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More functions added. · NHSDigital/codonPython@e76601f · GitHub

/ codonPython Public

Commit e76601f

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More functions added.
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‎codonPython/dateValidator.py‎

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import re
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def validDate(date_string: str)->bool:
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"""
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Validates stringtype dates of type `dd/mm/yyyy`, `dd-mm-yyyy` or `dd.mm.yyyy` from
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years 1900-9999. Leap year support included.
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Parameters
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----------
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date_string : str
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Date to be validated
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Returns
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----------
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boolean
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Whether the date is valid or not
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Examples
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---------
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>>> validDate("11/02/1996")
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True
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>>> validDate("29/02/2016")
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True
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>>> validDate("43/01/1996")
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False
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"""
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# This regex string will validate dates of type `dd/mm/yyyy`, `dd-mm-yyyy` or `dd.mm.yyyy`
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# from years 1900 - 9999. Leap year support included. Regex string from
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# https://stackoverflow.com/questions/15491894/regex-to-validate-date-format-dd-mm-yyyy
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if re.match(r"^(?:(?:31(\/|-|\.)(?:0?[13578]|1[02]))\1|(?:(?:29|30)(\/|-|\.)(?:0?[13-9]|1[0-2])\2))(?:(?:1[6-9]|[2-9]\d)?\d{2})$|^(?:29(\/|-|\.)0?2\3(?:(?:(?:1[6-9]|[2-9]\d)?(?:0[48]|[2468][048]|[13579][26])|(?:(?:16|[2468][048]|[3579][26])00))))$|^(?:0?[1-9]|1\d|2[0-8])(\/|-|\.)(?:(?:0?[1-9])|(?:1[0-2]))\4(?:(?:19|[2-9]\d)?\d{2})$", date_string, flags=0):
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return True
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else:
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return False

‎codonPython/nhsNumberGenerator.py‎

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import random
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def nhsNumberGenerator(to_generate: int)->list:
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"""
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Generates random NHS number(s) compliant with modulus 11 checks recorded
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in the data dictonary.
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https://www.datadictionary.nhs.uk/data_dictionary/attributes/n/nhs/nhs_number_de.asp?shownav=1
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Parameters
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----------
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to_generate : int
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number of NHS numbers to generate
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Returns
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----------
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generated : list
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List of randomly generated NHS numbers
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Examples
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---------
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>>> random.seed(42)
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>>> nhsNumberGenerator(2)
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[7865793030, 1933498560]
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"""
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generated = []
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while len(generated) < to_generate:
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# Random 9 digit number starting with non-zero digit
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number = random.randint(100000000, 999999999)
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digits = [int(digit) for digit in str(number)]
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# Apply weighting to digits
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weighted_digits = [(10 - index) * digit for (index, digit) in enumerate(digits)]
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# Sum of all weighted digits must be a multiple of 11 to be valid.
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if sum(weighted_digits) % 11 == 0:
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# Add check digit to valid number
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number = int(str(number) + "0")
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generated.append(number)
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return generated

‎codonPython/tableFromSql.py‎

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from sqlalchemy import create_engine
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import pandas as pd
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def tableFromSql(server: str, database: str, table_name: str, user: str = "", password: str = "", schema: str = None, index_col: str = None, coerce_float: bool = True, parse_dates: list = None, columns: list = None, chunksize: int = None):
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'''
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Returns a SQL table in a DataFrame.
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Convert a table stored in SQL Server 2016 into a pandas dataframe.
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Uses sqlalchemy and pandas.
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Parameters
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----------
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server : string
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Name of the SQL server
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database : string
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Name of the SQL database
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user : string, default: ""
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If verification is required, name of the user
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password : string, default: ""
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If verification is required, password of the user
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table_name : string
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Name of SQL table in database.
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schema : string, default : None
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Name of SQL schema in database to query (if database flavor supports this). Uses
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default schema if None (default).
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index_col : string or list of strings, default : None
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Column(s) to set as index(MultiIndex).
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coerce_float : boolean, default : True
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Attempts to convert values of non-string, non-numeric objects (like decimal.Decimal)
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to floating point. Can result in loss of Precision.
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parse_dates : list or dict, default : None
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- List of column names to parse as dates.
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- Dict of {column_name: format string} where format string is strftime compatible in
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case of parsing string times or is one of (D, s, ns, ms, us) in case of parsing
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integer timestamps.
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- Dict of {column_name: arg dict}, where the arg dict corresponds to the keyword
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arguments of pandas.to_datetime() Especially useful with databases without native
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Datetime support, such as SQLite.
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columns : list, default : None
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List of column names to select from SQL table
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chunksize : int, default : None
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If specified, returns an iterator where chunksize is the number of rows to include
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in each chunk.
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Returns
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----------
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pd.DataFrame
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Dataframe of the table requested from sql server
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Examples
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---------
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# >>> tableFromSql("myServer2", "myDatabase2", "myTable2")
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# pd.DataFrame
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# >>> tableFromSql("myServer", "myDatabase", "myTable", schema="specialSchema", columns=["col_1", "col_3"])
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# pd.DataFrame
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'''
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try:
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uri = "mssql+pyodbc://{}:{}@{}/{}?driver=SQL Server Native Client 11.0".format(user, password, server, database)
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engine = create_engine(uri)
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return pd.read_sql_table(table_name, engine, schema=schema, index_col=index_col, coerce_float=coerce_float, parse_dates=parse_dates, columns=columns, chunksize=chunksize)
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except Exception as error:
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raise error
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‎setup.py‎

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packages=['codonPython',],
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install_required=[
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'numpy',
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're',
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'pandas',
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'random',
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'sqlalchemy'
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],
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author='NHS Digital DIS Team',
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author_email='paul.ellingham@nhs.net',

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