## 📁 Python FileProcessor Class — Reading and Analyzing Numbers from a File

📁 Python FileProcessor Class — Reading and Analyzing Numbers from a File

When working with data files, it’s common to extract numbers and calculate basic statistics like sum, average, min, and max. Today, I’ll walk you through a simple but powerful Python class called FileProcessor that does exactly that! 🧮

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💡 목표

이 글에서는 다음을 다룹니다:

• 파일에서 숫자 데이터를 읽어오기
• 읽어온 숫자 리스트의 합계, 평균, 최소, 최대값 계산하기
• 클래스 기반 구조로 깔끔하게 정리하기

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📦 파일 예시 (Numbers.txt)

1.5
2.3
5.0
4.1
-1.2

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✅ FileProcessor 클래스 코드

class FileProcessor:
    def __init__(self, file_name):
        self.file_name = file_name
        self.data = []
        self.__read_file()  # 객체가 생성될 때 파일 읽기 실행

    def __read_file(self):
        with open(self.file_name, 'r') as f:
            for line in f:
                try:
                    number = float(line.rstrip())  # 줄 끝 개행 제거 후 실수형 변환
                    self.data.append(number)
                except ValueError:
                    continue  # 숫자로 변환할 수 없는 줄은 무시

    def sum(self):
        return sum(self.data)

    def average(self):
        if len(self.data) == 0:
            raise ZeroDivisionError("No data to average")
        return sum(self.data) / len(self.data)

    def min(self):
        return min(self.data)

    def max(self):
        return max(self.data)

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🔍 사용 예시

p = FileProcessor('Numbers.txt')

print("Data:", p.data)
print("합계:", p.sum())
print("평균:", p.average())
print("최소값:", p.min())
print("최대값:", p.max())

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🛠️ 내부 작동 설명

• __init__(): 파일 이름 저장 및 자동으로 __read_file() 실행
• __read_file(): 줄 단위로 읽고 float으로 변환 후 self.data에 저장
• sum(), average(), min(), max(): 각각의 통계 정보를 리턴

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🙋‍♀️ 꿀팁

• 숨겨진 메서드 호출: __read_file()은 __로 시작해 외부에서 직접 호출할 수 없어요. (name mangling)
  • 원하면 p._FileProcessor__read_file() 으로 호출할 수 있어요.
• 예외 처리: 잘못된 데이터로 인해 프로그램이 멈추지 않도록 try-except를 사용합니다.

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🔚 마무리

이제 여러분은 FileProcessor 클래스를 통해 숫자 데이터를 읽고 간단한 통계 정보를 자동으로 얻을 수 있습니다. 실제 데이터 분석이나 로그 파일 전처리 같은 상황에서 유용하게 활용해보세요!

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Yes, exactly! 😄

When you use dir(object) in Python, it returns all the attributes and methods of that object — including the "hidden" or private ones that start with double underscores (__), which are name-mangled by Python.

🔍 예시로 다시 살펴볼게요:

p = FileProcessor('Numbers.txt')
print(dir(p))

출력 결과에는 이런 게 포함되어 있을 거예요:

['_FileProcessor__read_file', ...]

Python은 __read_file() 같은 메서드를 외부에서 실수로 접근하지 못하도록 클래스이름__메서드이름 형식으로 바꿔 저장해요. 이를 name mangling이라고 합니다.

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🔓 접근하는 방법

p._FileProcessor__read_file()

이렇게 하면 은닉된 메서드도 호출할 수 있어요, 다만 일반적인 사용자는 사용하지 말라는 뜻으로 __로 감춰놓은 거니, 정말 필요한 경우에만 써야 해요.

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🧠 요약

• dir()로 숨겨진 메서드 확인 가능
• __method() → ._ClassName__method() 형태로 접근 가능
• 보안 목적이 아니라 실수 방지 목적이니 너무 믿지 말 것!

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Great question — and you're thinking deeply, which is awesome! 💡 Let's break it down gently and clearly:

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✅ What happens if you do not call self.__read_file() in __init__?

Your FileProcessor class is written like this:

class FileProcessor:
    def __init__(self, file_name):
        self.file_name = file_name
        self.data = []
        # self.__read_file()  ← This is what you're asking about

If you don't call self.__read_file() here, then self.data will stay an empty list, and any of the following calls:

p = FileProcessor("Numbers.txt")
p.average()

will raise this error:

ZeroDivisionError

Because len(self.data) is still 0.

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❗ But what if I try to call the hidden method directly?

You might think:

p.__read_file()

But this gives:

AttributeError: 'FileProcessor' object has no attribute '__read_file'

Because Python renamed it (name mangling).

If you want to force the method call, you can do this:

p._FileProcessor__read_file()

Then your .data list will be filled properly, and your .average() method will work.

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✅ Summary

Situation	Will it work?	Why
self.__read_file() in __init__	✅ Yes	Automatically reads the file on object creation
Skip self.__read_file()	❌ Not directly	You'll have to manually call it using the mangled name
Call p.__read_file()	❌ No	Python hides it (name mangling)
Call p._FileProcessor__read_file()	✅ Yes	You bypass the name mangling and call it manually

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That line:

if len(self.data) == 0: raise ZeroDivisionError

is a way to manually raise an error when there's no data in the list. Let me explain gently and clearly:

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🌱 What does it mean?

It checks if the self.data list is empty. If it is, it stops the program and raises a ZeroDivisionError.

In context, it looks like this:

def average(self):
    if len(self.data) == 0:
        raise ZeroDivisionError
    return sum(self.data) / len(self.data)

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🤔 Why raise a ZeroDivisionError?

Because dividing by zero (which would happen if the list is empty) is a mathematical error. This line is basically saying:

“There's nothing to average — we can't divide by zero!”

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💡 Friendlier way (optional improvement)

Raising an error is correct, but you could also show a message:

if len(self.data) == 0:
    raise ZeroDivisionError("Cannot calculate average from empty data.")

Now when the error happens, it tells you why.

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This line:

def min(self):
    return min(self.data)

causes a recursion error because you're defining a method named min, and then inside that method, you're trying to call min(self.data) — but Python now thinks you're trying to call your own method again, not the built-in min() function. This leads to infinite recursion.

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🧠 How to fix it?

You can fix it by telling Python to use the built-in min() function explicitly using the builtins module:

import builtins

def min(self):
    return builtins.min(self.data)

Or, better yet, to avoid confusion, you can rename your method:

def get_min(self):
    return min(self.data)

This keeps your code clear and avoids name conflicts. The same goes for max().

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Summary:

• ✅ min() — built-in function
• 🚫 min(self) — recursive trap!
• 💡 Rename your method or use builtins.min() if you want to keep the name.