Fetch with Python

You can use the python package to fetch enriched data for an entity.

Part 1 of this article with details on installing the package, authentication, advanced settings, identity and uploading statements are listed on this page.

Accounts#

To fetch accounts use the get_accounts method. It returns an iterator to the account dictionary list, after fetching.

accounts = entity.get_accounts()
# printing the account dictionary using iterator
for account in accounts:
print(account)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

This method also has the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False |

Exceptions#

  • In case the create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the account information could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Account Dictionary#

Sample account dictionary:

{
"months": [
"2018-11",
"2018-12",
"2019-01"
],
"statements": [
"uuid4_for_statement"
],
"account_id": "uuid4_for_account",
"ifsc": None,
"micr": None,
"account_number": "Account Number Extracted",
"bank": "axis"
}

Each of the account dictionary in the account list has the following keys:

  • months: month and year for which data is available. Each of string in this list is of format "YYYY-MM"
  • statements: list of statement unique identifiers under the account
  • account_id: unique identifier for an account
  • bank: name of the bank to which the account belongs

It also has some account level extracted fields like ifsc, micr, account_number (which can be None or could hold a string value)

Fraud#

To fetch fraud information use the get_fraud_info method. It returns an iterator to the fraud dictionary list, after fetching.

fraud_list_iter = entity.get_fraud_info()
# printing the fraud dict dictionary using iterator
for fraud_dict in fraud_list_iter:
print(fraud_dict)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

This method also has the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False |

Exceptions#

  • In case the create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the statement could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Fraud Dictionary#

Sample fraud dictionary:

{
"statement_id": "uuid4_for_statement",
"fraud_type": "some_fraud_type"
}

Each of the fraud dictionaries includes the keys statement_id and fraud_type indicating a fraud of which type was found in which statement.

Optionally a key transaction_hash may be present in some cases in this dictionary for transaction-level frauds indicating the transaction in which the fraud was found.

To know more about fraud_type, refer to Fraud section in Basics.

Transactions#

To fetch transactions use the get_transactions method. It returns an iterator to the transaction dictionary list, after fetching.

transactions = entity.get_transactions()
# printing the transaction dictionary using iterator
for transaction in transactions:
print(transaction)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

This method also has the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False | | account_id | String | If provided, only the transactions of specific account_id will be retrieved | - | | from_date | datetime.date object | If provided, only the transactions with a date greater than or equal to from_date will be retrieved. | - | | to_date | datetime.date object | If provided, only the transactions with a date less than or equal to to_date will be retrieved. | - |

An example for fetching transactions from last 10 days till today:

import datetime
import finbox_bankconnect as fbc
entity = fbc.Entity.get(entity_id="uuid_for_entity")
# fetching transactions from last 10 days
from_date = (datetime.datetime.today() - datetime.timedelta(days=10)).date()
to_date = datetime.datetime.today().date()
transactions = entity.get_transactions(from_date=from_date, to_date=to_date)
# print the transaction dictionary using iterator
for transaction in transactions:
print(transaction)

Exceptions#

  • In case there is any problem with arguments passed or if create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the transactions could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Transaction Dictionary#

Sample transaction dictionary:

{
"transaction_note": "SOME LONG TRANSACTION NOTE",
"hash": "unique_transaction_identifier",
"description": "lender_transaction",
"account_id": "uuid4_for_account",
"transaction_type": "debit",
"amount": 5188.0,
"date": "2019-01-08 00:00:00",
"merchant_category": "",
"balance": 922.15,
"transaction_channel": "salary"
}

Each of the transaction dictionary in the transaction list has the following keys:

  • transaction_note: exact transaction note / description present in the statement PDF
  • hash: a unique identifying hash for each transaction
  • description: describes more information about the transaction_channel field. Refer to this list for possible values.
  • account_id: unique UUID4 identifier for the account to which the transaction belongs to
  • transaction_type: can be debit or credit
  • amount: indicates the transaction amount
  • date: date of transaction
  • merchant_category: the category of the merchant in case a transaction is with a merchant. Refer to this list of possible values.
  • balance: account balance just after this transaction
  • transaction_channel: refer to this list for possible values.

Salary#

To fetch salary transactions use the get_salary method. It returns an iterator to the salary dictionary list, after fetching.

salary_iter = entity.get_salary()
# printing the salary dictionary using iterator
for salary_dict in salary_iter:
print(salary_dict)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

This method also has the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False | | account_id | String | If provided, only the salary of specific account_id will be retrieved | - | | from_date | datetime.date object | If provided, only the salary with a date greater than or equal to from_date will be retrieved. | - | | to_date | datetime.date object | If provided, only the salary with a date less than or equal to to_date will be retrieved. | - |

Exceptions#

  • In case there is any problem with arguments passed or if create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the transactions could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Salary Dictionary#

Sample salary dictionary:

{
"balance": 29979.15,
"hash": "unique_transaction_identifier_2",
"description": "",
"clean_transaction_note": "Clean Transaction Note",
"account_id": "uuid4_for_account",
"transaction_type": "credit",
"date": "2019-01-11 00:00:00",
"amount": 29057.0,
"month_year": "1-2019",
"merchant_category": "",
"transaction_channel": "net_banking_transfer",
"transaction_note": "SOME LONG TRANSACTION NOTE"
}

Each of the salary dictionary in the transaction list has the following keys:

  • balance: account balance just after this transaction
  • hash: a unique identifying hash for each transaction
  • description: describes more information about the transaction_channel field. Refer to this list for possible values.
  • clean_transaction_note: Transaction note in clean English words
  • account_id: unique UUID4 identifier for the account to which the transaction belongs to
  • transaction_type: can be debit or credit
  • date: date of transaction
  • amount: indicates the transaction amount
  • month_year: month and year for which the salary is
  • merchant_category: the category of the merchant in case a transaction is with a merchant. Refer to this list of possible values.
  • transaction_channel: refer to this list for possible values.
  • transaction_note: exact transaction note / description present in the statement PDF

Recurring Transactions#

To fetch recurring transactions use the get_credit_recurring and get_debit_recurring methods for credit and debit respectively. Both of these return an iterator to the recurring dictionary list, after fetching.

credit_recurring = entity.get_credit_recurring()
# printing the credit recurring dictionary using iterator
for credit_recurr_dict in credit_recurring:
print(credit_recurr_dict)
debit_recurring = entity.get_debit_recurring()
# printing the debit recurring dictionary using iterator
for debit_recurr_dict in debit_recurring:
print(debit_recurr_dict)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

Both of these methods have the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False | | account_id | String | If provided, only the recurring transactions of specific account_id will be retrieved | - |

Exceptions#

  • In case there is any problem with arguments passed or if create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the transactions could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Recurring Transaction Dictionary#

Sample recurring transaction dictionary:

{
"account_id": "uuid4_for_account",
"end_date": "2019-01-11 00:00:00",
"transactions": [
{
"transaction_channel": "net_banking_transfer",
"transaction_note": "SOME LONG TRANSACTION NOTE",
"hash": "unique_transaction_identifier_1",
"account_id": "uuid4_for_account",
"transaction_type": "credit",
"amount": 27598.0,
"date": "2018-12-12 00:00:00",
"balance": 32682.78,
"description": ""
},
{
"transaction_channel": "net_banking_transfer",
"transaction_note": "SOME LONG TRANSACTION NOTE",
"hash": "unique_transaction_identifier_2",
"account_id": "uuid4_for_account",
"transaction_type": "credit",
"amount": 29057.0,
"date": "2019-01-11 00:00:00",
"balance": 29979.15,
"description": ""
}
],
"median": 29057.0,
"start_date": "2018-12-12 00:00:00",
"transaction_channel": "NET_BANKING_TRANSFER"
}

Each of the recurring transaction dictionary (both credit and debit) has the following keys:

  • account_id: unique UUID4 identifier for the account to which transaction set belongs to
  • start_date: the start date for the recurring transaction set
  • end_date: end date for the recurring transaction set
  • transaction_channel: transaction channel in upper case. Refer to this list for possible values.
  • median: median of the transaction amounts under the given recurring transaction set
  • transactions: list of transaction dictionary under the recurring transaction set. Each transaction dictionary here has the same keys as a transaction dictionary in get_transactions (Refer here to know about the keys).

Lender Transactions#

To fetch lender transactions use the get_lender_transactions method. It returns an iterator to the lender transaction dictionary list, after fetching.

lender_transactions = entity.get_lender_transactions()
# printing the lender transaction dictionary using iterator
for lender_transaction in lender_transactions:
print(lender_transaction)
NOTE

If the value was not previously retrieved, it will poll and check for progress, and then fetch and cache the retrieved value for next usage.

Arguments#

This method also has the following optional arguments: | Argument | Type | Description | Default | | - | - | - | - | | reload | Boolean | If provided as True, it will ignore the cached value, and again make an API call and re-fetch the values | False | | account_id | String | If provided, only the lender transactions of specific account_id will be retrieved | - | | from_date | datetime.date object | If provided, only the lender transactions with a date greater than or equal to from_date will be retrieved. | - | | to_date | datetime.date object | If provided, only the lender transactions with a date less than or equal to to_date will be retrieved. | - |

Exceptions#

  • In case there is any problem with arguments passed or if create method was used while creating the entity instance and the entity object was not created on the server yet, it throws ValueError.

  • In case server could not be reached, it throws ServiceTimeOutError (finbox_bankconnect.custom_exceptions.ServiceTimeOutError).

  • In case entity_id cannot be found in our server, it throws EntityNotFoundError (finbox_bankconnect.custom_exceptions.EntityNotFoundError)

  • In case the transactions could not be extracted by us, it will throw ExtractionFailedError (finbox_bankconnect.custom_exceptions.ExtractionFailedError)

Lender Transaction Dictionary#

Sample lender transaction dictionary:

{
"transaction_note": "SOME LONG TRANSACTION NOTE",
"hash": "unique_transaction_identifier_2",
"description": "lender_transaction",
"account_id": "uuid4_for_account",
"transaction_type": "debit",
"amount": 5188.0,
"date": "2019-01-08 00:00:00",
"merchant_category": "",
"balance": 922.15,
"transaction_channel": "net_banking_transfer"
}

Each of the lender transaction dictionary in the transaction list has the following keys:

  • transaction_note: exact transaction note / description present in the statement PDF
  • hash: a unique identifying hash for each transaction
  • description: describes more information about the transaction_channel field. Refer to this list for possible values.
  • account_id: unique UUID4 identifier for the account to which the transaction belongs to
  • transaction_type: can be debit or credit
  • amount: indicates the transaction amount
  • date: date of transaction
  • merchant_category: the category of the merchant in case a transaction is with a merchant. Refer to this list of possible values.
  • balance: account balance just after this transaction
  • transaction_channel: refer to this list for possible values.

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