import json
import requests
import pandas as pd

data_source_id = "f3c47953-07bc-45d2-a91e-8f4dbbf7d2b1"
token = "Bearer <your API token>"
IMPORT_API_URL = "https://data.igniteprocurement.com" 

### Method to send a dataframe or data to Ignite
def upload_data_ignite(
  data,
  data_source_id,
  token,
  import_name,
  delete_query_id
):

  if isinstance(data, pd.DataFrame):
    json_data = json.loads(
        data.to_json(orient="records", force_ascii=False) 
     )
  else:
    json_data = data
    
  
  headers = {
    "Authorization" : token,
    "Content-Type": "application/json"
  }
 
  body = {
    "dataRepositoryId": data_source_id, # data repo = data source
    "data": json_data,
    "importName": import_name
  }
 
  if delete_query_id:
     body["deleteQueryId"]= delete_query_id

  payload = json.dumps(body)

  response = requests.post(
    url=f"{IMPORT_API_URL}/import/",
    headers=headers,
    data=payload
  )

  print(response.text)
   
  return response

 
### invoking the method using the parameters defined at the top
response = upload_data_ignite(
 data,
 data_source_id,
 token,
 import_name = "demo_import_42_2023-12-24.json",
 delete_query_id=""
)

### We advise that you properly understand how to use this code before using or copying

import time
import requests

BASE_URL = "https://datatable.igniteprocurement.com"
headers = {"Authorization": "Bearer <your API token>"}

### Send a request, and retry server errors (5xx) after a short delay
def send(method, path, body=None):
  for attempt in range(5):
    response = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if response.status_code < 500:
      return response
    time.sleep(2 ** attempt)
  response.raise_for_status()

### 1. List the tables and columns you can export
response = send("GET", "/tables/")
response.raise_for_status()
for table in response.json():
  print(table["id"], [column["name"] for column in table["columns"]])

### 2. Read spend rows, one page at a time
body = {
  "fields": ["id", "transaction_date", "amount", "supplier_name"],
  "filters": {"transaction_date": {"gte": "2026-01-01"}},
  "sort": [{"field": "transaction_date", "direction": "desc"}],
  "pageSize": 1000
}

rows = []
while True:
  response = send("POST", "/tables/spend/rows", body)
  if response.status_code in (400, 410) and response.json().get("code") == "page_token_expired":
    ### The page token expired: start again from the first page
    rows = []
    body.pop("pageToken", None)
    continue
  response.raise_for_status()
  page = response.json()
  rows.extend(page["data"])
  if "nextPageToken" not in page:
    break
  body["pageToken"] = page["nextPageToken"]

print(len(rows))

import time
import requests

BASE_URL = "https://datatable.igniteprocurement.com"
headers = {"Authorization": "Bearer <your API token>"}

### Send a request, and retry server errors (5xx) after a short delay
def send(method, path, body=None):
  for attempt in range(5):
    response = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if response.status_code < 500:
      return response
    time.sleep(2 ** attempt)
  response.raise_for_status()

### 1. Start the export
response = send("POST", "/tables/spend/exports", {"format": "json"})
response.raise_for_status()
export_id = response.json()["id"]

### 2. Poll until it has finished, for at most 1 hour
deadline = time.time() + 60 * 60
while True:
  response = send("GET", f"/table-exports/{export_id}")
  response.raise_for_status()
  status = response.json()
  if status["status"] in ("succeeded", "failed"):
    break
  if time.time() > deadline:
    raise SystemExit(f"Export {export_id} did not finish within 1 hour")
  time.sleep(10)

if status["status"] == "failed":
  raise SystemExit(f"Export failed: {status.get('error')}")

### 3. Download the files (the download links need no token)
for file in status["files"]:
  with requests.get(file["downloadUrl"], stream=True) as download:
    download.raise_for_status()
    with open(f"{export_id}-{file['name']}", "wb") as f:
      for chunk in download.iter_content(chunk_size=1024 * 1024):
        f.write(chunk)