Pickling and UnPickling in python |Serialization and Deserialization | Telugu | Python for beginners

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### Pickling and Unpickling in Python

**Pickling** is the process of converting a Python object into a byte stream, and **unpickling** is the reverse process of converting the byte stream back into a Python object. This process is useful for saving complex data structures to a file or sending them over a network.

The `pickle` module in Python is used for serializing and deserializing Python objects.

### Example: Pickling and Unpickling a Dictionary

Here's a step-by-step example using a dictionary `data = {'name': 'Sweety', 'age': 30, 'subject': 'python'}`.

#### Step 1: Pickling the Data

First, we will serialize (pickle) the dictionary and save it to a file.

```python
import pickle

# Data to be pickled
data = {'name': 'Sweety', 'age': 30, 'subject': 'python'}

# Serialize and save to a file

```

#### Step 2: Unpickling the Data

Next, we will deserialize (unpickle) the data from the file and convert it back to a Python object.

```python
import pickle

# Deserialize and load from the file

print("Loaded data:", loaded_data)
```

### Complete Code Example

```python
import pickle

# Step 1: Pickling the data
data = {'name': 'Sweety', 'age': 30, 'subject': 'python'}

# Serialize and save to a file

# Step 2: Unpickling the data

print("Loaded data:", loaded_data)
```

### Explanation

1. **Pickling:**
- The file is opened in binary write mode (`'wb'`).

2. **Unpickling:**
- The file is opened in binary read mode (`'rb'`).

### Advantages of Pickling

- **Persistence:** Easily save and load complex data structures to and from files.
- **Portability:** Transmit Python objects over a network in a format that can be deserialized by other Python programs.
- **Versatility:** Supports a wide range of Python data types, including custom classes.

### Security Note

**Caution:** Unpickling data from an untrusted source can be dangerous, as it may execute arbitrary code. Always ensure that the source of the pickle file is trustworthy.

In summary, pickling and unpickling allow you to serialize and deserialize Python objects, making it easier to save and transmit complex data structures.