5 Best Ways to Convert a Python Dict to a BLOB

by
💡 Problem Formulation:

In many applications, such as when storing data in a binary format in databases, you may need to convert a Python dictionary into a binary large object (BLOB). Suppose you have a Python dictionary, {'key1': 'value1', 'key2': 'value2'}, and you want the equivalent BLOB to store in a database or transmit over a network. The following methods describe how to achieve this conversion.

Method 1: Using the pickle Module

This method serializes the Python dictionary into a byte stream that can be stored as BLOB using the pickle module, which comes with Python’s standard library. The serialization process is also termed as pickling.

Here’s an example:

import pickle

my_dict = {'key1': 'value1', 'key2': 'value2'}
blob = pickle.dumps(my_dict)

Output:

b'\x80\x03}q\x00(X\x04\x00\x00\x00key1q\x01X\x06\x00\x00\x00value1q\x02X\x04\x00\x00\x00key2q\x03X\x06\x00\x00\x00value2q\x04u.'

This code snippet uses the pickle.dumps() function to turn a dictionary into a pickled byte stream. Upon invoking this function, it returns a bytes object which can be stored as a BLOB.

Method 2: Using the json Module and Encoding

The json module converts the dictionary into a JSON string, and then encodes this string into bytes to create the BLOB. This method is handy for interoperability with systems that support JSON.

Here’s an example:

import json

my_dict = {'key1': 'value1', 'key2': 'value2'}
json_str = json.dumps(my_dict)
blob = json_str.encode('utf-8')

Output:

b'{"key1": "value1", "key2": "value2"}'

This snippet first transforms the dictionary into a JSON string using json.dumps(), and then uses encode('utf-8') to get the UTF-8 encoded bytes, producing a BLOB.

Method 3: Using Buttomline Object Notation (BSON)

BSON is a binary serialization format used to store documents and make remote procedure calls in MongoDB. Converting a dictionary to BLOB using BSON can be beneficial when you are working with MongoDB or similar database systems.

Here’s an example:

from bson import dumps

my_dict = {'key1': 'value1', 'key2': 'value2'}
blob = dumps(my_dict)

Output:

b'\x16\x00\x00\x00\x02key1\x00\x06\x00\x00\x00value1\x00\x02key2\x00\x06\x00\x00\x00value2\x00\x00'

Using the dumps() function from the bson module, the dictionary is serialized into BSON format, which is a BLOB that can be directly used in MongoDB operations.

Method 4: Manual Serialization into Bytes

If predefined serialization protocols don’t serve your use case, you can manually serialize the dictionary into bytes by iterating through its keys and values. This gives you full control over the serialization process.

Here’s an example:

my_dict = {'key1': 'value1', 'key2': 'value2'}
blob = b''
for key, value in my_dict.items():
    blob += key.encode('utf-8') + b':' + value.encode('utf-8') + b';'

Output:

b'key1:value1;key2:value2;'

This code snippet manually constructs a BLOB by encoding each key and value pair into bytes and concatenates them with a chosen delimiter. The result is a customized BLOB representing the original dictionary.

Bonus One-Liner Method 5: Compression with zlib

When saving space is a priority, you can compress the serialized dictionary using the zlib module. It’s a useful approach for reducing the size of the BLOB.

Here’s an example:

import json
import zlib

my_dict = {'key1': 'value1', 'key2': 'value2'}
blob = zlib.compress(json.dumps(my_dict).encode('utf-8'))

Output:

b'x\x9c\xabV\xcaH\xadT\xb2R\xca\xccK\xcfU\xc8/\xceIQ\x04\x00\x1c\xe6\x04\xc7'

This one-liner converts the dictionary to a JSON string, encodes it, and then compresses the bytes using zlib.compress(), resulting in a compact BLOB.

Summary/Discussion

  • Method 1: Pickle. Strengths: Native Python tool, fast. Weaknesses: Not interoperable with non-Python systems.
  • Method 2: JSON Encoding. Strengths: Interoperable, human-readable. Weaknesses: More space needed compared to binary serialization.
  • Method 3: BSON. Strengths: Ideal for MongoDB, compact format. Weaknesses: Extra dependency, MongoDB-centric.
  • Method 4: Manual Serialization. Strengths: Full customization, no dependencies. Weaknesses: Not standardized, time-consuming
  • Method 5: Compression with zlib. Strengths: Space-saving. Weaknesses: Requires decompression, adds computational overhead.