from
     24    #underline([#format_round_timestamp(data.start_date,data.bucket_period.d_us,false)]) to
     25    #underline([#format_round_timestamp(data.end_date,data.bucket_period.d_us,false)])
     26    with
     27    #text(weight: "bold")[#format_timeframe(data.bucket_period.d_us)]
     28    granularity.
     29    ]
     30 
     31   let p = palette.new(colors: (blue, green, yellow, orange, purple, lime, teal, gray, red))
     32   v(1cm)
     33 
     34   for dchart in data.charts {
     35 
     36     heading(level: 2)[#dchart.chart_name]
     37 
     38     let data_groups = dchart.data_groups.map(dg => (
     39        values: dg.values,
     40        start_date_str: format_round_timestamp(dg.start_date,data.bucket_period.d_us, false),
     41        start_date_mini: format_round_timestamp(dg.start_date,data.bucket_period.d_us, true),
     42     ))
     43 
     44     canvas(length: 1cm, {
     45       import draw: *
     46 
     47       chart.columnchart(
     48         size: (12, 8),
     49         label-key: "start_date_mini",
     50         value-key: "values",
     51         x-label: [Time],
     52         y-label: dchart.y_label,
     53         x-tick-step: none,
     54         y-tick-step: auto,
     55         mode : if dchart.cumulative { "stacked" } else { "clustered" },
     56         // alternatives: "clustered" or "basic" or "stacked"
     57         bar-style: p,
     58         data_groups,
     59         labels: dchart.labels,
     60         legend: "east",
     61       )
     62     })
     63 
     64     v(1cm)
     65 
     66     let cols = (auto,) + dchart.labels.map(_ => auto)
     67     if dchart.cumulative {
     68       cols.push(auto)
     69     }
     70 
     71     let aligns = (left,) + dchart.labels.map(_ => right)
     72     if dchart.cumulative {
     73       aligns.push(right)
     74     }
     75 
     76     let header = ([*When*],) + dchart.labels.map(label => [*#label*])
     77     if dchart.cumulative {
     78       header.push([*Total*])
     79     }
     80 
     81     let rows = data_groups.map(entry => {
     82       let row = (entry.at("start_date_str"),)
     83       row += entry.at("values").map(val => str(val))
     84       if dchart.cumulative {
     85         row.push(str(entry.at("values").sum()))
     86       }
     87       row
     88     }).flatten()
     89 
     90     align(center,
     91       table(
     92         columns: cols,
     93         align: aligns,
     94         ..header,
     95         ..rows
     96     ))
     97     v(1cm)
     98 
     99   } // For all charts
    100 
    101 }