Introduction¶

Overview¶

Build the dataset for currency

Pipeline to fetch

• Des: Tỷ giá của 10 ngân hàng.

Targeted coverred

Related to PR 185

Methodology¶

Schema¶

Target:

BankID | *(str, int) Name | str Security | str

BankID | *(str, int) Currency | str Name | str Buy | float Transfer | float Sell | float

Indirect QUote = 1/Direct Quote = 1/

Validate¶

• Check the bank ID

• Check the resource ID

Handler¶

Flow¶

Foreign Key BankID - BankID

[2] Layout

n Banks -> n functions -> pl.DataFrame(Schema)

[3] Functionals

1. Typehint

2. Class enumuration of Bank

from typing import Callable import enum

class Bank(enum.Enum) BIDV = "BIDV" ...

(a) _get_currency_quote_from__ function with _ is bank_id

n Banks -> n Format (API | XML | HTML | Excel |...) -> Structured 1 dataset

argument: at_date (date) the date that get the function

Check:

at_date <= datetime.now() ## timezone

+ zoneinfo -> Zone Asia --> filter

What?

a) Requests -> Fetch - read to memory

b) Convert dataframe (pl.DataFrame - engine)

c) Convert data-type, columns name

/////

-> return: output dataframe

b)

configuration: dict[Type[Bank], Callable] = { # : Callable Bank.BIDV: _get_currency_quote_from_bidv }

CURRENCY: pl.DataFrame = pl.DataFrame([], orient="row")

for bank in Bank:

for _date in range_date:

    func: Callable = configuration.get(bank.name)

    data = func(_date)

    if << condition: data eixist | data.is_empty() is False >>:
        CURRENCY = pl.concat([CURRENCY, data])

CURRENCY <<<<<<<<<<<<<<<<<<

c) Storage local

CURRENCY.write*excel("CURRENCY*{<datetime.now().strftime('%Y%m%d')}.xlsx")

Specification¶

Website: Bank [ Vietcombank | Vietinbank | BIDV | Agribank ]

VCB --- API ----- ok BIDV --- API ----- ok ACB --- API ----- ok Techcombank --- API ----- ok Sacombank --- API ----- ok MBB --- API ----- blocked Agribank --- HTML ----- ok SHB --- HTML ----- ok Vietinbank --- ok

Note: Tỷ giá là gì

USDVND ->

Schema¶

Tỷ giá >

Process¶

Dataset: currency_rate

Dimension:

Date Currency Code

  <Mã ngoại tệ>+<VND>
  USDVND
  EURVND

-> List[Record]

-> Using polars >

Convert dataframe

• Rename: currencyCode -> currency_code (camel_case -> snake_case)

• Convert: string -> float

• <1 day>

For loop: < RANGE: 2000-7-28> ->

Source Reference¶

https://exchangeratesapi.io/