insseption adat-API

curl -sS "https://insse.csaladen.es/api/v1/context?lang=en" | jq .
curl -sS "https://insse.csaladen.es/api/v1/context/1?lang=en" | jq .

from insseption import Client

with Client("https://insse.csaladen.es/api/v1") as c:
    roots = c.context(lang="en")["nodes"]
    print([n["name"] for n in roots])
    kids = c.context("1", lang="en")["nodes"]
    print([n["code"] for n in kids[:5]])

library(httr2)

roots <- request("https://insse.csaladen.es/api/v1/context") |>
  req_url_query(lang = "en") |>
  req_perform() |>
  resp_body_json()
vapply(roots$nodes, \(n) n$name, character(1))

const roots = await (await fetch("https://insse.csaladen.es/api/v1/context?lang=en")).json();
console.log(roots.nodes.map(n => n.name));
const kids = await (await fetch("https://insse.csaladen.es/api/v1/context/1?lang=en")).json();
console.log(kids.nodes.slice(0, 5));

// Power Query > Blank Query > Advanced Editor (angol menünevek)
let
    Source = Json.Document(Web.Contents("https://insse.csaladen.es/api/v1/context", [Query=[lang="en"]])),
    Nodes = Table.FromRecords(Source[nodes])
in
    Nodes

curl -sS "https://insse.csaladen.es/api/v1/matrices/POP105A?lang=en" | jq '.dimensions[] | {dim_code,label}'

from insseption import Client

with Client("https://insse.csaladen.es/api/v1") as c:
    m = c.matrix("POP105A", lang="en")
    print(m["name"])
    for d in m["dimensions"]:
        print(d["dim_code"], d["label"], "options=", len(d["options"]))

library(httr2)

m <- request("https://insse.csaladen.es/api/v1/matrices/POP105A") |>
  req_url_query(lang = "en") |>
  req_perform() |>
  resp_body_json()
cat(m$name, "\n")
lapply(m$dimensions, \(d) c(d$dim_code, d$label, length(d$options)))

const m = await (await fetch("https://insse.csaladen.es/api/v1/matrices/POP105A?lang=en")).json();
console.log(m.name);
console.table(m.dimensions.map(d => ({ code: d.dim_code, label: d.label, n: d.options.length })));

let
    Source = Json.Document(Web.Contents("https://insse.csaladen.es/api/v1/matrices/POP105A", [Query=[lang="en"]])),
    Dims = Table.FromRecords(Source[dimensions])
in
    Dims

curl -sS "https://insse.csaladen.es/api/v1/matrices/POP105A/query?lang=en" | jq '{columns,row_count}'

from insseption import Client

with Client("https://insse.csaladen.es/api/v1") as c:
    data = c.query("POP105A", lang="en")  # empty selections → defaults
    print(data["columns"])
    print(data["row_count"], "rows")
    print(data["rows"][:3])

library(httr2)

data <- request("https://insse.csaladen.es/api/v1/matrices/POP105A/query") |>
  req_url_query(lang = "en") |>
  req_perform() |>
  resp_body_json()
str(data$columns)
length(data$rows)

const data = await (await fetch("https://insse.csaladen.es/api/v1/matrices/POP105A/query?lang=en")).json();
console.log(data.columns, data.row_count);
console.table(data.rows.slice(0, 5));

let
    Source = Json.Document(Web.Contents("https://insse.csaladen.es/api/v1/matrices/POP105A/query", [Query=[lang="en"]])),
    Rows = Table.FromRows(Source[rows], Source[columns])
in
    Rows

curl -sS -X POST "https://insse.csaladen.es/api/v1/matrices/POP105A/query" \
  -H "content-type: application/json" \
  -d '{"lang":"en","selections":{"1":[1],"2":[105],"3":[108],"4":[112],"5":[4931],"6":[9685]}}' \
  | jq '{row_count, rows}' 

from insseption import Client

# az azonosítók: c.matrix(...)["dimensions"][*]["options"][*]["nom_item_id"]
sel = {
    "1": [1],       # age: Total
    "2": [105],     # sex: Total
    "3": [108],     # area: Total
    "4": [112],     # geo: TOTAL
    "5": [4931],    # year: 2026
    "6": [9685],    # unit
}
with Client("https://insse.csaladen.es/api/v1") as c:
    data = c.query("POP105A", selections=sel, lang="en")
    print(data["rows"])

library(httr2)

body <- list(
  lang = "en",
  selections = list(`1` = list(1), `2` = list(105), `3` = list(108),
                    `4` = list(112), `5` = list(4931), `6` = list(9685))
)
data <- request("https://insse.csaladen.es/api/v1/matrices/POP105A/query") |>
  req_body_json(body) |>
  req_perform() |>
  resp_body_json()
data$rows

const body = {
  lang: "en",
  selections: { "1": [1], "2": [105], "3": [108], "4": [112], "5": [4931], "6": [9685] },
};
const data = await (await fetch("https://insse.csaladen.es/api/v1/matrices/POP105A/query", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify(body),
})).json();
console.log(data.rows);

// Prefer GET defaults, or load CSV (next recipe) into Power Query.
// POST bodies are awkward in Excel — use Python/R/curl for selections.

curl -sS -X POST "https://insse.csaladen.es/api/v1/matrices/POP105A/query?format=csv" \
  -H "content-type: application/json" \
  -d '{"lang":"en","selections":{}}' -o pop105a.csv

import io
import pandas as pd
import requests

r = requests.post(
    "https://insse.csaladen.es/api/v1/matrices/POP105A/query",
    params={"format": "csv"},
    json={"lang": "en", "selections": {}},
    timeout=60,
)
r.raise_for_status()
df = pd.read_csv(io.StringIO(r.text))
print(df.head())

library(httr2)
library(readr)

resp <- request("https://insse.csaladen.es/api/v1/matrices/POP105A/query") |>
  req_url_query(format = "csv") |>
  req_body_json(list(lang = "en", selections = setNames(list(), character(0)))) |>
  req_perform()
df <- read_csv(resp_body_string(resp), show_col_types = FALSE)
head(df)

const r = await fetch("https://insse.csaladen.es/api/v1/matrices/POP105A/query?format=csv", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({ lang: "en", selections: {} }),
});
const csv = await r.text();
console.log(csv.split("\n").slice(0, 5).join("\n"));

// Save CSV from curl/Python, then Data > From Text/CSV.
// Or use the GET JSON recipe and convert in Power Query.

curl -sS "https://insse.csaladen.es/api/v1/news" | jq '.items[:5]'

from insseption import Client

with Client("https://insse.csaladen.es/api/v1") as c:
    news = c.news()
    for item in news["items"][:5]:
        print(item["date"], item["code"], item.get("domain"))

library(httr2)
news <- request("https://insse.csaladen.es/api/v1/news") |> req_perform() |> resp_body_json()
head(do.call(rbind, lapply(news$items[1:5], as.data.frame)), 5)

const news = await (await fetch("https://insse.csaladen.es/api/v1/news")).json();
console.table(news.items.slice(0, 8).map(i => ({ date: i.date, code: i.code, domain: i.domain })));

let
    Source = Json.Document(Web.Contents("https://insse.csaladen.es/api/v1/news")),
    Items = Table.FromRecords(Source[items])
in
    Items

# a csomag ezeket a HTTP-hívásokat burkolja
curl -sS "https://insse.csaladen.es/api/v1/meta" | jq .

# pip install insseption
from insseption import Client

c = Client("https://insse.csaladen.es/api/v1")
print(c.health())
print(c.query("POP105A", lang="en")["row_count"])
c.close()

# R users: httr2 against the same URLs (see other recipes).
# There is also CRAN TEMPO for bulk CSV dumps of the whole warehouse.

// fetch against https://insse.csaladen.es/api/v1 — or use the page UI at https://insse.csaladen.es/

// Not applicable — use CSV downloads from the query endpoint.