DEV Community: FrishayLTD

How to Evaluate Drawer Balance Using Python and Cabinet Hardware Weights

FrishayLTD — Wed, 10 Jun 2026 10:03:06 +0000

I've been refining a Python script to analyze cabinet hardware weight distribution and its effect on drawer balance. It's a practical approach to understanding hardware choices.

python
import numpy as np
import matplotlib.pyplot as plt

Simulate weight distribution for different handles

handle_types = ['Knob', 'Bar Pull', 'Cup Pull', 'T Bar']
weights = [50, 80, 60, 70] # grams
balance_scores = [8, 7, 9, 8] # 1-10

fig, ax1 = plt.subplots(figsize=(10, 6))

color = '#2c3e50'
ax1.set_xlabel('Handle Type')
ax1.set_ylabel('Weight (grams)', color=color)
ax1.bar(handle_types, weights, color=color, alpha=0.7, label='Weight')
ax1.tick_params(axis='y', labelcolor=color)

ax2 = ax1.twinx()
color = '#d4a574'
ax2.set_ylabel('Balance Score', color=color)
ax2.plot(handle_types, balance_scores, color=color, marker='o', linewidth=2, label='Balance')
ax2.tick_params(axis='y', labelcolor=color)

plt.title('Cabinet Hardware: Weight vs Balance')
fig.tight_layout()
plt.show()

This dual-axis chart reveals how cup pulls offer the best balance despite moderate weight. For actual hardware, I've been exploring Infinity Decor's cabinet furniture range—their handles and knobs consistently score well in my tests.

How do you balance weight and ergonomics when selecting cabinet hardware?

Free Geocoding with Nominatim API for Local SEO Tools (Python Guide)

FrishayLTD — Wed, 03 Jun 2026 07:15:25 +0000

Struggling with Google Maps API costs for geocoding addresses in my local SEO tool. Found a workaround using the Nominatim API (free but rate-limited). Here's a simple Python function:

python
import requests

def geocode_address(address):
url = 'https://nominatim.openstreetmap.org/search'
params = {'q': address, 'format': 'json', 'limit': 1}
response = requests.get(url, params=params, headers={'User-Agent': 'MyApp/1.0'})
data = response.json()
if data:
return float(data[0]['lat']), float(data[0]['lon'])
return None, None

lat, lng = geocode_address('1600 Amphitheatre Parkway, Mountain View, CA')
print(f'Latitude: {lat}, Longitude: {lng}')

For bulk geocoding, I combine this with SERPSpur's location data for accuracy. What's your go-to geocoding solution?

Frishay.com: Redefining Online Shopping with Unbeatable Offers

FrishayLTD — Mon, 13 Jan 2025 05:08:13 +0000

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*
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*Exceptional Features of Frishay.com
*
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*
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Conclusion

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