Practical Python, Real Results

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<h2 class="py-title">Python That Ships</h2>
<p class="py-lead">Compact, production-minded snippets I use in real client work.</p><div class="py-grid"><!-- 1) Micro API (Flask) -->
<div class="py-card">
<h3>Micro API, Zero Bloat</h3>
<div class="py-badges"><span class="py-badge">Web</span><span class="py-badge">API</span><span class="py-badge">Flask</span></div>
<div class="py-desc">Tiny Flask service for forms/webhooks with health check and JSON echo.</div>
<div class="py-code">from flask import Flask, jsonify, requestapp = Flask(name)@app.get("/health")
def health():
return {"status": "ok"}@app.post("/echo")
def echo():
data = request.getjson(silent=True) or {}
return jsonify({"yousent": data}), 200if name == "main":
app.run(port=8000, debug=True)</div>
</div><!-- 2) CSV Cleaner (pandas) -->
<div class="py-card">
<h3>CSV Cleaner, On Tap</h3>
<div class="py-badges"><span class="py-badge">Data</span><span class="py-badge">ETL</span><span class="py-badge">pandas</span></div>
<div class="py-desc">Fix headers, types, and dupes; export a clean dataset in seconds.</div>
<div class="py-code">import pandas as pddf = pd.readcsv("input.csv")
df.columns = [c.strip().lower().replace(" ", "") for c in df.columns]
df = df.dropduplicates().dropna(how="all")if "email" in df.columns:
df["email"] = df["email"].astype(str).str.strip().str.lower()df.tocsv("clean.csv", index=False)
print("Saved clean.csv")</div>
</div><!-- 3) Uptime Monitor (requests) -->
<div class="py-card">
<h3>Ping • Alert • Relax</h3>
<div class="py-badges"><span class="py-badge">Automation</span><span class="py-badge">Ops</span><span class="py-badge">requests</span></div>
<div class="py-desc">Checks your URL on a schedule and flags issues before users do.</div>
<div class="py-code">import time, requestsURL = "https://www.sumandas.in"
INTERVAL = 300 # 5 minuteswhile True:
try:
r = requests.get(URL, timeout=8)
print(time.strftime("%Y-%m-%d %H:%M:%S"), "->", r.statuscode)
except Exception as e:
print(time.strftime("%Y-%m-%d %H:%M:%S"), "ERROR:", e)
time.sleep(INTERVAL)</div>
</div><!-- 4) Image → Brand Palette (Pillow) -->
<div class="py-card">
<h3>Image → Brand Palette</h3>
<div class="py-badges"><span class="py-badge">Design</span><span class="py-badge">Pillow</span><span class="py-badge">Visualization</span></div>
<div class="py-desc">Extract top five colors and render a neat, shareable swatch.</div>
<div class="py-code">from PIL import Image, ImageDraw
from collections import Counterdef topcolors(path, n=5):
img = Image.open(path).convert("RGBA").resize((400, 400))
px = [p for p in img.getdata() if p[3] > 0]
counts = Counter((r,g,b) for r,g,b,a in px)
return [rgb for rgb,_ in counts.mostcommon(n)]def swatch(colors, out="palette.png"):
w, h = 100len(colors), 120
im = Image.new("RGB", (w,h), "white")
d = ImageDraw.Draw(im)
for i,c in enumerate(colors):
x = i100
d.rectangle([x,0,x+100,100], fill=c)
im.save(out)if name == "main":
cols = topcolors("input.jpg", n=5)
swatch(cols, "palette.png")</div>
</div><!-- 5) Dual-Tone Ringtone (stdlib) -->
<div class="py-card">
<h3>Dual-Tone Ringtone (440/480)</h3>
<div class="py-badges"><span class="py-badge">Audio</span><span class="py-badge">Telecom</span><span class="py-badge">Stdlib</span></div>
<div class="py-desc">Generate IVR-ready WAV tones with precise on/off cadence.</div>
<div class="py-code">import math, wave, structdef sine(f, t, sr=8000):
return [math.sin(2math.pif(i/sr)) for i in range(int(tsr))]def normalize(samples):
m = max(abs(x) for x in samples) or 1
return [int(32767 * (x/m)) for x in samples]def writewav(samples, path, sr=8000):
with wave.open(path, "w") as w:
w.setnchannels(1); w.setsampwidth(2); w.setframerate(sr)
for s in samples: w.writeframes(struct.pack(&#39;&lt;h&#39;, s))def makedualtone(f1=440, f2=480, on=2.0, off=4.0, cycles=2, sr=8000):
out = []
for _ in range(cycles):
onp = [(a+b)/2 for a,b in zip(sine(f1,on,sr), sine(f2,on,sr))]
offp = [0.0]int(offsr)
out.extend(onp + offp)
return normalize(out)if name == "main":
data = makedualtone()
writewav(data, "ringtone.wav")</div>
</div><!-- 6) Async Fetch (httpx + asyncio) -->
<div class="py-card">
<h3>Async Fetch at Scale</h3>
<div class="py-badges"><span class="py-badge">Async</span><span class="py-badge">I/O</span><span class="py-badge">httpx</span></div>
<div class="py-desc">Concurrent HTTP requests with timeouts—starter for scrapers and status.</div>
<div class="py-code">import asyncio, httpxURLS = ["https://example.com", "https://httpbin.org/get"]async def fetch(url, client):
r = await client.get(url, timeout=10)
return url, r.status_codeasync def main():
async with httpx.AsyncClient() as client:
results = await asyncio.gather(*(fetch(u, client) for u in URLS))
for url, status in results:
print(url, status)if name == "main":
asyncio.run(main())</div>
</div></div>
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Nulla commodo

Suman Das

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