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Demo page

This page gives longer demos of the core pynvl functions and their pd_* pandas equivalents.

🔹 NVL

Substitute a value when a None value is encountered.

NVL( string1, replace_with)

from pynvl import nvl

print(nvl(None, 5))      # 5
print(nvl("hello", 99))  # 'hello'

# Nesting - Use email if exists, fallback to phone then office. Show 'No contacts if all are None.
email = phone = office = office_extension = None

# Core Python - If-elif bloat
if email is not None:
    primary_contact = email
elif phone is not None:
    primary_contact = phone
elif office_extension is not None:
    primary_contact = office
else:
    primary_contact = "No contacts"

# With pynvl
print(nvl(nvl(nvl(email, phone), office), "No contacts"))

🔹 SIGN

Returns a value indicating the sign of a number

sign(number)

from pynvl import sign

print(sign(-5))  # -1
print(sign(0))   # 0
print(sign(9))   # 1

# Simplified expressions
balance = 500

# Core Python - If-elif bloat
if balance > 0:
    status_if = "In Credit"
elif balance == 0:
    status_if = "Zero Balance"
else:
    status_if = "Overdrawn"

# With pynvl
status = {1: "In Credit", 0: "Zero Balance", -1: "Overdrawn"}[sign(balance)]

🔹 DECODE

if-elif-else functionality

decode(expression , search , result [, search , result]... [, default] )

If no matches are found, the DECODE function will return default.

If default is omitted, then the DECODE function will return None (if no matches are found).

from pynvl import decode

print(decode("A", "A", "Alpha", "B", "Beta", default="Unknown")) # 'Alpha'
print(decode("Z", "A", "Alpha", "B", "Beta", "Fallback")) # 'Fallback'
print(decode("Z", "A", "Alpha", "B", "Beta")) # None

# Remove multiple if-elif tests - Clean and easy to read
status_code = None

# Core Python - If-elif bloat
if status_code == "A":
    customer_status_if = "Active"
elif status_code == "B":
    customer_status_if = "Blocked"
elif status_code == "C":
    customer_status_if = "Closed"
elif status_code is None:
    customer_status_if = "Unknown"
else:
    customer_status_if = "Other"

# With pynvl
customer_status = decode(
    status_code,
    "A", "Active",
    "B", "Blocked",
    "C", "Closed",
    None, "Unknown",
    default="Other"
)

🔹 NONEIF

If expr1 and expr2 are equal, the NONEIF function returns NONE. Otherwise, it returns expr1.

NONEIF( expr1, expr2 )

from pynvl import noneif

print(noneif(5, 5))   # None
print(noneif(7, 8))   # 7

primary = "alice@example.com"
backup = "alice@example.com"

# Core Python - If-else bloat
if backup == primary:
    contact_if = primary
else:
    contact_if = backup if backup is not None else primary

# With pynvl
contact = noneif(backup, primary) or primary # alice@example.com

🔹 NVL2

Lets you substitutes a value when a null value is encountered as well as when a non-null value is encountered.

NVL2( string1, value_if_not_none, value_if_none )

from pynvl import nvl2

print(nvl2("X", "not-none", "is-none"))  # 'not-none'
print(nvl2(None, "not-none", "is-none")) # 'is-none'

discount_code = "ABC"

# Core Python - If-else bloat
if discount_code is not None:
    message_if = "Discount applied!"
else:
    message_if = "No discount available"

# With pynvl
message = nvl2(discount_code, "Discount applied!", "No discount available")  # Discount applied!

🔹 COALESCE

Returns the first non-None expression in the parameter list. If all expressions evaluate to None then coalesce will return None.

COALESCE( expr1, expr2, ..., expr_n)

from pynvl import coalesce

print(coalesce(None, None, 5, 10)) # 5

port_address = None
ip_address = None
mac_address = "A1:B2:C3:D4:E5:F6"

# Core Python - If-elif bloat
if port_address is not None:
    address_if = port_address
elif ip_address is not None:
    address_if = ip_address
elif mac_address is not None:
    address_if = mac_address

# With pynvl
address = coalesce(port_address, ip_address, mac_address) # "A1:B2:C3:D4:E5:F6"

🔹 Pandas Integration

import pandas as pd
from pynvl import pd_sign, pd_nvl, pd_nvl2, pd_noneif, pd_decode, pd_coalesce

s = pd.Series([-5, 0, 3, None])

print(pd_sign(s).tolist())
# [-1, 0, 1, None]

print(pd_nvl(s, 99).tolist())
# [-5, 0, 3, 99]

print(pd_nvl2(s, "not-null", "is-null").tolist())
# ['not-null', 'not-null', 'not-null', 'is-null']

print(pd_noneif(s, 0).tolist())
# [-5, None, 3, None]

print(pd_decode(s, -5, "neg", 0, "zero", 3, "pos", default="other").tolist())
# ['neg', 'zero', 'pos', 'other']

a = pd.Series([None, 2, None, 4])
b = pd.Series([1, None, 3, None])
c = pd.Series([9, 9, 9, 9])
out = pd_coalesce(a, b, c)
# [1, 2, 3, 4]