python-lei 0.1.1

Description:

pythonlei 0.1.1

python-lei




This project is wraper for Leilex, legal entity identifier API. Includes ISIN-LEI conversion. Search LEI number using company name.
Dependencies

Python >= 3.4
requests
dateutils
pandas

Usage
After installing the module, first step is to download the data for ISIN and LEI mappings
>>> from python_lei.utils import Download

>>> Download()

This will download latest ISIN LEI mappings into resources directory. This is only necessary if you want to use ISIN LEI conversion.
Get LEI information
>>> from python_lei.pylei import pyLEI

>>> getinfo = pyLEI()

>>> raw_output, lei_results, dataframe = getinfo.get_lei_info(["A23RUXWKASG834LTMK28"], return_dataframe=True)

>>> print(raw_output)

[{'total_record_count': 1,
'page_number': 1,
'page_size': 100,
'total_pages': 1,
'has_more': False,
'records': [{'LEI': 'A23RUXWKASG834LTMK28',
'LegalName': 'AUTOLIV, INC.',
'LegalJurisdiction': 'US-DE',
'LegalForm': 'XTIQ',
'OtherLegalForm': '',
'EntityStatus': 'ACTIVE',
'EntityExpirationDate': None,
'EntityExpirationReason': '',
'SuccessorEntity': '',
'InitialRegistrationDate': '2012-06-06T03:52:00.000 +00:00',
'LastUpdateDate': '2019-12-18T03:32:00.000 +00:00',
'RegistrationStatus': 'ISSUED',
'NextRenewalDate': '2020-12-15T10:15:00.000 +00:00',
'ManagingLOU': 'EVK05KS7XY1DEII3R011',
'ValidationSources': 'FULLY_CORROBORATED',
'AssociatedLEI': '',
'AssociatedEntityName': '',
'AssociatedEntityType': '',
'RegistrationAuthorityID': 'RA000602 ',
'OtherRegistrationAuthorityID': '',
'RegistrationAuthorityEntityID': '2155072',
'EntityCategory': '',
'Addresses': [{'Line1': 'Box 70381',
'Line2': '',
'Line3': '',
'Line4': '',
'City': 'Stockholm',
'Region': 'SE-AB',
'Country': 'SE',
'PostalCode': '107 24',
'OtherType': '',
'AddressType': 'HEADQUARTERS_ADDRESS'},
{'Line1': 'C/O THE CORPORATION TRUST COMPANY',
'Line2': 'CORPORATION TRUST CENTER 1209 ORANGE ST',
'Line3': '',
'Line4': '',
'City': 'WILMINGTON',
'Region': 'US-DE',
'Country': 'US',
'PostalCode': '19801',
'OtherType': '',
'AddressType': 'LEGAL_ADDRESS'}],
'OtherNames': [],
'ValidationAuthorities': [{'ValidationAuthorityID': 'RA000602',
'OtherValidationAuthorityID': '',
'ValidationAuthorityEntityID': '2155072'}],
'Relationships': [],
'ReportingExceptions': [{'LEI': 'A23RUXWKASG834LTMK28',
'ExceptionCategory': 'DIRECT_ACCOUNTING_CONSOLIDATION_PARENT',
'ExceptionReasons': [{'Reason': 'NON_CONSOLIDATING'}],
'ExceptionReferences': []},
{'LEI': 'A23RUXWKASG834LTMK28',
'ExceptionCategory': 'ULTIMATE_ACCOUNTING_CONSOLIDATION_PARENT',
'ExceptionReasons': [{'Reason': 'NON_CONSOLIDATING'}],
'ExceptionReferences': []}]}]}]


# Class based retrieval
>>> print(lei_results.lei_names)
['AUTOLIV, INC.']

>>> print(lei_results.lei_list)
['A23RUXWKASG834LTMK28']

# Dataframe
>>> print(dataframe[["LEI", "Legal_Name"]])
| | LEI | Legal_Name |
|---:|:---------------------|:--------------|
| 0 | A23RUXWKASG834LTMK28 | AUTOLIV, INC. |

Get LEI-ISIN information
# LEI TO ISIN
>>> from python_lei.isin_lei import ISINtoLEI, LEItoISIN

>>> lei_to_isin = LEItoISIN()

>>> isin_list, dataframe = lei_to_isin.get_isin("A23RUXWKASG834LTMK28", return_dataframe=True)

>>> print(isin_list)
['SE0000382335',
'US052800AB59',
'US0528002084',
'US0528003074',
'US0528001094',
'US0528001177']

>>> print(dataframe)
| | LEI | ISIN |
|--------:|:---------------------|:-------------|
| 1858574 | A23RUXWKASG834LTMK28 | SE0000382335 |
| 2141681 | A23RUXWKASG834LTMK28 | US052800AB59 |
| 2990824 | A23RUXWKASG834LTMK28 | US0528002084 |
| 3450877 | A23RUXWKASG834LTMK28 | US0528003074 |
| 3766379 | A23RUXWKASG834LTMK28 | US0528001094 |
| 4442500 | A23RUXWKASG834LTMK28 | US0528001177 |

# ISIN TO LEI
>> isin_to_lei = ISINtoLEI()

>> lei_number = isin_to_lei.get_lei("US0528003074")

>> print(lei_number)
['A23RUXWKASG834LTMK28']

Search LEI using company name
You can also search for possible LEI numbers for a given company name.
>>> from python_lei.lei_search import SearchLEI
>>> search_possible_lei = SearchLEI()
>>> raw_data, table = search_possible_lei.search_lei("Apple INC.", show_table=True)
>>> print(table)
+------------+----------------------+
| Legal Name | LEI |
+------------+----------------------+
| APPLE INC. | HWUPKR0MPOU8FGXBT394 |
+------------+----------------------+

>>> print(raw_data)
[{'LegalName': 'APPLE INC.', 'LEI': 'HWUPKR0MPOU8FGXBT394'}]