Realtime Date Input Validation - regex

I am building a realtime input validation for a date format.
That is supposed to validate the date format while typing.
In order to do that i need a regex to do the following: X is a number {0,9} and every step of the input needs to be valid.
I tried building a regex and finding one fitting but both without success.
Best regards.
Valid Input Cases
"" - i.e empty
"X" - i.e. 3
"XX" - i.e. 31
"XX." - i.e. 31.
"XX.X" - i.e. 31.1
"XX.XX" - i.e. 31.10
"XX.XX." - i.e. 31.10.
"XX.XX.X" - i.e. 31.10.1
"XX.XX.XX" - i.e. 31.10.19
"XX.XX.XXX" - i.e. 31.10.199
"XX.XX.XXXX" - i.e. 31.10.1998
Edit: To clarify this will not replace date validation this will only be used in an HTML Input element in react to prevent the user from typing other chars.

Related

How to convert text field with formatted currency to numeric field type in Postgres?

I have a table that has a text field which has formatted strings that represent money.
For example, it will have values like this, but also have "bad" invalid data as well
$5.55
$100050.44
over 10,000
$550
my money
570.00
I want to convert this to a numeric field but maintain the actual numbers that can be retained, and for any that can't , convert to null.
I was using this function originally which did convert clean numbers (numbers that didn't have any formatting). The issue was that it would not convert $5.55 as an example and set this to null.
CREATE OR REPLACE FUNCTION public.cast_text_to_numeric(
v_input text)
RETURNS numeric
LANGUAGE 'plpgsql'
COST 100
VOLATILE
AS $BODY$
declare v_output numeric default null;
begin
begin
v_output := v_input::numeric;
exception when others then return null;
end;
return v_output;
end;
$BODY$;
I then created a simple update statement which removes the all non digit characters, but keeps the period.
update public.numbertesting set field_1=regexp_replace(field_1,'[^\w.]','','g')
and if I run this statement, it correctly converts the text data to numeric and maintains the number:
alter table public.numbertesting
alter column field_1 type numeric
using field_1::numeric
But I need to use the function in order to properly discard any bad data and set those values to null.
Even after I run the clean up to set the text value to say 5.55
my "cast_text_to_numeric" function STILL sets this to null ? I don't understand why this sets it to null, but the above statement correctly converts it to a proper number.
How can I fix my cast_text_to_numeric function to properly convert values such as 5.55 , etc?
I'm ok with disgarding (setting to NULL) any values that don't end up with numbers and a period. The regular expression will strip out all other characters... and if there happens to be two numbers in the text field, with the script, they would be combined into one (spaces are removed) and I'm good with that.
In the example of data above, after conversion, the end result in numeric field would be:
5.55
100050.44
null
550
null
570.00
FYI, I am on Postgres 11 right now

Parsing a name from a complex string in Tableau

I have a series of values in Tableau that are long strings intermixed with letters and numbers. I am unable to control the data output, but would like to parse the names from these strings. They follow the following format:
Potato 1TByte 4.5 NFA
Board 256GByte 553 NCA
Launch 4 512GByte 4.5 NFA
Launch 4S 512GByte 4.5 NCA
From each of these, I am attempting to capture the following:
"Potato"
"Board"
"Launch 4"
"Launch 4S"
Each string follows the same format: the name, followed by size, followed by some extra information we don't really care about.
I've tried to put together some text parsing strings, but am coming up short, and am still trying to learn regular expressions.
The Tableau calculated field I was trying to work with was something like the following:
LEFT([String], FIND([String], "Byte") - 2)
The issue is that the text and numbers preceding Byte can be anywhere from 4 to 2 characters and I need a way to identify the length of that.
Any help would be greatly appreciated!
One option which uses a regex replacement:
REGEXP_REPLACE('Launch 4 512GByte 4.5 NFA', ' \d+[A-Z]Byte .*$', '')
This strips off everything from the Byte term to the right, leaving us with only the product name.
You could try the following - this seems to work - Screenshot of Tableau output. Find below the formulas for the various derived columns you see in the screenshot (Your source column is called [Name])
Step1 = LEFT([Name],FIND([Name],"Byte")-1)
Step2 = LEN([Step1])-LEN(REPLACE([Step1]," ",""))
Step3 = FINDNTH([Step1]," ",[Step2])
Step4 = LEFT([Step1],[Step3]-1)
And of course you can nest all these in a single calculated field - kept them as separate columns for easier understanding

Data validation using regular expressions in Google Sheets

I am using the below date/time format in gSheets:
01 Apr at 11:00
I wonder whether it is possible to use Data Validation (or any other function) to report error (add the small red triangle to the corner of the cell) when the format differs in any way.
Possible values in the given format:
01 -> any number between 01-31 (but not "1", there must be the leading zero)
space
Apr -> 3 letters for month (Jan, Feb, Mar... Dec)
space
at
space
11 -> hours in 24h format (00, 01...23)
:
00 -> minutes (00, 01,...59)
Is there any way to validate that the cell contains "text/data" exactly in the above mentioned format?
The right way to do this is using Regular Expression and "regexmatch()" function in Google Sheets. For the given example, I made the below regular expression:
[0-3][0-9] (Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec) at [0-2][0-9]\:[0-5][0-9]
Process:
Select range of cells to be validated
Go to Data > Data Validation
Under Criteria select "Own pattern is" (not sure the exact translation used in EN)
Paste: =regexmatch(to_text(K4); "[0-3][0-9] (Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec) at [0-2][0-9]\:[0-5][0-9]")
Make sure that instead of K4 in "to_text(K4)" there is a upper-left cell from the selected range
Save
Hope it helps someone :)
You may try the formula for data validation:
=not(iserror(SUBSTITUTE(A1," at","")*1))*(len(A1)=15)*(right(A1,2)*1<61)
not(iserror(SUBSTITUTE(A1," at","")*1)) checks all statemant is legal date
(len(A1)=15) checks dates are entered with 2 digits
(right(A1,2)*1<61) cheks too much minutes, for some reason 01 Apr at 11:99 is a legal date..
Select the range of fields, where you need the data validation to occur to.
Press on -> Data -> Data validation
For "Criteria" select "Custom formula is"
Enter the following in the textfield next to "Custom formula is":
=regexmatch(Tablename!B2; "^[a-z_]*$")
Where as "Tablename" should be replaced by the table name and "B2" should be replaced by the first cell of the range.
Inside the "" you enter then your regex-expression. Here this would allow only small letters and underscores.
Using the to_text() function additionally didn't work for me. So you should maybe avoid it in order to make sure, that it works.
Press save

Access 2010 Query add text to end of existing text if condition is met

I have a column of data, diagnosis codes to be exact. the problem is that when the data is imported it turns 111.0 into 111 (or any whole number). I am wondering if there is an update query I can run that will add the ".0" to the end of any value that is 3 characters long. I had a problem of it stripping a value from 008.45 to 8.45 but I figured that part out using:
UPDATE Master SET DIAGNOSIS01 = LEFT("00", 3-LEN(DIAGNOSIS01)) + DIAGNOSIS01
WHERE LEN(DIAGNOSIS01)<3 AND Len(DIAGNOSIS01)>0;
I got that from here on stackoverflow. Is there a variation of this update query I can use to add to the right if it's only 3 digits?
Additional info... formats of the values in this column include xxx.x or xxx.xx with x being a number
When it comes to sql I am very new so please treat me like I'm 3... ;)
UPDATE Master
SET Master.DIAGNOSIS01 = IIf(Len([Master].[DIAGNOSIS01])=3,[Master].[DIAGNOSIS01] & ".0",[Master].[DIAGNOSIS01]);

Format mask for number field items: trailing and 'leading' zero

I'm having some trouble with displaying numbers in apex, but only when i fill them in through code. When numbers are fetched through an automated row fetch, they're fine!
Leading Zero
For example, i have a report where a user can click a link, which runs a javascript function. There i get detailed values for that record through an application process. The returned values are in JSON. Several fields are number fields.
My response looks as follows (fe):
{"AVAILABLE_STOCK": "15818", "WEIGHT": ".001", "VOLUME": ".00009", "BASIC_PRICE": ".06", "COST_PRICE": ".01"}
Already the numbers here 'not correct': values less than one do not have a zero before the .
I kind of hoped that the format mask on the items would catch this. If i specify FM999G990D000 for the item weight, i'd expect it to show '0.001' .
But okay, i suppose it only works that way when it comes through session state, and not when you set an item value through $("#").val() ?
Where do i go wrong? Is my only option to change my select in the app process?
Now:
SELECT '"AVAILABLE_STOCK": "' || AVAILABLE_STOCK ||'", '||
'"WEIGHT": "' || WEIGHT ||'", '||
'"VOLUME": "' || VOLUME ||'", '||
'"BASIC_PRICE": "' || BASIC_PRICE ||'", '||
Do i need to provide my numberfields a to_char with the format mask here (to_char(available_stock, 'FM999G990D000')) ?
Right now i need to put my numbers between quotes ofcourse, or i get invalid json when i parse it.
Trailing Zero
I have an application process on a page on the after header point, right after an automated row fetch. Several fields are calculated here (totals). The variables used are all specified as number(10, 2). All values are correct and rounded to 2 values after the comma. My format masks on the items are also specified as FM999G999G990D00.
However, when one of the calculated values has only one meaningfull value after the comma, the trailing zeros get dropped. Instead of '987.50', it is displayed as '987.5'.
So, i have a number variable, and assign it like this: :P12_NDB_TOTAL_INCL := v_totI;
Would i need to convert my numbers here too, with format mask?
What am i doing wrong, or what am i missing?
If you aren't doing math on it and are more concerned with formatting, I suggest treating it as a varchar/string instead of as a number wherever you can.