1. Degiro Connector

This is yet another library to access Degiro's API.

Notes :

• Migration scripts are available :

python -m degiro_connector.migration.from_0_1_3_to_1_0_0
python -m degiro_connector.migration.from_1_0_4_to_1_0_5
python -m degiro_connector.migration.from_1_0_10_to_2_0_0
python -m degiro_connector.migration.from_2_0_2_to_2_0_3

• GRPC services are available to let you consume this library through other languages like Javascript, Java, Go, C++, Rust, etc :

python -m examples.quotecast.relay_server
python -m examples.trading.relay_server

1.1. Which features ?

Here are the features you can access through this library :

1.2. How to install ?

pip install degiro-connector

1.3. How to upgrade ?

pip install --no-cache-dir --upgrade degiro-connector

1.4. How to uninstall ?

pip uninstall degiro-connector

1.5. Table of contents

• 1. Degiro Connector
  • 1.1. Which features ?
  • 1.2. How to install ?
  • 1.3. How to upgrade ?
  • 1.4. How to uninstall ?
  • 1.5. Table of contents
• 2. Real-time data
  • 2.1. What are the workflows ?
  • 2.2. What are the credentials ?
  • 2.3. How to find your : user_token ?
  • 2.4. How to login ?
  • 2.5. Is there a timeout ?
  • 2.6. How to subscribe to a data-stream ?
  • 2.7. How to unsubscribe to a data-stream ?
  • 2.8. How to fetch the data ?
  • 2.9. How to use this data ?
  • 2.10. Which are the available data types ?
  • 2.11. What is a Ticker ?
  • 2.12. What is inside the Dictionary ?
  • 2.13. What is inside the DataFrame ?
  • 2.14. How to get chart data ?
  • 2.15. How to find a : vwd_id ?
• 3. Trading connection
  • 3.1. How to login ?
  • 3.2. How to logout ?
  • 3.3. What are the credentials ?
  • 3.4. How to find your : int_account ?
  • 3.5. How to use 2FA ?
  • 3.6. How to find your : totp_secret_key ?
  • 3.7. How to find your : one_time_password ?
  • 3.8. Is there a timeout ?
  • 3.9. How to manage : TimeoutError ?
• 4. Order
  • 4.1. How to create an Order ?
  • 4.1.1. Check Order
  • 4.1.2. Confirm Order
  • 4.2. How to update an Order ?
  • 4.3. How to delete an Order ?
• 5. Portfolio
  • 5.1. How to retrieve pending Orders ?
  • 5.2. How to get the Portfolio ?
  • 5.3. How to get the TotalPortfolio ?
  • 5.4. How to retrieve the OrdersHistory ?
  • 5.5. How to retrieve the TransactionsHistory ?
• 6. Account
  • 6.1. How to retrieve the table : Config ?
  • 6.2. How to retrieve the table : ClientDetails ?
  • 6.3. How to retrieve the table : AccountInfo ?
  • 6.4. How to get the table : AccountOverview ?
  • 6.5. How to export the table : CashAccountReport ?
  • 6.6. How to export the table : PositionReport ?
• 7. Products
  • 7.1. How to get the table : ProductsConfig ?
  • 7.2. How to get my favourite products ?
  • 7.3. How to lookup products (search by name) ?
  • 7.4. How to search bonds ?
  • 7.5. How to search etfs ?
  • 7.6. How to search funds ?
  • 7.7. How to search futures ?
  • 7.8. How to search leverageds ?
  • 7.9. How to search options ?
  • 7.10. How to search stocks ?
  • 7.11. How to search warrants ?
  • 7.12. How to search products from ids ?
  • 7.13. How to create a favourite list ?
  • 7.14. How to delete a favourite list ?
  • 7.15. How to put favourite list products ?
  • 7.16. How to delete favourite list products ?
• 8. Companies
  • 8.1. How to get : CompanyProfile ?
  • 8.2. How to get : CompanyRatios ?
  • 8.3. How to get : FinancialStatements ?
  • 8.4. How to get : LatestNews ?
  • 8.5. How to get : TopNewsPreview ?
  • 8.6. How to get : NewsByCompany ?
  • 8.7. How to get : Agenda ?
  • 8.8. How to get : EstimatesSummaries ?
• 9. Contributing
• 10. License

2. Real-time data

It is possible to fetch a stream of data in real-time from Degiro's API.

For instance if one needs the following data from the "AAPL" stock :

• LastDate
• LastTime
• LastPrice
• LastVolume

You can use this library to retrieve updates like this :

LastDate    LastTime    LastPrice LastVolume
2020-11-13  22:00:00    119.26    4697040

For a list of available metrics, see the example in section 2.6.

2.1. What are the workflows ?

This is the workflow for consuming real-time data-stream :

A. Find your "user_token".
B. Setup the API object with your "user_token".
C. Connect.
D. Subscribe to data-stream.
E. Fetch data-stream.

This is the worflow for consuming charts :

A. Find your "user_token".
B. Setup the API object with your "user_token".
C. Fetch charts.

All the details of these steps are explained in the rest of this section.

2.2. What are the credentials ?

The only credential you need in order to fetch real-time data and charts is the :

• user_token

Beware, these two identifiers are not the same thing :

• user_token : used to fetch real-time data and charts.
• int_account : used for some trading operations.

2.3. How to find your : user_token ?

You can find your "user_token" inside one of these tables :

• "Config" : attribute "clientId"
• "ClientDetails" : attribute "id"

See sections related to "Config" and "ClientDetails" tables.

2.4. How to login ?

In order to fetch data you need to establish a connection.

You can use the following code to connect :

# SETUP QUOTECAST API
quotecast_api = API(user_token=YOUR_USER_TOKEN)

# CONNECTION
quotecast_api.connect()

2.5. Is there a timeout ?

Connection timeout is around 15 seconds.

Which means a connection will cease to work after this timeout.

This timeout is reset each time you use this connection to :

• Subscribe to a metric (for instance a stock Price)
• Fetch the data-stream

So if you use it nonstop (in a loop) you won't need to reconnect.

2.6. How to subscribe to a data-stream ?

To subscribe to a data-stream you need to setup a Request message.

A Request has the following parameters :

Here is an example of a request :

request = Quotecast.Request()
request.subscriptions['360015751'].extend([
    'LastDate',
    'LastTime',
    'LastPrice',
    'LastVolume',
    'AskPrice',
    'AskVolume',
    'LowPrice',
    'HighPrice',
    'BidPrice',
    'BidVolume'
])
request.subscriptions['AAPL.BATS,E'].extend([
    'LastDate',
    'LastTime',
    'LastPrice',
    'LastVolume',
    'AskPrice',
    'AskVolume',
    'LowPrice',
    'HighPrice',
    'BidPrice',
    'BidVolume'
])

In this example these are the vwd_id of the products from which you want Real-time data :

• 360015751
• AAPL.BATS,E

See the section related to vwd_id for more information.

Once you have built this Request object you can send it to Degiro's API like this :

quotecast_api.subscribe(request=request)

For more comprehensive examples : realtime_poller.py / realtime_one_shot.py

2.7. How to unsubscribe to a data-stream ?

To remove metrics from the data-stream you need to setup a Request message.

If you try to unsubscribe to a metric to which you didn't subscribed previously it will most likely have no impact.

A Request has the following parameters :

Here is an example of a request :

request = Quotecast.Request()
request.unsubscriptions['360015751'].extend([
    'LastDate',
    'LastTime',
    'LastPrice',
    'LastVolume',
    'AskPrice',
    'AskVolume',
    'LowPrice',
    'HighPrice',
    'BidPrice',
    'BidVolume'
])
request.unsubscriptions['AAPL.BATS,E'].extend([
    'LastDate',
    'LastTime',
    'LastPrice',
    'LastVolume',
    'AskPrice',
    'AskVolume',
    'LowPrice',
    'HighPrice',
    'BidPrice',
    'BidVolume'
])

Once you have built this Request object you can send it to Degiro's API like this :

quotecast_api.subscribe(request=request)

For more comprehensive examples : realtime_poller.py / realtime_one_shot.py

2.8. How to fetch the data ?

You can use the following code :

quotecast = quotecast_api.fetch_data()

For a more comprehensive example : realtime_poller.py

2.9. How to use this data ?

Received data is a Quotecast object with the following properties :

Here is how to access these properties :

json_data = quotecast.json_data
response_datetime = quotecast.metadata.response_datetime
request_duration= quotecast.metadata.request_duration

Notes:

• The API sometimes might return an empty Quotecast object.
• The API often returns a subset of the requested metrics, e.g. only 'LastPrice'. Please take this into account when appending consecutive data responses.

2.10. Which are the available data types ?

This library provides the tools to convert Degiro's JSON data into something more programmer-friendly.

Here is the list of available data types :

Here is how to build each type :

# UPDATE PARSER
quotecast_parser.put_quotecast(quotecast=quotecast)

# BUILD TICKER
ticker = quotecast_parser.ticker

# BUILD DICT
ticker_dict = quotecast_parser.ticker_dict

# BUILD PANDAS.DATAFRAME
ticker_df = quotecast_parser.ticker_df

2.11. What is a Ticker ?

The generated Ticker contains :

Here are some operations available :

product = '360015751'
metric_name = 'LastPrice'

# ACCESS SPECIFIC PRODUCT
product = ticker.products[product]

# ACCESS SPECIFIC METRIC
metric = product[metric_name]

# LOOP OVER PRODUCTS
for product in ticker.products:
    product = ticker.products[product]

# LOOP OVER METRICS
for metric_name in product.metrics:
    metric = product.metrics[metric_name]

A Ticker is a custom Protocol Buffer Message built for this library.

It can be transmitted over GRPC framework.

2.12. What is inside the Dictionary ?

The dictionary representation of a ticker contains the metrics grouped by "vwd_id" (product id), with :

• keys : vwd_id
• values : another dictionary with the metrics concerning this specific product.

Example - Dictionary :

{
    '360114899': {
        'vwd_id': 360114899,
        'response_datetime': '2020-11-08 12:00:27',
        'request_duration': 1.0224891666870117,
        'LastDate': '2020-11-06',
        'LastTime': '17:36:17',
        'LastPrice': '70.0',
        'LastVolume': '100'
    },
    '360015751': {
        'vwd_id': 360015751,
        'response_datetime': '2020-11-08 12:00:27',
        'request_duration': 1.0224891666870117,
        'LastDate': '2020-11-06',
        'LastTime': '17:36:17',
        'LastPrice': '22.99',
        'LastVolume': '470'
    }
}

2.13. What is inside the DataFrame ?

In addition to whatever metrics you have chosen to subscribe to (see the example in section 2.6), the DataFrame will contain the following columns :

Example - DataFrame :

       vwd_id    response_datetime  request_duration    LastDate  LastTime LastPrice LastVolume
0   360114899  2020-11-08 12:00:27          1.022489  2020-11-06  17:39:57      70.0        100
1   360015751  2020-11-08 12:00:27          1.022489  2020-11-06  17:36:17     22.99        470

2.14. How to get chart data ?

You can fetch an object containing the same data than in Degiro's website graph.

For that you need to prepare a Chart.Request object.

Here is a table with the available attributes for Chart.Request.

Example of code :

request = Chart.Request()
request.culture = "fr-FR"
request.period = Chart.Interval.PT1H
request.requestid = "1"
request.resolution = Chart.Interval.P1D
# request.series.append("issueid:360148977")
# request.series.append("price:issueid:360148977")
request.series.append("ohlc:issueid:360148977")
# request.series.append("volume:issueid:360148977")
# request.series.append("vwdkey:AAPL.BATS,E")
# request.series.append("price:vwdkey:AAPL.BATS,E")
# request.series.append("ohlc:vwdkey:AAPL.BATS,E")
# request.series.append("volume:vwdkey:AAPL.BATS,E")
request.tz = "Europe/Paris"

# FETCH DATA
chart = quotecast_api.get_chart(
    request=request,
    override={
        "resolution": "P1D",
        "period": "P1W",
    },
    raw=True,
)

The issueid parameter is the vwd_id of the product from which you want the Chart data.

See the section related to vwd_id for more information.

All the options for the enumerations are available in this file : quotecast.proto

For a more comprehensive examples :

• chart.py
• chart_format.py

2.15. How to find a : vwd_id ?

In operations related to Quotecast, Degiro uses the vwd_id to identify a product.

Which means that if you want a Chart or Real-time data for a specific product : you first need to find this product's vwd_id.

This two identifiers are not the same :

Here are some methods you can use to fetch a product's vwd_id :

• product_search
• get_products_info

The method product_search let you use the name or other attributes of a product to fetch it's vwd_id.

The method get_products_info let you use a product's id to fetch it's vwd_id.

3. Trading connection

This library is divided into two modules :

• quotecast : to consume real-time financial data.
• trading : to manage your Degiro's account.

The module quotecast is described in the section related to real-time data.

The rest of this document will only refer to the module : trading.

3.1. How to login ?

In order to use the module trading.api you need to establish a connection.

Check the section related to int_account to understand how to get yours.

Here is how to connect :

# SETUP CREDENTIALS
credentials = Credentials(
    username = YOUR_USERNAME,
    password = YOUR_PASSWORD,
    int_account = YOUR_INT_ACCOUNT,  # OPTIONAL FOR LOGIN
)

# SETUP TRADING API
trading_api = API(credentials=credentials)

# ESTABLISH CONNECTION
trading_api.connect()

For a more comprehensive example : connection.py

3.2. How to logout ?

Once you no longer need to use the API you can destroy your connection.

You can use the following code to disconnect :

# DESTROY CONNECTION
trading_api.logout()

For a more comprehensive example : logout.py

3.3. What are the credentials ?

Some credentials are required to use Degiro's trading API.

Here are these credentials :

Check the section related to int_account to understand how to get yours.

Check the section related to 2FA if you want to know more about these two parameters :

• totp_secret_key
• one_time_password

3.4. How to find your : int_account ?

To get your int_acccount you can run this example : client_details_table.py

See section related to ClientDetails table for more details.

This int_acccount is required to do most of the trading operations available in this connector.

Here are some operations for which your int_acccount is not required :

• Connection
• Fetch table : ClientDetails
• Fetch table : Config

Beware, these two identifiers are not the same thing :

• user_token : used to fetch real-time data and charts.
• int_account : used for some trading operations.

3.5. How to use 2FA ?

First I will briefly explain what is : Two-Factor Authentication (2FA).

I recommend to skip a few paragraphs if you already know what is 2FA.

In a standard connection you are providing two parameters :

• username
• password

If you use Two-Factor Authentication (2FA) you need an extra parameter :

• one_time_password

This one_time_password has a validity of 30 secondes and is generated using a totp_secret_key code.

This totp_secret_key code is provided in Degiro's website when you enable 2FA : it is the QRCode.

Usually you put this QRCode inside an app like ‎Google Authenticator.

‎Google Authenticator generates a one_time_password that you can to log in.

To use 2FA with this library you have two solution.

SOLUTION 1

Provide your totp_secret_key : the library will use it to generate a new one_time_password at each connection.

So you won't have to type your one_time_password manually at each connection.

This is the proper way.

See the section about totp_secret_key to understand how to get yours.

Here is an example of connection with the totp_secret_key :

# SETUP CREDENTIALS
credentials = Credentials(
    username=YOUR_USERNAME,
    password=YOUR_PASSWORD,
    int_account=YOUR_INT_ACCOUNT,  # OPTIONAL FOR LOGIN
    totp_secret_key=YOUR_2FA_SECRET_KEY,  # ONLY IF 2FA IS ENABLED
)

# SETUP TRADING API
trading_api = API(credentials=credentials)

# ESTABLISH CONNECTION
trading_api.connect()

A complete example here : connection_2fa.py

SOLUTION 2

Provide a new one_time_password at each connection.

Here is an example of connection with the one_time_password :

# SETUP CREDENTIALS
credentials = Credentials(
    username=YOUR_USERNAME,
    password=YOUR_PASSWORD,
    int_account=YOUR_INT_ACCOUNT,  # OPTIONAL FOR LOGIN
    one_time_password=YOUR_2FA_OTP,  # ONLY IF 2FA IS ENABLED
)

# SETUP TRADING API
trading_api = API(credentials=credentials)

# ESTABLISH CONNECTION
trading_api.connect()

A complete example here : connection_otp.py

3.6. How to find your : totp_secret_key ?

The parameter totp_secret_key is only required if you have enabled 2FA on Degiro's website.

When you try to activate 2FA on Degiro's website, it displays a QRCode.

This QRCode changes at each activation.

A QRCode is a picture which can be converted into a text.

You can download this QRCode and use a tool to extract the text from it.

This extracted text will look like this :

otpauth://totp/DEGIRO:YOUR_USERNAME?algorithm=SHA1&issuer=DEGIRO&secret=YOUR_TOPT_SECRET_KEY&digits=6&period=30

Has you can guess the "totp_secret_key" is in this part :

secret=YOUR_TOPT_SECRET_KEY

Here is an example of script that extracts the text from a QRCode : qrcode.py

3.7. How to find your : one_time_password ?

The parameter one_time_password is the password you type when you log in the website using 2FA.

Usually you get it through an app like Google Authenticator.

It is preferable to use the parameter totp_secret_key instead of one_time_password.

3.8. Is there a timeout ?

A connection for trading operations has a timeout of 30 minutes. It's defined in seconds as constant timeouts.TRADING_TIMEOUT.

The timeout period is started when the TradingAPI.connect() results successfully.

Every time an operation is made to this TradingAPI connection, the timeout for this connection will be reset.

If a TradingAPI connection is left unused during the timeout period, the connection will expire. Every consecutive function call to the TraderAPI will then throw a TimeoutError exception.

A connection timeout might occur when your trading strategy only performs a few trades per day, e.g. once per hour. So when finally a buy opportuntiy occurs, check_order():

# FETCH CHECKING_RESPONSE
checking_response = trading_api.check_order(order=order)

Will fail with TimeoutError:

TimeoutError: Connection has probably expired.

3.9. How to manage : TimeoutError ?

HANDLE EXCEPTION

It's recommended to catch the TimeoutError on every function call to the TradingAPI.

When it's detected, it's sufficient to call connect() again, followed by repeating the original call that threw the exception. Example for the check_order() call:

try:
    checking_response = trading_api.check_order(order=order)
except TimeoutError:
    logging.warning("TradingAPI session did timeout, reconnecting for new session ID...")
    trading_api.connect()
    checking_response = trading_api.check_order(order=order)

This shows the following in the log, while the order is checked successfully after a successful reconnect:

WARNING - TradingAPI session did timeout, reconnecting for new session ID...
INFO - get_session_id:response_dict: {'isPassCodeEnabled': False, 'locale': 'nl_NL', 'redirectUrl': 'https://trader.degiro.nl/trader/', 'sessionId': '2BADBBEF3****', 'status': 0, 'statusText': 'success'}
INFO - confirmation_id: "053df7cf-****"
response_datetime {
  seconds: 1643801134
  nanos: 715765000
}

REFRESH TIMEOUT

As mentioned before, the timeout will be reset after each call to the TradingAPI. This provides the opportunity to make a periodic function call, for example every 10 minutes to get_update().

However, this might interfere with your other logic and might not be robust over time when DeGiro decides to decrease the timeout on their server.

Therefor it's strongly recommended to always incorporate the exception handling for TimeoutError as indicated in the example above.

CHANGE PERIOD

It's possible to change the timeout period while creating the TradingAPI. Just add a ModelConnection object for parameter connection_storage:

# SETUP TRADING API
trading_api = TradingAPI(
    credentials=credentials,
    connection_storage=ModelConnection(
        timeout=600,
    )
)

# Connect:
trading_api.connect()

The connection will now expire after 10 minutes (10 * 60 s).

4. Order

Creating and updating of orders is done with an Order object. Here are the parameters:

The full description of an Order is available here : trading.proto

4.1. How to create an Order ?

The order creation is done in two steps :

1. Checking : send the Order to the API to check if it is valid.
2. Confirmation : confirm the creation of the Order.

Keeping these two steps (instead of reducing to one single "create" function) provides more options.

4.1.1 Check order

Use the check_order() function of the Trading API:

Request parameters

Response parameters

On a succesfull request, a dict with the following parameters is returned:

When the request fails, None is returned.

4.1.2 Confirm order

Use the confirm_order() function of the Trading API:

Request parameters

Response parameters

On a succesfull request, a dict with the following parameters is returned:

When the request fails, None is returned.

4.1.3 Example of combining these functions

# SETUP ORDER
order = Order(
    action=Order.Action.BUY,
    order_type=Order.OrderType.LIMIT,
    price=10,
    product_id=71981,
    size=1,
    time_type=Order.TimeType.GOOD_TILL_DAY,
)

# FETCH CHECKING_RESPONSE
checking_response = trading_api.check_order(order=order)

# EXTRACT CONFIRMATION_ID
confirmation_id = checking_response.confirmation_id

# SEND CONFIRMATION
confirmation_response = trading_api.confirm_order(
    confirmation_id=confirmation_id,
    order=order,
)

For a more comprehensive example : order.py

4.2. How to update an Order ?

To modify a specific Order, you need to set it up with the order_id from the confirm_order() response and use the update_order() function of the Trading API:

Request parameters

Response parameters

On a succesfull request, a bool with the value True is returned.

When the request fails, None is returned. A valid reason is that the pending order has been already executed on the exchange, and this order_id no longer exists.

Here is an example:

# ORDER SETUP
order = Order(
    id=YOUR_ORDER_ID,   # `order_id` from `confirm_order()` response
    action=Order.Action.BUY,
    order_type=Order.OrderType.LIMIT,
    price=10.60,
    product_id=71981,
    size=1,
    time_type=Order.TimeType.GOOD_TILL_DAY,
)

# UPDATE ORDER
succcess = trading_api.update_order(order=order)

4.3. How to delete an Order ?

To delete a specific Order you just need the order_id from the confirm_order() response and use the delete_order() function of the Trading API:

Request parameters

Response parameters

On a succesfull request, a bool with the value True is returned.

When the request fails, None is returned. A valid reason is that the pending order has been already executed on the exchange, and this order_id no longer exists.

Here is an example:

# DELETE ORDER
succcess = trading_api.delete_order(order_id=YOUR_ORDER_ID) # `order_id` from `confirm_order()` response

5. Portfolio

5.1. How to retrieve pending Orders ?

This is how to get the list of Orders currently created but not yet executed or deleted :

request_list = Update.RequestList()
request_list.values.extend([
    Update.Request(option=Update.Option.ORDERS, last_updated=0),
])

update = trading_api.get_update(request_list=request_list)
update_dict = pb_handler.message_to_dict(message=update)
orders_df = pd.DataFrame(update_dict['orders']['values'])

Example : Orders

   product_id      time_type  price  size                                    id  ...  action  order_type stop_price retained_order  sent_to_exchange
0           0  GOOD_TILL_DAY      2     3  202cb962-ac59-075b-964b-07152d234b70  ...     BUY       LIMIT         16             17                18

For a more comprehensive example : update.py

5.2. How to get the Portfolio ?

This is how to list the stocks/products currently in the portfolio :

request_list = Update.RequestList()
request_list.values.extend([
    Update.Request(option=Update.Option.PORTFOLIO, last_updated=0),
])

update = trading_api.get_update(request_list=request_list)
update_dict = pb_handler.message_to_dict(message=update)
portfolio_df = pd.DataFrame(update_dict['portfolio']['values'])

For a more comprehensive example : update.py

Note: In order to resolve product IDs to Human readable names, see 7.12. How to search products from ids ?

5.3. How to get the TotalPortfolio ?

This is how to get aggregated data about the portfolio :

request_list = Update.RequestList()
request_list.values.extend([
    Update.Request(option=Update.Option.TOTALPORTFOLIO, last_updated=0),
])

update = trading_api.get_update(request_list=request_list)
update_dict = pb_handler.message_to_dict(message=update)
total_portfolio_df = pd.DataFrame(update_dict['total_portfolio']['values'])

Example : DataFrame

   degiroCash  flatexCash  totalCash  totalDepositWithdrawal  todayDepositWithdrawal  ...  reportNetliq  reportOverallMargin  reportTotalLongVal  reportDeficit  marginCallStatus
0           0           1          2                       3                       4  ...            16                   17                  18             19    NO_MARGIN_CALL

For a more comprehensive example : update.py

5.4. How to retrieve the OrdersHistory ?

This method returns data about passed orders between two dates.

The result contains a list of "Orders" objects with the following attributes :

Here is how to get this data :

# SETUP REQUEST
from_date = OrdersHistory.Request.Date(year=2020,month=11,day=15)
to_date = OrdersHistory.Request.Date(year=2020,month=10,day=15)
request = OrdersHistory.Request(from_date=from_date, to_date=to_date)

# FETCH DATA
orders_history = trading_api.get_orders_history(request=request)

For a more comprehensive example : orders_history.py

5.5. How to retrieve the TransactionsHistory ?

Here is how to get this data :

# SETUP REQUEST
from_date = TransactionsHistory.Request.Date(year=2020,month=11,day=15)
to_date = TransactionsHistory.Request.Date(year=2020,month=10,day=15)
request = TransactionsHistory.Request(from_date=from_date, to_date=to_date)

# FETCH DATA
transactions_history = trading_api.get_transactions_history(request=request)

For a more comprehensive example : transactions_history.py

6. Account

6.1. How to retrieve the table : Config ?

The config table contains the following informations :

Here is how to get this table :

# FETCH DATA
config_table = trading_api.get_config()

# EXTRACT SOME DATA
user_token = config_table['clientId']
session_id = config_table['sessionId']

For a more comprehensive example : config_table.py

6.2. How to retrieve the table : ClientDetails ?

The ClientDetails table contains information about the current Degiro Account.

Here is how to get this table :

# FETCH DATA
client_details_table = trading_api.get_client_details()

# EXTRACT SOME DATA
int_account = client_details_table['data']['intAccount']
user_token = client_details_table['data']['id']

For a more comprehensive example : client_details_table.py

6.3. How to retrieve the table : AccountInfo ?

The AccountInfo table contains the following information about currencies.

Here is how to get this table :

account_info_table = trading_api.get_account_info()

For a more comprehensive example : account_info_table.py

6.4. How to get the table : AccountOverview ?

It will provide a list of cash movements.

Here is how to get this data :

# SETUP REQUEST
from_date = AccountOverview.Request.Date(year=2020,month=11,day=15)
to_date = AccountOverview.Request.Date(year=2020,month=10,day=15)
request = AccountOverview.Request(from_date=from_date, to_date=to_date)

# FETCH DATA
account_overview = trading_api.get_account_overview(request=request)

For a more comprehensive example : account_overview.py

Each cash movement contains this kind of parameters :

6.5. How to export the table : CashAccountReport ?

It will export a list of cash movements in a specific format.

Available formats :

• CSV
• HTML
• PDF
• XLS

Here is how to get this content in CSV format :

# SETUP REQUEST
from_date = CashAccountReport.Request.Date(year=2020,month=11,day=15)
to_date = CashAccountReport.Request.Date(year=2020,month=10,day=15)
request = CashAccountReport.Request(
    format=CashAccountReport.Format.CSV,
    country='FR',
    lang='fr',
    from_date=from_date,
    to_date=to_date,
)

# FETCH DATA
cash_account_report = trading_api.get_cash_account_report(
    request=request,
    raw=False,
)

Here are the available parameters for CashAccountReport.Request :

Exact definitions of CashAccountReport and CashAccountReport.Request are in this file : trading.proto

For a more comprehensive example : cash_account_report.py

6.6. How to export the table : PositionReport ?

It will export a list of cash movements in a specific format.

Available formats :

• CSV
• HTML
• PDF
• XLS

Here is how to get this content in CSV format :

# SETUP REQUEST
to_date = CashAccountReport.Request.Date(year=2020,month=10,day=15)
request = CashAccountReport.Request(
    format=CashAccountReport.Format.CSV,
    country='FR',
    lang='fr',
    to_date=to_date,
)

# FETCH DATA
position_report = trading_api.get_position_report(
    request=request,
    raw=False,
)

Here are the available parameters for PositionReport.Request :

Exact definitions of PositionReport and PositionReport.Request are in this file : trading.proto

For a more comprehensive example : position_report.py

7. Products

7.1. How to get the table : ProductsConfig ?

This table contains useful parameters to filter products.

Here are the parameters which are inside this table :

Here is how to get this data :

# FETCH DATA
products_config = trading_api.get_products_config()

For a more comprehensive example : products_config.py

7.2. How to get my favourite products ?

Here is how to get this data :

# FETCH DATA
favourites_list = trading_api.get_favourites_list()

For a more comprehensive example : favourites_list.py

7.3. How to lookup products (search by name) ?

Text research on a financial product.

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestLookup(
    search_text='APPLE',
    limit=10,
    offset=0,
    product_type_id=1,
)

# FETCH DATA
products_lookup = trading_api.product_search(request=request)

For a more comprehensive example : product_lookup.py

7.4. How to search bonds ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestBonds(
    bond_issuer_type_id=0,
    bond_exchange_id=710,

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
bond_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.5. How to search etfs ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestETFs(
    popular_only=False,
    input_aggregate_types='',
    input_aggregate_values='',

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
etf_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.6. How to search funds ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestFunds(
    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
fund_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.7. How to search futures ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestFutures(
    future_exchange_id=1,
    underlying_isin='FR0003500008',

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
fund_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.8. How to search leverageds ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestLeverageds(
    popular_only=False,
    input_aggregate_types='',
    input_aggregate_values='',

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
etf_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.9. How to search options ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestOptions(
    input_aggregate_types='',
    input_aggregate_values='',
    option_exchange_id=3,
    underlying_isin='FR0003500008',

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='expirationDate,strike',
    sort_types='asc,asc',
)

# FETCH DATA
option_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.10. How to search stocks ?

It contains information about available stocks.

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestStocks(
    index_id=122001,    # NASDAQ 100
    exchange_id=663,    # NASDAQ
                        # You can either use `index_id` or `exchange id`
                        # See which one to use in the `ProductsConfig` table
    is_in_us_green_list=True,
    stock_country_id=846, # US

    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
stock_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.11. How to search warrants ?

Here is how to get this data :

# SETUP REQUEST
request = ProductSearch.RequestWarrants(
    search_text='',
    offset=0,
    limit=100,
    require_total=True,
    sort_columns='name',
    sort_types='asc',
)

# FETCH DATA
warrant_list = trading_api.product_search(request=request)

For a more comprehensive example : product_search.py

7.12. How to search products from ids ?

Here is how to get this data :

# SETUP REQUEST
request = ProductsInfo.Request()
request.products.extend([96008, 1153605, 5462588])

# FETCH DATA
products_info = trading_api.get_products_info(
    request=request,
    raw=True,
)

For a more comprehensive example : products_info.py

7.13. How to create a favourite list ?

Example :

favorite_list_id = trading_api.create_favourite_list(name="SOME_NAME")

For a more comprehensive example : favourite_list_create.py

7.14. How to delete a favourite list ?

Example :

success = trading_api.delete_favourite_list(id=1234567)

For a more comprehensive example : favourite_list_delete.py

7.15. How to put favourite list products ?

Example :

success = trading_api.put_favourite_list_product(
    id=1234567,
    product_id=1234567,
)

For a more comprehensive example : favourite_list_put_product.py

7.16. How to delete favourite list products ?

Example :

success = trading_api.delete_favourite_list_product(
    id=1234567,
    product_id=1234567,
)

For a more comprehensive example : [favourite_list_delete product.py](examples/trading/favourite_list_delete product.py)

8. Companies

8.1. How to get : CompanyProfile ?

Here is how to get this data :

# FETCH DATA
company_profile = trading_api.get_company_profile(
    product_isin='FR0000131906',
)

For a more comprehensive example : company_profile.py

8.2. How to get : CompanyRatios ?

This table contains information about the company.

Here are the parameters which are inside this table :

Here is how to get this data :

# FETCH DATA
company_ratios = trading_api.get_company_ratios(
    product_isin='FR0000131906',
)

For a more comprehensive example : company_ratios.py

8.3. How to get : FinancialStatements ?

Here is how to get this data :

# FETCH DATA
financials_statements = trading_api.get_financials_statements(
    product_isin='FR0000131906',
)

For a more comprehensive example : financial_statements.py

8.4. How to get : LatestNews ?

Here is how to get this data :

# SETUP REQUEST
request = LatestNews.Request(
    offset=0,
    languages='en,fr',
    limit=20,
)

# FETCH DATA
latest_news = trading_api.get_latest_news(
    request=request,
    raw=True,
)

For a more comprehensive example : latest_news.py

8.5. How to get : TopNewsPreview ?

Here is how to get this data :

# FETCH DATA
top_news_preview = trading_api.get_top_news_preview(raw=True)

For a more comprehensive example : top_news_preview.py

8.6. How to get : NewsByCompany ?

Here is how to get this data :

# SETUP REQUEST
request = NewsByCompany.Request(
    isin='NL0000235190',
    limit=10,
    offset=0,
    languages='en,fr',
)

# FETCH DATA
news_by_company = trading_api.get_news_by_company(
    request=request,
    raw=True,
)

For a more comprehensive example : news_by_company.py

8.7. How to get : Agenda ?

Here is how to get this data :

# SETUP REQUEST
request = Agenda.Request()
request.start_date.FromJsonString('2021-06-21T22:00:00Z')
request.end_date.FromJsonString('2021-11-28T23:00:00Z')
request.calendar_type = Agenda.CalendarType.DIVIDEND_CALENDAR
request.offset = 0
request.limit = 25

# FETCH DATA
agenda = trading_api.get_agenda(
    request=request,
    raw=False,
)

Here are the available parameters for Agenda.Request :

Exact definitions of Agenda and Agenda.Request are in this file : trading.proto

For a more comprehensive example : agenda.py

8.8. How to get : EstimatesSummaries ?

Here is how to get this data :

# SETUP REQUEST
request = Agenda.Request()
request.start_date.FromJsonString('2021-06-21T22:00:00Z')
request.end_date.FromJsonString('2021-11-28T23:00:00Z')
request.calendar_type = Agenda.CalendarType.DIVIDEND_CALENDAR
request.offset = 0
request.limit = 25

# FETCH DATA
product_isin = "FR0000131906"
estimates_summaries = trading_api.get_estimates_summaries(
    product_isin=product_isin,
    raw=False,
)

Here are the available parameters for Agenda.Request :

Exact definition of EstimatesSummaries is in this file : trading.proto

For a more comprehensive example : estimates_summaries.py

9. Contributing

Pull requests are welcome.

Feel free to open an issue or send me a message if you have a question.

10. License

BSD-3-Clause License