### FinMind DataLoader Example

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Example of using the FinMind DataLoader class in Python to fetch option data, including asynchronous fetching.

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='YOUR_API_TOKEN') # Replace with your actual API token

start = datetime.datetime.now()
df = api.taiwan_option_open_interest_large_traders(
    option_id_list=['TXO', 'TEO'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Python Request Example

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Example of how to fetch Taiwan Option Open Interest Large Traders data using Python's requests library.

```python
import requests
import pandas as pd

url = "https://api.finmindtrade.com/api/v4/data"
token = "YOUR_API_TOKEN" # Replace with your actual API token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanOptionOpenInterestLargeTraders",
    "data_id":"CA",
    "start_date": "2024-09-01",
    "end_date": "2024-09-02",
}

data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

--------------------------------

### Python Request Example

Source: https://finmind.github.io/tutor/TaiwanMarket/ConvertibleBond

Example of how to fetch Taiwan Stock Convertible Bond Daily Overview data using Python's requests library.

```python
import requests
import pandas as pd

url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to get the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockConvertibleBondDailyOverview",
    "data_id":"15131",
    "start_date": "2020-04-01",
    "end_date": "2020-04-10",
}

data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

--------------------------------

### R httr Example

Source: https://finmind.github.io/tutor/TaiwanMarket/ConvertibleBond

Example of how to fetch Taiwan Stock Convertible Bond Daily Overview data using R's httr library.

```r
library(httr)
library(data.table)
library(dplyr)

token = "" # Refer to login to get the token
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockConvertibleBondDailyOverview",
        data_id="15131",
        start_date= "2020-04-01",
        end_date='2020-04-10'
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = response %>% content
df = do.call('cbind',data$data) %>%data.table
head(df)
```

--------------------------------

### Get Taiwan Stock Month Revenue by Stock ID (Python Requests)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

This example shows how to fetch Taiwan stock month revenue data using the requests library in Python. It requires an API token for authentication.

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMonthRevenue",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

--------------------------------

### R httr Example

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Example of how to fetch Taiwan Option Open Interest Large Traders data using R's httr library.

```r
library(httr)
library(data.table)
library(dplyr)

token = "YOUR_API_TOKEN" # Replace with your actual API token
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanOptionOpenInterestLargeTraders",
        data_id="CA",
        start_date= "2024-09-01",
        end_date= "2024-09-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = response %>% content
df = do.call('cbind',data$data) %>%data.table
head(df)
```

--------------------------------

### Retrieve Taiwan Stock PER and PBR Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Examples for fetching Price-to-Earnings and Price-to-Book ratios for specific stocks.

```python
df = api.taiwan_stock_per_pbr(
    stock_id='2330',
    start_date='2020-01-02',
    end_date='2020-04-12',
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockPER",
    "data_id": "2330",
    "start_date": "2020-04-01",
    "end_date": "2020-04-12",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockPER",
        data_id= "2330",
        start_date= "2020-01-02",
        end_date= "2020-04-12"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_per_pbr(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Retrieve Stock Shareholding Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Examples for fetching foreign shareholding data for specific stocks.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_shareholding(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockShareholding",
    "data_id": "2330",
    "start_date": "2020-04-01",
    "end_date": "2020-04-12",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockShareholding",
        data_id= "2330",
        start_date= "2020-01-02",
        end_date="2020-04-12"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_shareholding(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Retrieve Institutional Investors Total Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Examples for fetching total institutional investor data for a specific date range.

```python
df = api.taiwan_stock_institutional_investors_total(
    start_date='2020-04-01',
    end_date='2020-04-12',
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockTotalInstitutionalInvestors",
    "start_date": "2020-04-01",
    "end_date": "2020-04-12",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockTotalInstitutionalInvestors",
        start_date= "2020-01-02",
        end_date='2020-04-12'
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### Retrieve Taiwan Stock Margin Purchase and Short Sale Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Examples for fetching margin purchase and short sale data for specific stocks.

```python
df = api.taiwan_stock_margin_purchase_short_sale(
    start_date='2020-04-01',
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarginPurchaseShortSale",
    "start_date": "2020-04-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarginPurchaseShortSale",
        start_date= "2020-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### GET /data

Source: https://finmind.github.io/llms.txt

Fetches specific financial datasets based on provided parameters.

```APIDOC
## GET /data

### Description
Retrieves financial data for a specific dataset and identifier.

### Method
GET

### Endpoint
/data

### Parameters
#### Query Parameters
- **dataset** (string) - Required - The name of the dataset
- **data_id** (string) - Required - The specific identifier for the data
- **start_date** (string) - Optional - Start date for the data range
- **end_date** (string) - Optional - End date for the data range
- **token** (string) - Optional - Authorization token
```

--------------------------------

### Retrieve Taiwan Stock Holding Shares Per Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Examples for fetching stock holding shares per data, including async support for multiple stocks.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_holding_shares_per(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockHoldingSharesPer",
    "data_id": "2330",
    "start_date": "2020-04-01",
    "end_date": "2020-04-12",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockHoldingSharesPer",
        data_id= "2330",
        start_date= "2020-01-02",
        end_date='2020-04-12'
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_holding_shares_per(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Retrieve Daily Adjusted Stock Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Examples for fetching daily adjusted stock price data for a specific stock ID and date range.

```python
df = api.taiwan_stock_daily_adj(
    stock_id='2330',
    start_date='2020-04-02',
    end_date='2020-04-12'
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockPriceAdj",
    "data_id": "2330",
    "start_date": "2020-04-02",
    "end_date": "2020-04-12",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockPriceAdj",
        data_id= "2330",
        start_date= "2020-04-02",
        end_date= "2020-04-08"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### FinMind DataLoader - Python Library

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Example usage of the FinMind Python DataLoader library for fetching financial data, including asynchronous requests for multiple futures contracts.

```APIDOC
## Python DataLoader Library

### Description
This section demonstrates how to use the FinMind Python DataLoader library to fetch financial data, including futures open interest. It shows how to log in with an API token and make asynchronous requests for multiple futures contracts.

### Method
`DataLoader.taiwan_futures_open_interest_large_traders()`

### Parameters
- **api_token** (string) - Required - Your API token for authentication.
- **futures_id_list** (list of strings) - Required - A list of futures contract IDs (e.g., ['TXF', 'MXF', 'EXF']).
- **start_date** (string) - Required - The start date for the data in YYYY-MM-DD format.
- **end_date** (string) - Required - The end date for the data in YYYY-MM-DD format.
- **use_async** (boolean) - Optional - Set to `True` to enable asynchronous data fetching.

### Request Example (Python)
```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='YOUR_API_TOKEN')

start = datetime.datetime.now()
df = api.taiwan_futures_open_interest_large_traders(
    futures_id_list=['TXF', 'MXF', 'EXF'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

### Response
- The function returns a pandas DataFrame containing the requested financial data. The structure of the DataFrame is as follows:

#### DataFrame Schema
| name | contract_type | buy_top5_trader_open_interest | buy_top5_trader_open_interest_per | buy_top10_trader_open_interest | buy_top10_trader_open_interest_per | sell_top5_trader_open_interest | sell_top5_trader_open_interest_per | sell_top10_trader_open_interest | sell_top10_trader_open_interest_per | market_open_interest | buy_top5_specific_open_interest | buy_top5_specific_open_interest_per | buy_top10_specific_open_interest | buy_top10_specific_open_interest_per | sell_top5_specific_open_interest | sell_top5_specific_open_interest_per | sell_top10_specific_open_interest | sell_top10_specific_open_interest_per | date | futures_id  
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---  
0 | 東證期貨 | 202409 | 93 | 74.4 | 113 | 90.4 | 102 | 81.6 | 118 | 94.4 | 125 | 16 | 12.8 | 16 | 12.8 | 14 | 11.2 | 14 | 11.2 | 2024-09-02 | TJF  
1 | 東證期貨 | 202409 | 133 | 62.7 | 170 | 80.2 | 172 | 81.1 | 194 | 91.5 | 212 | 16 | 7.5 | 16 | 7.5 | 42 | 19.8 | 42 | 19.5 | 2024-09-02 | TJF  

#### Field Descriptions
- **name** (str): 商品名稱 (Product name)
- **contract_type** (str): 到期月份 (Expiration month)
- **buy_top5_trader_open_interest** (int32): 買方前五大交易人合計部位數 (Total open interest for top 5 buying traders)
- **buy_top5_trader_open_interest_per** (float32): 買方前五大交易人合計百分比 (Percentage of open interest for top 5 buying traders)
- **buy_top10_trader_open_interest** (int32): 買方前十大交易人合計部位數 (Total open interest for top 10 buying traders)
- **buy_top10_trader_open_interest_per** (float32): 買方前十大交易人合計百分比 (Percentage of open interest for top 10 buying traders)
- **sell_top5_trader_open_interest** (int32): 賣方前五大交易人合計部位數 (Total open interest for top 5 selling traders)
- **sell_top5_trader_open_interest_per** (float32): 賣方前五大交易人合計百分比 (Percentage of open interest for top 5 selling traders)
- **sell_top10_trader_open_interest** (int32): 賣方前十大交易人合計部位數 (Total open interest for top 10 selling traders)
- **sell_top10_trader_open_interest_per** (float32): 賣方前十大交易人合計百分比 (Percentage of open interest for top 10 selling traders)
- **market_open_interest** (int32): 全市場未沖銷部位數 (Total open interest for the entire market)
- **buy_top5_specific_open_interest** (int32): 買方前五大特定法人合計部位數 (Total open interest for top 5 specific buying institutions)
- **buy_top5_specific_open_interest_per** (float32): 買方前五大特定法人合計百分比 (Percentage of open interest for top 5 specific buying institutions)
- **buy_top10_specific_open_interest** (int32): 買方前十大特定法人合計部位數 (Total open interest for top 10 specific buying institutions)
- **buy_top10_specific_open_interest_per** (float32): 買方前十大特定法人合計百分比 (Percentage of open interest for top 10 specific buying institutions)
- **sell_top5_specific_open_interest** (int32): 賣方前五大特定法人合計部位數 (Total open interest for top 5 specific selling institutions)
- **sell_top5_specific_open_interest_per** (float32): 賣方前五大特定法人合計百分比 (Percentage of open interest for top 5 specific selling institutions)
- **sell_top10_specific_open_interest** (int32): 賣方前十大特定法人合計部位數 (Total open interest for top 10 specific selling institutions)
- **sell_top10_specific_open_interest_per** (float32): 賣方前十大特定法人合計百分比 (Percentage of open interest for top 10 specific selling institutions)
- **date** (str): 日期 (Date)
- **futures_id** (str): 期貨代碼 (Futures ID)
```

--------------------------------

### Retrieve Institutional Investor Data for a Specific Stock

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Examples for fetching institutional investor buy/sell data for a specific stock ID within a date range.

```python
df = api.taiwan_stock_institutional_investors(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12',
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockInstitutionalInvestorsBuySell",
    "data_id": "2330",
    "start_date": "2020-04-01",
    "end_date": "2020-04-12",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockInstitutionalInvestorsBuySell",
        data_id= "2330",
        start_date= "2020-04-01",
        end_date= "2020-04-12"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### Retrieve Taiwan Stock Market Value Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Examples for fetching market value data for specific stocks, restricted to backer and sponsor members.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_market_value(
    stock_id='2330',
    start_date='2023-01-01',
    end_date='2024-01-01'
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarketValue",
    "data_id": "2330",
    "start_date": "2023-01-01",
    "end_date": "2024-01-01",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
    response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarketValue",
        data_id= "2330",
        start_date= "2023-01-01",
        end_date= "2024-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### Retrieve Taiwan Options Daily Data

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Examples for fetching daily options data using the FinMind Python package, direct requests, R, and asynchronous requests.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_option_daily(
    option_id='TXO',
    start_date='2020-04-01',
    end_date='2020-04-02',
)
```

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanOptionDaily",
    "data_id":"TXO",
    "start_date": "2020-04-01",
    "end_date": "2020-04-02",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
token = "" # 參考登入，獲取金鑰
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanOptionDaily",
        data_id="TXO",
        start_date= "2020-04-01",
        end_date= "2020-04-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = response %>% content
df = do.call('rbind',data$data) %>%data.table
```

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_option_daily(
    option_id_list=['TXO', 'TEO'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Fetch All Taiwan Stock Daily Data from a Specific Date via HTTP (Python)

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Retrieves all available daily stock price data starting from a specified date using a direct HTTP GET request. Requires authentication and specifies the dataset and start date.

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockPrice",
    "start_date": "2020-04-06",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
```

--------------------------------

### Initialize DataLoader and Login with Token (Python)

Source: https://finmind.github.io/llms.txt

Initializes the DataLoader and logs in using an API token. Ensure you have obtained your token from finmindtrade.com.

```python
from FinMind.data import DataLoader
api = DataLoader()
api.login_by_token(api_token='your_token')
```

--------------------------------

### Fetch All Taiwan Stock Daily Data from a Specific Date via HTTP (R)

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Retrieves all available daily stock price data starting from a specified date using an HTTP GET request with the httr package in R. Requires authentication and specifies the dataset and start date.

```r
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockPrice",
        start_date= "2020-04-06"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
```

--------------------------------

### Retrieve Daily Tick Data for All Stocks

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Methods for fetching full-day tick data for all stocks, intended for SponsorPro members.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_tick(
    date='2019-01-02',
    use_object=True,
)
```

```python
import requests
import pandas as pd

url = "https://api.finmindtrade.com/api/v4/storage_objects"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockPriceTick",
    "date": '2019-01-02',
}
resp = requests.get(url, headers=headers, params=parameter)
data = pd.read_parquet(io.BytesIO(resp.content))
print(data.head())
```

```r
library(httr)
library(data.table)
library(dplyr)
library(arrow)

url = 'https://api.finmindtrade.com/api/v4/storage_objects'
token = "" # 參考登入，獲取金鑰
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockPriceTick",
        date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
con = content(response, "raw")
data <- read_parquet(con)
close(con)
head(data)
```

--------------------------------

### Async Batch Query for Taiwan Stocks (Python)

Source: https://finmind.github.io/llms.txt

Fetches daily stock data for multiple Taiwan stock IDs concurrently using `use_async=True`. This method is faster for multiple queries. Not supported for all dataset types.

```python
df = api.taiwan_stock_daily(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
```

--------------------------------

### GET /api/v4/data (TaiwanStockDelisting)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Retrieves information about delisted Taiwan stocks.

```APIDOC
## GET /api/v4/data

### Description
Retrieves information about delisted Taiwan stocks.

### Method
GET

### Endpoint
https://api.finmindtrade.com/api/v4/data

### Parameters
#### Query Parameters
- **dataset** (string) - Required - Set to 'TaiwanStockDelisting'

### Request Example
{
  "dataset": "TaiwanStockDelisting"
}

### Response
#### Success Response (200)
- **date** (string) - Date
- **stock_id** (string) - Stock ID
- **stock_name** (string) - Stock Name
```

--------------------------------

### Asynchronous Data Loading for Multiple Stocks

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Demonstrates using the DataLoader with asynchronous requests for multiple stock IDs.

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_institutional_investors(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### GET /datalist

Source: https://finmind.github.io/llms.txt

Lists all available data_id values for a specific dataset.

```APIDOC
## GET /datalist

### Description
Returns a list of available data_id values for a given dataset.

### Method
GET

### Endpoint
/datalist
```

--------------------------------

### Retrieve warrant trading report using async

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Demonstrates asynchronous data loading for warrant trading reports.

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

date = '2025-12-08'
start = datetime.datetime.now()
df = api.taiwan_stock_warrant_trading_daily_report(
    date=date,
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### Get All Taiwan Stock Month Revenue Data (Python)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Fetch monthly revenue data for all stocks within a specified date range. This is useful for broad market analysis. Ensure you are logged in.

```python
from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_month_revenue(
    start_date='2019-04-01',
)
```

--------------------------------

### GET /user_info

Source: https://finmind.github.io/llms-full.txt

Retrieves current API usage statistics and quota limits.

```APIDOC
## GET https://api.web.finmindtrade.com/v2/user_info

### Description
Check current API usage and quota limits.

### Method
GET

### Endpoint
https://api.web.finmindtrade.com/v2/user_info

### Response
#### Success Response (200)
- **user_count** (int) - Current API usage count
- **api_request_limit** (int) - API request limit

### Response Example
{
  "user_count": 150,
  "api_request_limit": 600
}
```

--------------------------------

### GET /translation

Source: https://finmind.github.io/llms.txt

Retrieves the English-Chinese column name mapping for a specific dataset.

```APIDOC
## GET /translation

### Description
Provides a mapping between English and Chinese column names for a dataset.

### Method
GET

### Endpoint
/translation
```

--------------------------------

### Initialize DataLoader

Source: https://finmind.github.io/tutor/TaiwanMarket/ConvertibleBond

Initializes the FinMind DataLoader instance for subsequent data requests.

```python
from FinMind.data import DataLoader

api = DataLoader()
```

--------------------------------

### GET /data

Source: https://finmind.github.io/llms-full.txt

Fetches financial data from a specified dataset based on provided filters.

```APIDOC
## GET /data

### Description
Fetches dataset records based on the provided parameters.

### Method
GET

### Endpoint
/data

### Query Parameters
- **dataset** (str) - Required - The name of the dataset to query
- **data_id** (str) - Optional - Specific identifier for the data
- **start_date** (str) - Optional - Start date in YYYY-MM-DD format
- **end_date** (str) - Optional - End date in YYYY-MM-DD format

### Response
#### Success Response (200)
- **msg** (str) - Status message
- **status** (int) - HTTP status code
- **data** (array) - List of data records

### Response Example
{
  "msg": "success",
  "status": 200,
  "data": [ { ... } ]
}
```

--------------------------------

### GET /api/v4/data (TaiwanStockMarketValue)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Retrieves daily market value data for Taiwan stocks.

```APIDOC
## GET /api/v4/data

### Description
Retrieves daily market value data for Taiwan stocks.

### Method
GET

### Endpoint
https://api.finmindtrade.com/api/v4/data

### Parameters
#### Query Parameters
- **dataset** (string) - Required - Set to 'TaiwanStockMarketValue'
- **start_date** (string) - Optional - Start date in YYYY-MM-DD format

### Request Example
{
  "dataset": "TaiwanStockMarketValue",
  "start_date": "2023-01-03"
}

### Response
#### Success Response (200)
- **date** (string) - Date
- **stock_id** (string) - Stock ID
- **market_value** (int64) - Market Value
```

--------------------------------

### Get All Taiwan Stock Month Revenue Data (Python Requests)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

This Python snippet uses the requests library to fetch monthly revenue data for all stocks within a given date range. Authentication with a token is required.

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMonthRevenue",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
```

--------------------------------

### GET /api/v4/data

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Retrieves Taiwan stock dividend data for a specified date range.

```APIDOC
## GET /api/v4/data

### Description
Retrieves the Taiwan Stock Dividend dataset for a specific date range.

### Method
GET

### Endpoint
https://api.finmindtrade.com/api/v4/data

### Parameters
#### Query Parameters
- **dataset** (string) - Required - The dataset name, use 'TaiwanStockDividend'.
- **start_date** (string) - Required - The start date for the data query (YYYY-MM-DD).

### Request Example
{
  "dataset": "TaiwanStockDividend",
  "start_date": "2025-10-06"
}

### Response
#### Success Response (200)
- **date** (string) - 權利分派基準日
- **stock_id** (string) - 股票代碼
- **year** (string) - 股利所屬年度
- **StockEarningsDistribution** (float64) - 股票股利:盈餘轉增資配股
- **StockStatutorySurplus** (float64) - 股票股利:法定盈餘公積資本公積轉增資配股
- **StockExDividendTradingDate** (string) - 除權交易日
- **CashEarningsDistribution** (float64) - 現金股利:盈餘轉增資配股
- **CashStatutorySurplus** (float64) - 現金股利:法定盈餘公積資本公積轉增資配股
- **CashExDividendTradingDate** (string) - 除息交易日
- **CashDividendPaymentDate** (string) - 現金股利發放日
- **AnnouncementDate** (string) - 公告日期

#### Response Example
{
  "data": [
    {
      "date": "2025-10-06",
      "stock_id": "2540",
      "year": "113年",
      "CashEarningsDistribution": 0.4
    }
  ]
}
```

--------------------------------

### Fetch Taiwan Daily Short Sale Balances (Python)

Source: https://finmind.github.io/tutor/TaiwanMarket/Chip

Retrieves daily short sale balance data for Taiwan stocks. Requires authentication with an API token.

```python
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # 參考登入，獲取金鑰
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanDailyShortSaleBalances",
    "start_date": "2021-05-20",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data)
```

--------------------------------

### Load Multiple Futures Open Interest (Python DataLoader Async)

Source: https://finmind.github.io/tutor/TaiwanMarket/Derivative

Use the FinMind DataLoader with async to fetch open interest for multiple futures contracts. Requires login with an API token.

```python
from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_futures_open_interest_large_traders(
    futures_id_list=['TXF', 'MXF', 'EXF'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)
```

--------------------------------

### GET /api/v4/data (TaiwanStockStatisticsOfOrderBookAndTrade)

Source: https://finmind.github.io/tutor/TaiwanMarket/Technical

Retrieves 5-second interval order book and trade statistics for the Taiwan stock market.

```APIDOC
## GET /api/v4/data

### Description
Retrieves 5-second interval statistics for order book and trade data. Note: Due to data volume, only one day of data is provided per request.

### Method
GET

### Endpoint
https://api.finmindtrade.com/api/v4/data

### Query Parameters
- **dataset** (string) - Required - Set to 'TaiwanStockStatisticsOfOrderBookAndTrade'
- **start_date** (string) - Required - The date to retrieve data for (YYYY-MM-DD)

### Response
#### Success Response (200)
- **Time** (string) - Time of the record
- **TotalBuyOrder** (string) - Cumulative buy order count
- **TotalBuyVolume** (int64) - Cumulative buy volume
- **TotalSellOrder** (int64) - Cumulative sell order count
- **TotalSellVolume** (int64) - Cumulative sell volume
- **TotalDealOrder** (int64) - Cumulative deal order count
- **TotalDealVolume** (int64) - Cumulative deal volume
- **TotalDealMoney** (int64) - Cumulative deal money
- **date** (string) - Date of the record
```

--------------------------------

### GET /api/v4/data (TaiwanStockMarketValueWeight)

Source: https://finmind.github.io/tutor/TaiwanMarket/Fundamental

Retrieves market value weight data for Taiwan stocks (Restricted to backer/sponsor members).

```APIDOC
## GET /api/v4/data

### Description
Retrieves market value weight data for Taiwan stocks.

### Method
GET

### Endpoint
https://api.finmindtrade.com/api/v4/data

### Parameters
#### Query Parameters
- **dataset** (string) - Required - Set to 'TaiwanStockMarketValueWeight'
- **data_id** (string) - Optional - Stock ID
- **start_date** (string) - Optional - Start date
- **end_date** (string) - Optional - End date

### Request Example
{
  "dataset": "TaiwanStockMarketValueWeight",
  "data_id": "2330",
  "start_date": "2024-01-01",
  "end_date": "2025-01-01"
}

### Response
#### Success Response (200)
- **rank** (int64) - Rank
- **stock_id** (string) - Stock ID
- **stock_name** (string) - Stock Name
- **weight_per** (float32) - Weight Percentage
- **date** (string) - Date
- **type** (string) - Market type (twse/tpex)
```