degiro-connector 0.1.3

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1. Degiro Connector

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

1.1. Which features ?

Here are the features you can access through this library :

Endpoint	Feature(s)
AccountInfo	Retrieve a table containing : "clientId" and Currencies.
AccountOverview	Retrieve all the CashMovements between two dates.
Bonds ETFs Funds Futures Leverageds Lookup Options Stocks Warrants	Search list of products according their name, type and other criterias. For instance all the stocks from NASDAQ 100.
Chart	Retrieve chart data.
ClientDetails	Retrieve a table containing : "clientId", "intAccount" and other account information.
CompanyProfile	Retrieve a company's profile using its ISIN code.
CompanyRatios	Retrieve a company's ratios using its ISIN code.
Config	Retrieve a table containing : "clientId" and URLs which are constitutive of Degiro's API.
Favourites	Retrieve favorite products lists.
FinancialStatements	Retrieve a company's financial statements using its ISIN code.
LatestNews	Retrieve latest news about all the companies.
LoginQuotecast	Establish a connection for quotecast operations.
LoginTrading	Establish a connection for trading operations.
LogoutTrading	Destroy previously established connection for trading operations.
NewsByCompany	Retrieve news related to a specific company.
Order	Create, update, delete an Order.
OrderHistory	Retrieve all Orders created between two dates.
Orders	List pending Orders.
Portoflio	List products in your Portoflio.
ProductsConfig	Retrieve a table containing : useful parameters to filter products.
ProductsInfo	Search for products using their ids.
Quotecasts	Fetch real-time data on financial products. For instance the real-time stock Price.
TopNewsPreview	Retrieve some news preview about all the companies.
TotalPorfolio	Retrieve aggregated information about your assets.
TransactionsHistory	Retrieve all Transactions created between two dates.

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 Dictionnary ?
  • 2.13. What is inside the DataFrame ?
  • 2.14. How to get chart data ?
• 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 ?
• 4. Order
  • 4.1. How to create an 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 ?
• 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 ?
• 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 ?
• 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

He can use this library to retrieve update like this :

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

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 section 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 :

Parameter	Type	Description
subscriptions	MessageMap	List of products and metrics to subscribe to.
unsubscriptions	MessageMap	List of products and metrics to unsubscribe to.

Here is an example of request :

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

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 :

Parameter	Type	Description
subscriptions	MessageMap	List of products and metrics to subscribe to.
unsubscriptions	MessageMap	List of products and metrics to unsubscribe to.

Here is an example of request :

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

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 :

Parameter	Type	Description
json_data	dict	Dictionnary representation of what Degiro's API has sent.
metadata	Metadata	Containing the "response_datetime" and "request_duration".

Here is how to access these properties :

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

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 type :

Type	Description
Ticker	Protobuf message (for GRPC).
Dictionnaries	Standard Python Dictionaries : dict.
DataFrame	DataFrame from the library Pandas.

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 :

Parameter	Type	Description
metadata	Metadata	Containing the "response_datetime" and "request_duration".
products	MessageMap	Dictionnary like object containing the metrics group by "vwd_id".
product_list	RepeatedScalarFieldContainer	List of available "vwd_id".

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 Dictionnary ?

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

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

Example - Dictionnary :

{
    '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 ?

The generated DataFrame will content :

• In rows : the product, for instance the "AAPL" stock which has "vwd_id" = "AAPL.BATS,E".
• In columns : the product's parameters for instance "LastPrice", "LastVolume"...

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.

Parameter	Type	Description
requestid	str	It sends you back whatever string you put here, you can set it to : "1".
resolution	Chart.Resolution	Resolution of the chart like : Chart.Resolution.PT1M.
culture	str	Country code like : "en-US" or "fr-FR".
period	Chart.Period	Period of the chart, like : Chart.Period.P1D.
series	repeated string	Data to get like : ['issueid:36014897', 'price:issueid:360148977'].
tz	str	Timezone like : "Europe/Paris"

Example of code :

request = Chart.Request()
request.requestid = '1'
request.resolution = Chart.Resolution.PT1M
request.culture = 'fr-FR'
request.series.append('issueid:360148977')
request.series.append('price:issueid:360148977')
request.series.append('ohlc:issueid:360148977')
request.series.append('volume:issueid:360148977')
request.period = Chart.Period.P1D
request.tz = 'Europe/Paris'

chart = quotecast_api.get_chart(request=request)

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

For a more comprehensive example : chart.py

3. Trading connection

This library contains two main 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
quotecast_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 :

Parameter	Type	Description
username	str	Username used to log into Degiro's website.
password	str	Password used to log into Degiro's website.
int_account	int	OPTIONAL : unique identifier of the account : used by Degiro's server.
totp_secret_key	str	OPTIONAL : used for Two-factor Authentication (2FA).
one_time_password	str	OPTIONAL : used for Two-factor Authentication (2FA).

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.

When you do a standard connection you are providing two parameters, which are your :

• username
• password

But if you use Two-Factor Authentication (2FA) you need to provide an additional parameter, which is your :

• 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 giving to you by Degiro's website when you enabled 2FA : in the form of a QRCode.

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

Then this app will generate a new one_time_password that you can use for each connection.

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

CHOICE A

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

CHOICE B

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 to extract 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 ?

The connection for trading operations seems to have a timeout of : around 30 minutes.

If this connection is left unused for this amount of time it will cease to work.

Each time you do an operation using this connection Degiro's API seems to reset the timeout.

4. Order

Here are the main parameters of an Order.

Parameter	Type	Description
action	Order.Action	Whether you want to : BUY or SELL.
order_type	Order.OrderType	Type of order : LIMIT, STOP_LIMIT, MARKET or STOP_LOSS.
price	float	Price of the order.
product_id	int	Identifier of the product concerned by the order.
size	float	Size of the order.
time_type	Order.TimeType	Duration of the order : GOOD_TILL_DAY or GOOD_TILL_CANCELED

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 step :

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

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

Here are the parameters of a CheckingResponse :

Parameter	Type	Description
confirmation_id	str	Id necessary to confirm the creation of the Order.
free_space_new	float	New free space (balance) if the Order is confirmed.
response_datetime	Timestamp	Timestamp can be converted to date string using : ToJsonString().
transaction_fees	repeated Struct	Transaction fees that will be applied to the Order.
transaction_opposite_fees	repeated Struct	Other kind of fees that will be applied to the Order.
transaction_taxes	repeated Struct	Taxes that will be applied to the Order.

Here are the parameters of a ConfirmationResponse :

Parameter	Type	Description
orderId	str	Id of the created Order.
response_datetime	Timestamp	Timestamp can be converted to date string using : ToJsonString().

Here is an example :

# 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 setup it's "id".

Here is an example :

# ORDER SETUP
order = Order(
    id=YOUR_ORDER_ID,
    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 it's "id".

Here is an example :

# DELETE ORDER
succcess = trading_api.delete_order(order_id=YOUR_ORDER_ID)

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

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 :

Parameter	Type	Description
created	str	RFC 3339 Datetime, example : "2020-10-06T20:07:18+02:00".
orderId	str	MD5 HASH, example : "098f6bcd-4621-d373-cade-4e832627b4f6"
productId	int	Id of the product example : 65156
size	float	Size of the order, example : 10.0000
price	float	Price of the order, example : 8.6800
buysell	str	"B" or "S"
orderTypeId	int	see 3.Order
orderTimeTypeId	int	see 3.Order
stopPrice	float	Price like : 0.0000
totalTradedSize	int	-
type	str	"CREATE", "DELETE" or "MODIFY"
status	str	"CONFIRMED"
last	str	RFC 3339 Datetime, example : "2020-10-06T20:07:18+02:00".
isActive	bool	-

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 :

Parameter	Type	Description
sessionId	str	Current session id.
clientId	int	Unique Degiro's Account identifier also called "userToken"
tradingUrl	str	-
paUrl	str	-
reportingUrl	str	-
paymentServiceUrl	str	-
productSearchUrl	str	-
dictionaryUrl	str	-
productTypesUrl	str	-
companiesServiceUrl	str	-
i18nUrl	str	-
vwdQuotecastServiceUrl	str	-
vwdNewsUrl	str	-
vwdGossipsUrl	str	-
taskManagerUrl	str	-
refinitivNewsUrl	str	-
refinitivAgendaUrl	str	-
refinitivCompanyProfileUrl	str	-
refinitivCompanyRatiosUrl	str	-
refinitivFinancialStatementsUrl	str	-
refinitivClipsUrl	str	-
landingPath	str	-
betaLandingPath	str	-
mobileLandingPath	str	-
loginUrl	str	-

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.

Parameter	Type
id	int
intAccount	int
loggedInPersonId	int
clientRole	str
effectiveClientRole	str
contractType	str
username	str
displayName	str
email	str
firstContact.firstName	str
firstContact.lastName	str
firstContact.displayName	str
firstContact.nationality	str
firstContact.gender	str
firstContact.dateOfBirth	str
firstContact.placeOfBirth	str
firstContact.countryOfBirth	str
address.streetAddress	str
address.streetAddressNumber	str
address.zip	str
address.city	str
address.country	str
cellphoneNumber	str
locale	str
language	str
culture	str
bankAccount.bankAccountId	int
bankAccount.bic	str
bankAccount.iban	str
bankAccount.status	str
flatexBankAccount.bic	str
flatexBankAccount.iban	str
memberCode	str
isWithdrawalAvailable	bool
isAllocationAvailable	bool
isIskClient	bool
isCollectivePortfolio	bool
isAmClientActive	bool
canUpgrade	bool

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.

Parameter	Type
clientId	int
baseCurrency	str
currencyPairs	dict
marginType	str
cashFunds	dict
compensationCapping	float

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 contains information about 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

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 :

Parameter	Type
stockCountries	list
bondExchanges	list
bondIssuerTypes	list
eurexCountries	list
futureExchanges	list
optionExchanges	list
combinationExchanges	list
cfdExchanges	list
exchanges	list
indices	list
regions	list
countries	list
productTypes	list
etfFeeTypes	list
investmentFundFeeTypes	list
optionAggregateTypes	list
leveragedAggregateTypes	list
etfAggregateTypes	list
investmentFundAggregateTypes	list
lookupSortColumns	list
stockSortColumns	list
bondSortColumns	list
cfdSortColumns	list
etfSortColumns	list
futureSortColumns	list

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(
    bondIssuerTypeId=0,
    bondExchangeId=710,

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    popularOnly=False,
    inputAggregateTypes='',
    inputAggregateValues='',

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    futureExchangeId=1,
    underlyingIsin='FR0003500008',

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    popularOnly=False,
    inputAggregateTypes='',
    inputAggregateValues='',

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    inputAggregateTypes='',
    inputAggregateValues='',
    optionExchangeId=3,
    underlyingIsin='FR0003500008',

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='expirationDate,strike',
    sortTypes='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(
    indexId=5,
    isInUSGreenList=False,
    stockCountryId=886,

    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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(
    searchText='',
    offset=0,
    limit=100,
    requireTotal=True,
    sortColumns='name',
    sortTypes='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

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 :

Parameter	Type
totalFloat	str
sharesOut	str
consRecommendationTrend	dict
forecastData	dict
currentRatios	dict

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

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