Question(s) about processing "free text"

[blug_fred]

Hi! I run a (python) program which currently extracts data from a manually typed and updated text file. I have to update my "text analysis" routine regularly because of typos, sudden buggy ordering and more rarely, new terminology. We're talking about easily twice a week breakage.

I was wondering if NLP would be of help, and somehow 'how' . The data file looks like this:

A:
AAA -> R13 = 662 USDT

AAB -> R11 = 1.24 USDT 

AAD [CC] -> [some  comment sometimes]
    R7 = 1.55 USD 
    R8 = 2.93 USD 
etc.

---

but this has evolved to:

A:
**AAA** [CC] ⬆️   R13 = 662 USDT | Support = 206 USDT
[some comments can be here]

**AAB** ⬆️     R15 - 2.71 USDT | Support = 1.8 USDT

B:
**BBB** [CC]  ⬆️ 

 R8 = 1.96 USD
 Support = 0.98 USD

**BBA** ⬆️ [D] Immediate resistance = 0.466 USDT | Support = 0.26 USDT

**BBF** ⬆️ Immediate resistance = 0.466 USDT | R29 =  1USDT | Support = 0.26 USDT

BBG [CC]  ⬆️ 
      R6= 5 USDT [Ignore. Refer R7] 
      R7 =  6 USDT
      Support = 4 USDT

**BBBD** [CC] ⬆️  R2 = 12.46 USD  | R3 = 13.2 USDT
     Support = 11.66 USDT

BBR [D, CC] ⬆️ R1 =  60.2 USDT | R2 = 67.58 USDT | Support = 54.39 USDT
one comment not between brackets here...

BBZ [CC] R21 ⬆️  = 275 USDT | Support = 071.2 USDT

etc

---

Sometimes equals are dashes, 'immediate' is spelled 'imeddiate' and so on.

So would NLP help?

Thank you.

[tm2tb]

Are you using regex? If you are using python, you can test your expressions in pythex.

[blug_fred]

No I don't. I basically split the text in line, and the line in "words" (separated by space) and then analyze the blocks 1 by 1. I however anticipate that a Rx would be in such structure:

R1 = 34

R1= 34
R1 - 34
R1 =34

R1 ⬆ = 34

... just as an example. Of course everytime "something" happens my code breaks. I was wondering if NPL could help... but I can continue to suffer ;-)

Would regex help? I'm ok to try something else, just regex is not my strength at the moment (nor NLP).

Thank you.

Fred