---
title: "Getting Started with comex"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting Started with comex}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)
```

## Overview

The **comex** package provides an R interface to the
[ComexStat API](https://comexstat.mdic.gov.br/) from the Brazilian
Ministry of Development, Industry, Trade and Services (MDIC). It gives
you programmatic access to:
 
- **General trade data** — exports and imports from 1997 to present,
  with 22 detail/grouping fields and 6 metrics.
- **City-level trade data** — trade statistics broken down by
  municipality.
- **Historical data** — export/import records from 1989 to 1996
  using the older NBM nomenclature.
- **Auxiliary lookup tables** — countries, economic blocs, states,
  cities, transport modes, customs units, and product nomenclatures
  (NCM, NBM, HS, CGCE, SITC).

The package has only two dependencies (`httr2` and `cli`) and does not
require a headless browser or any external software.

## Installation

```{r install}
# Install from GitHub:
remotes::install_github("StrategicProjects/comexr")
```

## Quick start

### 1. Check what data is available

Before querying, you can discover the date range, available grouping
fields (details), and metrics for each data type:

```{r discover}
library(comex)

# What is the most recent data available?
comex_last_update("general")
#> $updated
#> [1] "2026-02-05"
#> $year
#> [1] "2026"
#> $monthNumber
#> [1] "01"

# What years are covered?
comex_available_years("general")
#> $max
#> [1] "2026"
#> $min
#> [1] "1997"

# What detail/grouping fields can I use?
comex_details("general")
#> # A tibble: 22 × 2
#>    filter        text
#>    <chr>         <chr>
#>  1 country       Countries
#>  2 economicBlock Economic Blocks
#>  3 state         States
#>  4 ...
```

### 2. Run a simple export query

The easiest way to query is with `comex_export()` and `comex_import()`:

```{r simple_query}
# Top export destinations in January 2024
exports <- comex_export(
  start_period = "2024-01",
  end_period   = "2024-01",
  details      = "country"
)

exports
#> # A tibble: 219 × 4
#>    year  country                   metricFOB metricKG
#>    <chr> <chr>                         <dbl>    <dbl>
#>  1 2024  China                    7812623070    ...
#>  2 2024  United States            3254810234    ...
#>  3 2024  Argentina                 916456789    ...
#>  ...
```

### 3. Add filters and multiple details

```{r filtered_query}
# Exports to China and USA, broken down by HS4 product group
exports_filtered <- comex_export(
  start_period = "2024-01",
  end_period   = "2024-06",
  details      = c("country", "hs4"),
  filters      = list(country = c(160, 249)),
  month_detail = TRUE
)
```

Filter codes come from the auxiliary tables — use `comex_countries()`,
`comex_states()`, etc. to look them up.

### 4. Look up auxiliary tables

```{r tables}
# All countries
countries <- comex_countries()
countries
#> # A tibble: 281 × 2
#>    id    text
#>    <chr> <chr>
#>  1 994   A Designar
#>  2 132   Afeganistão
#>  ...

# Search for a specific country
comex_countries(search = "Brazil")
```

## Available detail names

The `details` parameter accepts user-friendly names that are mapped to
the API's internal names. Here is the full list:

| User name | API name | Available in |
|---|---|---|
| `country` | country | general, city, historical |
| `bloc` / `economic_block` | economicBlock | general, city |
| `state` | state | general, city |
| `city` | city | city |
| `transport_mode` | transportMode | general |
| `customs_unit` | urf | general |
| `ncm` | ncm | general |
| `hs6` / `sh6` | sh6 | general |
| `hs4` / `sh4` | sh4 | general |
| `hs2` / `sh2` | sh2 | general |
| `section` | section | general, city |
| `cgce_n1` / `cgce_n2` / `cgce_n3` | cgceN1/N2/N3 | general |
| `sitc_section` ... `sitc_item` | cuciSection...cuciItem | general |
| `isic_section` ... `isic_class` | isicSection...isicClass | general |
| `nbm` | nbm | historical |
| `company_size` | companySize | general |

**Note:** City endpoint uses `heading` (≈HS4), `chapter` (≈HS2),
`section` — not sh2/sh4/sh6. Use `comex_details("city")` to confirm.

## Language support

All functions accept a `language` parameter. Use `"pt"` (Portuguese),
`"en"` (English), or `"es"` (Spanish):
  
```{r language}
comex_blocs(language = "pt")
#> # A tibble: 12 × 2
#>    id    text
#>    <chr> <chr>
#>  1 105   América Central e Caribe
#>  2 107   América do Norte
#>  ...

comex_blocs(language = "en")
#> # A tibble: 12 × 2
#>    id    text
#>    <chr> <chr>
#>  1 105   Central America and Caribbean
#>  2 107   North America
#>  ...
```

## Next steps

- See `vignette("querying-trade-data")` for advanced query patterns
  including monthly breakdowns, multiple metrics, CIF values, and
  working with city and historical endpoints.
- See `vignette("auxiliary-tables")` for a tour of all lookup tables
  (NCM, HS, countries, blocs, classifications).
