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LiteJsonDb Utility Functions

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Coding Team edited this page Aug 4, 2024 · 1 revision

These functions are designed to make your coding life easier, more organized, and a bit more fun. 🌟

Why Use Utility Functions?

Utility functions are your best friends when it comes to writing clean, efficient, and reusable code. By using these pre-built helpers, you avoid rewriting the same logic over and over again, which means fewer bugs and more time for enjoying coding (or coffee breaks ☕). Plus, they're like the Swiss Army knife of coding—compact, versatile, and incredibly handy.

Table of Contents

  1. Initialization
  2. Utility Functions
  3. Example Usage

Initialization

To kick things off with LiteJsonDb, initialize your database. You can even enable encryption if you want that extra layer of security!

import LiteJsonDb

# Initialize the database with encryption enabled
db = LiteJsonDb.JsonDB(crypted=True)

Utility Functions

Here’s a run-down of the utility functions you’ll find super useful:

Convert to Datetime

Convert a string to a datetime object. Perfect for handling date and time data.

if "profile" in data and "joined" in data["profile"]:
    joined_date = db.convert_to_datetime(data["profile"]["joined"])
    print("\nJoined Date:", joined_date)
else:
    print("No join date found for user 1.")

Get or Default

Fetch a value from your data or return a default if the key is not found.

name = db.get_or_default(data, "name", "Anonymous")
print("\nName:", name)

Key Exists or Add

Check if a key is present in your data; if not, add it with a default value.

db.key_exists_or_add(data, "Nickname", "Ali")
print("\nData with Nickname:")
db.pretty_print(data)

Normalize Keys

Convert all keys in your dictionary to lowercase for consistency.

normalized_data = db.normalize_keys(data)
print("\nNormalized Keys:")
db.pretty_print(normalized_data)

Flatten JSON

Transform nested JSON into a flat dictionary. Great for simplifying complex structures!

normalized_data = db.flatten_json(data)
print("\nFlattened JSON:")
db.pretty_print(normalized_data)

Filter Data

Filter your list based on a condition. Perfect for sifting through data.

data_list = [{"name": "Aliou", "age": 35}, {"name": "Max", "age": 21}]
filtered_data = db.filter_data(data_list, lambda d: d["age"] > 25)
print("\nFiltered Data:")
db.pretty_print(filtered_data)

Sort Data

Sort your data by a specific key. Whether ascending or descending, it’s all under control.

sorted_data = db.sort_data(data_list, lambda d: d["age"])
print("\nSorted Data:")
db.pretty_print(sorted_data)

Hash Password

Hash a password using SHA-256 to keep it secure and out of reach from prying eyes.

password = "securepassword123"
hashed = db.hash_password(password)
print("\nHashed Password:", hashed)

Check Password

Verify if the given password matches the hashed one. Security at its finest!

is_correct = db.check_password(hashed, password)  # change value to check
print("Password Verification:", is_correct)  # True

Sanitize Output

Protect against XSS attacks by sanitizing your output. Keeping your app safe and sound! [XSS VULNERABILITY IS EVERYWHERE :)]

unsanitized_data = {"bio": "<script>alert('hack');</script>"}

sanitized_data = db.sanitize_output(unsanitized_data)
print("\nSanitized Output:")
db.pretty_print(sanitized_data)

Example Usage

Here’s a full example showing how you can put these functions to work:

import LiteJsonDb

# Initialize the database with encryption enabled
db = LiteJsonDb.JsonDB(crypted=True)

# Editing data
db.edit_data("users/1", {
    "profile": {
        "joined": "2023-08-04",  
        "name": "John Doe",       
        "age": 30                
    }
})

data = db.get_data("users/1")


# Convert to Datetime
if "profile" in data and "joined" in data["profile"]:
    joined_date = db.convert_to_datetime(data["profile"]["joined"])
    print("\nJoined Date:", joined_date)
else:
    print("No join date found for user 1.")

# Get or Default
name = db.get_or_default(data, "name", "Anonymous")
print("\nName:", name)

# Key Exists or Add
db.key_exists_or_add(data, "Nickname", "Ali")
print("\nData with Nickname:")
db.pretty_print(data)

# Flatten JSON
normalized_data = db.flatten_json(data)
print("\nFlattened JSON:")
db.pretty_print(normalized_data)

# Normalize Keys
normalized_data = db.normalize_keys(data)
print("\nNormalized Keys:")
db.pretty_print(normalized_data)

# Filter Data
data_list = [{"name": "Aliou", "age": 35}, {"name": "Max", "age": 21}]
filtered_data = db.filter_data(data_list, lambda d: d["age"] > 25)
print("\nFiltered Data:")
db.pretty_print(filtered_data)

# Sort Data
sorted_data = db.sort_data(data_list, lambda d: d["age"])
print("\nSorted Data:")
db.pretty_print(sorted_data)

# Hash Password
password = "securepassword123"
hashed = db.hash_password(password)
print("\nHashed Password:", hashed)
is_correct = db.check_password(hashed, password)  # change value to check
print("Password Verification:", is_correct)  # True

# Sanitize Output
unsanitized_data = {"bio": "<script>alert('hack');</script>"}
sanitized_data = db.sanitize_output(unsanitized_data)
print("\nSanitized Output:")
db.pretty_print(sanitized_data)

# Retrieve the complete database
print(db.get_db(raw=True))

Feel free to explore these functions and make your code more efficient and secure. Happy coding! 🚀

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