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<!DOCTYPE html>
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<title>Python Interview Cheat Sheet</title>
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<meta property="og:description" content="Concise Python reference covering data structures, algorithms, built-ins, and common interview patterns.">
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<span style="color:#f2ece0;">Python Interview Cheat Sheet</span>
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<header>
<h1>Python Cheat Sheet</h1>
<p>Interview-Ready Reference — Arrays · Dicts · Sets · Strings · Collections · Builtins</p>
</header>
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<!-- ═══════════════════════════════ LIST / ARRAY ═══════════════════════════════ -->
<div class="card c1" data-tags="list array append pop insert remove sort reverse index count extend copy clear slice">
<div class="card-header">
<div class="dot"></div>
<h2>List (Dynamic Array)</h2>
<span class="type-badge">mutable · ordered · O(1) append</span>
</div>
<pre>
<span class="cm"># Creation</span>
a = [] <span class="cm"># empty list</span>
a = [<span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">3</span>]
a = [<span class="nm">0</span>] * <span class="nm">5</span> <span class="cm"># [0, 0, 0, 0, 0]</span>
a = <span class="bi">list</span>(<span class="bi">range</span>(<span class="nm">5</span>)) <span class="cm"># [0, 1, 2, 3, 4]</span>
a = [x**<span class="nm">2</span> <span class="kw">for</span> x <span class="kw">in</span> <span class="bi">range</span>(<span class="nm">5</span>)] <span class="cm"># comprehension</span>
<span class="cm"># ── Core mutations ─────────────────────────────</span>
a.append(x) <span class="cm"># O(1) add to right</span>
a.pop() <span class="cm"># O(1) remove+return from right</span>
a.pop(<span class="nm">0</span>) <span class="cm"># O(n) remove from left — use deque!</span>
a.insert(<span class="nm">2</span>, x) <span class="cm"># O(n) insert at index</span>
a.remove(x) <span class="cm"># O(n) removes FIRST occurrence</span>
a.extend([<span class="nm">4</span>,<span class="nm">5</span>]) <span class="cm"># += in place; faster than + (no copy)</span>
a.clear() <span class="cm"># empties list, keeps object</span>
<span class="cm"># ── Access & search ────────────────────────────</span>
a[<span class="nm">0</span>], a[-<span class="nm">1</span>] <span class="cm"># first, last — O(1)</span>
a[<span class="nm">1</span>:<span class="nm">4</span>] <span class="cm"># slice [1,4) — returns new list</span>
a[::-<span class="nm">1</span>] <span class="cm"># reversed copy</span>
a.index(x) <span class="cm"># first index of x — raises if missing</span>
a.count(x) <span class="cm"># how many times x appears — O(n)</span>
x <span class="kw">in</span> a <span class="cm"># membership — O(n)! use set for O(1)</span>
<span class="cm"># ── Sorting ─────────────────────────────────────</span>
a.sort() <span class="cm"># in-place, stable, O(n log n)</span>
a.sort(reverse=<span class="kw">True</span>)
a.sort(key=<span class="kw">lambda</span> x: x[<span class="nm">1</span>]) <span class="cm"># sort by field</span>
a.sort(key=<span class="kw">lambda</span> x: (x[<span class="nm">1</span>], -x[<span class="nm">0</span>])) <span class="cm"># multi-key</span>
<span class="bi">sorted</span>(a) <span class="cm"># returns NEW list, original unchanged</span>
a.reverse() <span class="cm"># in-place reverse — O(n)</span>
<span class="cm"># ── Copy & misc ─────────────────────────────────</span>
b = a.copy() <span class="cm"># shallow copy (same as a[:])</span>
b = a[:] <span class="cm"># also shallow copy — idiomatic</span>
<span class="bi">len</span>(a) <span class="cm"># O(1) — stored as attribute</span>
a + [<span class="nm">4</span>,<span class="nm">5</span>] <span class="cm"># concatenate — creates new list O(n)</span>
<span class="cm"># ── 2D / Matrix ────────────────────────────────</span>
matrix = [[<span class="nm">0</span>]*<span class="nm">3</span> <span class="kw">for</span> _ <span class="kw">in</span> <span class="bi">range</span>(<span class="nm">3</span>)] <span class="cm"># CORRECT</span>
bad = [[<span class="nm">0</span>]*<span class="nm">3</span>] * <span class="nm">3</span> <span class="cm"># WRONG — same row object 3 times!</span>
transposed = <span class="bi">list</span>(<span class="bi">zip</span>(*matrix)) <span class="cm"># elegant transpose</span>
flat = [x <span class="kw">for</span> row <span class="kw">in</span> matrix <span class="kw">for</span> x <span class="kw">in</span> row] <span class="cm"># flatten</span></pre>
</div>
<!-- ═══════════════════════════════ DICT / HASHMAP ════════════════════════════ -->
<div class="card c2" data-tags="dict hashmap keys values items get setdefault update pop defaultdict counter">
<div class="card-header">
<div class="dot"></div>
<h2>Dict (HashMap)</h2>
<span class="type-badge">mutable · O(1) avg lookup</span>
</div>
<pre>
<span class="cm"># Creation</span>
d = {}
d = {<span class="st">'a'</span>: <span class="nm">1</span>, <span class="st">'b'</span>: <span class="nm">2</span>}
d = <span class="bi">dict</span>(a=<span class="nm">1</span>, b=<span class="nm">2</span>)
d = <span class="bi">dict</span>(<span class="bi">zip</span>(keys, values)) <span class="cm"># zip two lists → dict</span>
d = {k: v <span class="kw">for</span> k, v <span class="kw">in</span> pairs} <span class="cm"># dict comprehension</span>
<span class="cm"># ── Read ────────────────────────────────────────</span>
d[<span class="st">'a'</span>] <span class="cm"># KeyError if missing</span>
d.get(<span class="st">'a'</span>) <span class="cm"># None if missing — SAFE</span>
d.get(<span class="st">'a'</span>, <span class="nm">0</span>) <span class="cm"># default value — very common</span>
<span class="st">'a'</span> <span class="kw">in</span> d <span class="cm"># O(1) key membership</span>
<span class="cm"># ── Write ───────────────────────────────────────</span>
d[<span class="st">'c'</span>] = <span class="nm">3</span> <span class="cm"># insert or overwrite</span>
d.setdefault(<span class="st">'c'</span>, []).append(x) <span class="cm"># init+append in one line</span>
d.update({<span class="st">'d'</span>: <span class="nm">4</span>}) <span class="cm"># merge another dict in</span>
d |= {<span class="st">'e'</span>: <span class="nm">5</span>} <span class="cm"># Python 3.9+ merge operator</span>
d.pop(<span class="st">'a'</span>) <span class="cm"># remove + return; KeyError if missing</span>
d.pop(<span class="st">'a'</span>, <span class="kw">None</span>) <span class="cm"># safe pop with default</span>
d.popitem() <span class="cm"># remove+return last inserted (LIFO)</span>
<span class="cm"># ── Iterate ─────────────────────────────────────</span>
d.keys() <span class="cm"># view of keys</span>
d.values() <span class="cm"># view of values</span>
d.items() <span class="cm"># view of (k, v) tuples — use this most</span>
<span class="kw">for</span> k, v <span class="kw">in</span> d.items(): <span class="cm"># idiomatic dict iteration</span>
<span class="kw">pass</span>
<span class="cm"># ── Group-by pattern (most powerful dict pattern) ─</span>
<span class="kw">from</span> collections <span class="kw">import</span> defaultdict
groups = defaultdict(<span class="bi">list</span>)
<span class="kw">for</span> item <span class="kw">in</span> data:
groups[key(item)].append(item) <span class="cm"># no KeyError, no setdefault</span>
count = defaultdict(<span class="bi">int</span>)
count[word] += <span class="nm">1</span> <span class="cm"># starts at 0 automatically</span>
<span class="cm"># ── Sorting a dict ──────────────────────────────</span>
<span class="bi">sorted</span>(d.items(), key=<span class="kw">lambda</span> x: x[<span class="nm">1</span>]) <span class="cm"># sort by value</span>
<span class="bi">sorted</span>(d.items(), key=<span class="kw">lambda</span> x: -x[<span class="nm">1</span>]) <span class="cm"># sort by value desc</span>
<span class="cm"># Python 3.7+: dict preserves insertion order</span></pre>
</div>
<!-- ═══════════════════════════════ SET ═══════════════════════════════════════ -->
<div class="card c3" data-tags="set add remove discard union intersection difference symmetric frozen">
<div class="card-header">
<div class="dot"></div>
<h2>Set (HashSet)</h2>
<span class="type-badge">mutable · O(1) lookup · unordered</span>
</div>
<pre>
<span class="cm"># Creation</span>
s = <span class="bi">set</span>() <span class="cm"># NOT {} — that's an empty dict!</span>
s = {<span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">3</span>}
s = <span class="bi">set</span>([<span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">2</span>, <span class="nm">3</span>]) <span class="cm"># deduplication — {1, 2, 3}</span>
s = {x <span class="kw">for</span> x <span class="kw">in</span> arr <span class="kw">if</span> x > <span class="nm">0</span>} <span class="cm"># set comprehension</span>
<span class="cm"># ── Mutation ────────────────────────────────────</span>
s.add(x) <span class="cm"># O(1) — no-op if already present</span>
s.remove(x) <span class="cm"># O(1) — KeyError if missing</span>
s.discard(x) <span class="cm"># O(1) — SAFE, no error if missing ✓</span>
s.pop() <span class="cm"># remove+return arbitrary element</span>
s.clear() <span class="cm"># empty the set</span>
<span class="cm"># ── Lookup ──────────────────────────────────────</span>
x <span class="kw">in</span> s <span class="cm"># O(1) — the whole reason to use a set</span>
<span class="bi">len</span>(s) <span class="cm"># O(1)</span>
<span class="cm"># ── Set algebra — operator syntax ───────────────</span>
a & b <span class="cm"># intersection: elements in BOTH</span>
a | b <span class="cm"># union: elements in EITHER</span>
a - b <span class="cm"># difference: in a but NOT b</span>
a ^ b <span class="cm"># symmetric diff: in one but NOT both</span>
a <= b <span class="cm"># is a a subset of b?</span>
a >= b <span class="cm"># is a a superset of b?</span>
<span class="cm"># ── Set algebra — method syntax (accepts any iterable) ─</span>
a.intersection(b)
a.union(b)
a.difference(b)
a.isdisjoint(b) <span class="cm"># True if no elements in common</span>
a.issubset(b)
a.issuperset(b)
<span class="cm"># ── Frozenset (hashable, can be dict key) ───────</span>
fs = <span class="bi">frozenset</span>([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>])
d[fs] = <span class="st">"value"</span> <span class="cm"># regular set can't be a key!</span>
<span class="cm"># ── Common patterns ─────────────────────────────</span>
seen = <span class="bi">set</span>()
<span class="kw">if</span> x <span class="kw">not in</span> seen:
seen.add(x) <span class="cm"># visit-once pattern (DFS, dedup)</span>
dupes = [x <span class="kw">for</span> x <span class="kw">in</span> arr <span class="kw">if</span> arr.count(x) > <span class="nm">1</span>] <span class="cm"># slow</span>
dupes = <span class="bi">list</span>(<span class="bi">set</span>(x <span class="kw">for</span> x <span class="kw">in</span> arr <span class="kw">if</span> arr.count(x)><span class="nm">1</span>)) <span class="cm"># better</span></pre>
</div>
<!-- ═══════════════════════════════ STRING ════════════════════════════════════ -->
<div class="card c4" data-tags="string str split join strip replace find count upper lower isalpha isdigit isalnum ord chr startswith endswith">
<div class="card-header">
<div class="dot"></div>
<h2>String</h2>
<span class="type-badge">immutable · hashable · sequence</span>
</div>
<pre>
<span class="cm"># Strings are immutable — every method returns a NEW string</span>
<span class="cm"># ── Case & cleaning ─────────────────────────────</span>
s.upper() <span class="cm"># "HELLO"</span>
s.lower() <span class="cm"># "hello"</span>
s.title() <span class="cm"># "Hello World"</span>
s.strip() <span class="cm"># remove leading+trailing whitespace</span>
s.lstrip() / s.rstrip()
s.strip(<span class="st">'*'</span>) <span class="cm"># strip specific characters</span>
<span class="cm"># ── Search & check ──────────────────────────────</span>
s.find(<span class="st">'x'</span>) <span class="cm"># index or -1 (safe)</span>
s.index(<span class="st">'x'</span>) <span class="cm"># index or ValueError (raises)</span>
s.count(<span class="st">'l'</span>) <span class="cm"># occurrences of substring</span>
s.startswith(<span class="st">'he'</span>)
s.endswith(<span class="st">'ld'</span>)
<span class="st">'sub'</span> <span class="kw">in</span> s <span class="cm"># substring check — O(n) but fast</span>
<span class="cm"># ── Type checks (returns bool) ──────────────────</span>
s.isalpha() <span class="cm"># all letters</span>
s.isdigit() <span class="cm"># all digits</span>
s.isalnum() <span class="cm"># letters or digits (no spaces/punct)</span>
s.isspace() <span class="cm"># all whitespace</span>
s.isupper() / s.islower()
<span class="cm"># ── Split & join ────────────────────────────────</span>
s.split() <span class="cm"># split on whitespace, strips empties</span>
s.split(<span class="st">','</span>) <span class="cm"># split on delimiter</span>
s.split(<span class="st">','</span>, maxsplit=<span class="nm">2</span>) <span class="cm"># limit splits</span>
s.splitlines() <span class="cm"># split on \n</span>
<span class="st">','</span>.join([<span class="st">'a'</span>,<span class="st">'b'</span>,<span class="st">'c'</span>]) <span class="cm"># 'a,b,c' — O(n), use this not +=</span>
<span class="st">''</span>.join([<span class="st">'h'</span>,<span class="st">'i'</span>]) <span class="cm"># 'hi' — build string from chars</span>
<span class="cm"># ── Replace & format ────────────────────────────</span>
s.replace(<span class="st">'old'</span>, <span class="st">'new'</span>)
s.replace(<span class="st">'o'</span>, <span class="st">'0'</span>, <span class="nm">2</span>) <span class="cm"># limit replacements</span>
f<span class="st">"Hello {name}, you are {age}"</span> <span class="cm"># f-string (preferred)</span>
f<span class="st">"{value:.2f}"</span> <span class="cm"># format float to 2 decimal places</span>
f<span class="st">"{n:04d}"</span> <span class="cm"># zero-pad integer</span>
<span class="cm"># ── Slicing & reversing ─────────────────────────</span>
s[<span class="nm">1</span>:<span class="nm">4</span>] <span class="cm"># substring</span>
s[::-<span class="nm">1</span>] <span class="cm"># reverse — 'hello' → 'olleh'</span>
s[::2] <span class="cm"># every other char</span>
<span class="cm"># ── Character ↔ integer ─────────────────────────</span>
<span class="bi">ord</span>(<span class="st">'a'</span>) <span class="cm"># 97</span>
<span class="bi">chr</span>(<span class="nm">97</span>) <span class="cm"># 'a'</span>
<span class="bi">ord</span>(c) - <span class="bi">ord</span>(<span class="st">'a'</span>) <span class="cm"># 0-25 index for lowercase letter</span>
<span class="cm"># ── Building strings efficiently ────────────────</span>
parts = []
<span class="kw">for</span> c <span class="kw">in</span> iterable:
parts.append(c)
result = <span class="st">''</span>.join(parts) <span class="cm"># O(n) total — not O(n²) like +=</span></pre>
</div>
<!-- ═══════════════════════════════ COLLECTIONS ═══════════════════════════════ -->
<div class="card c5" data-tags="collections deque counter defaultdict ordereddict namedtuple appendleft popleft rotate most_common">
<div class="card-header">
<div class="dot"></div>
<h2>Collections Module</h2>
<span class="type-badge">deque · Counter · defaultdict · namedtuple</span>
</div>
<pre>
<span class="kw">from</span> collections <span class="kw">import</span> deque, Counter, defaultdict, namedtuple, OrderedDict
<span class="cm"># ── deque — double-ended queue ───────────────────</span>
<span class="cm"># O(1) on BOTH ends. list.pop(0) is O(n) — always prefer deque for queues</span>
d = deque()
d = deque([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>])
d = deque(maxlen=<span class="nm">3</span>) <span class="cm"># circular buffer — auto-evicts oldest</span>
d.append(x) <span class="cm"># push right — O(1)</span>
d.appendleft(x) <span class="cm"># push left — O(1)</span>
d.pop() <span class="cm"># pop right — O(1)</span>
d.popleft() <span class="cm"># pop left — O(1) ← use for BFS!</span>
d.extend([<span class="nm">4</span>,<span class="nm">5</span>]) <span class="cm"># extend right</span>
d.extendleft([<span class="nm">0</span>,-<span class="nm">1</span>]) <span class="cm"># extend left (note: reverses order)</span>
d.rotate(<span class="nm">1</span>) <span class="cm"># rotate right by 1 (last→first)</span>
d.rotate(-<span class="nm">1</span>) <span class="cm"># rotate left by 1</span>
d[<span class="nm">0</span>], d[-<span class="nm">1</span>] <span class="cm"># peek without removing — O(1)</span>
<span class="bi">len</span>(d) <span class="cm"># O(1)</span>
<span class="cm"># Use as STACK: append + pop</span>
<span class="cm"># Use as QUEUE: append + popleft</span>
<span class="cm"># ── Counter ─────────────────────────────────────</span>
c = Counter(<span class="st">"aabbccc"</span>) <span class="cm"># Counter({'c':3,'a':2,'b':2})</span>
c = Counter([<span class="nm">1</span>,<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>])
c = Counter({<span class="st">'a'</span>:<span class="nm">3</span>, <span class="st">'b'</span>:<span class="nm">1</span>})
c[<span class="st">'x'</span>] <span class="cm"># 0 (not KeyError!) for missing keys</span>
c.most_common(<span class="nm">2</span>) <span class="cm"># [('c',3),('a',2)] — top 2</span>
c.most_common()[:-<span class="nm">3</span>:-<span class="nm">1</span>] <span class="cm"># least common 2</span>
<span class="bi">list</span>(c.elements()) <span class="cm"># reconstruct with repetitions</span>
c.total() <span class="cm"># sum of all counts (Python 3.10+)</span>
<span class="cm"># Counter arithmetic (very useful!):</span>
Counter(<span class="st">"aab"</span>) + Counter(<span class="st">"abb"</span>) <span class="cm"># add counts</span>
Counter(<span class="st">"aab"</span>) - Counter(<span class="st">"ab"</span>) <span class="cm"># subtract, floor 0</span>
Counter(<span class="st">"aab"</span>) & Counter(<span class="st">"abb"</span>) <span class="cm"># min of each count</span>
Counter(<span class="st">"aab"</span>) | Counter(<span class="st">"abb"</span>) <span class="cm"># max of each count</span>
<span class="cm"># ── defaultdict ─────────────────────────────────</span>
dd = defaultdict(<span class="bi">list</span>) <span class="cm"># missing key → []</span>
dd = defaultdict(<span class="bi">int</span>) <span class="cm"># missing key → 0</span>
dd = defaultdict(<span class="bi">set</span>) <span class="cm"># missing key → set()</span>
dd = defaultdict(<span class="kw">lambda</span>: [<span class="nm">0</span>]*<span class="nm">26</span>) <span class="cm"># missing key → custom</span>
<span class="cm"># ── namedtuple ──────────────────────────────────</span>
Point = namedtuple(<span class="st">'Point'</span>, [<span class="st">'x'</span>, <span class="st">'y'</span>])
p = Point(<span class="nm">3</span>, <span class="nm">4</span>)
p.x, p.y <span class="cm"># named access AND index access</span>
p[<span class="nm">0</span>], p[<span class="nm">1</span>] <span class="cm"># still a tuple underneath</span></pre>
</div>
<!-- ═══════════════════════════════ HEAP ═══════════════════════════════════════ -->
<div class="card c6" data-tags="heap heapq push pop heapify nlargest nsmallest priority queue min max">
<div class="card-header">
<div class="dot"></div>
<h2>Heap (heapq)</h2>
<span class="type-badge">min-heap · O(log n) push/pop · O(1) peek</span>
</div>
<pre>
<span class="kw">import</span> heapq
<span class="cm"># Python ONLY has min-heap. Negate values for max-heap.</span>
<span class="cm"># Heap = list; heapq mutates it in place.</span>
<span class="cm"># ── Build ────────────────────────────────────────</span>
h = []
heapq.heappush(h, <span class="nm">3</span>) <span class="cm"># O(log n)</span>
heapq.heapify(lst) <span class="cm"># convert list in-place — O(n)!</span>
<span class="cm"># ── Access ───────────────────────────────────────</span>
h[<span class="nm">0</span>] <span class="cm"># peek minimum — O(1)</span>
heapq.heappop(h) <span class="cm"># pop minimum — O(log n)</span>
heapq.heapreplace(h, val) <span class="cm"># pop min + push val — 1 op, faster</span>
heapq.heappushpop(h, val) <span class="cm"># push val then pop min — 1 op</span>
<span class="cm"># ── Convenience ─────────────────────────────────</span>
heapq.nlargest(<span class="nm">3</span>, lst) <span class="cm"># O(n log k) — better than sort for small k</span>
heapq.nsmallest(<span class="nm">3</span>, lst) <span class="cm"># O(n log k)</span>
heapq.nlargest(<span class="nm">3</span>, lst, key=<span class="kw">lambda</span> x: x[<span class="nm">1</span>]) <span class="cm"># with key function</span>
<span class="cm"># ── Max-heap trick ───────────────────────────────</span>
heapq.heappush(h, -val) <span class="cm"># negate on push</span>
-heapq.heappop(h) <span class="cm"># negate on pop</span>
<span class="cm"># ── Tuple heaps (priority queues) ───────────────</span>
<span class="cm"># Tuples compared element-by-element; first element = priority</span>
heapq.heappush(h, (priority, value))
heapq.heappush(h, (<span class="nm">0</span>, <span class="st">'urgent'</span>))
heapq.heappush(h, (<span class="nm">5</span>, <span class="st">'low'</span>))
heapq.heappop(h) <span class="cm"># (0, 'urgent') — lowest priority first</span>
<span class="cm"># Tie-breaking: add a counter to avoid comparing values</span>
<span class="kw">import</span> itertools
counter = itertools.count()
heapq.heappush(h, (priority, <span class="bi">next</span>(counter), value))
<span class="cm"># ── K-th largest (keep a min-heap of size k) ────</span>
<span class="kw">def</span> kth_largest(nums, k):
h = nums[:k]
heapq.heapify(h) <span class="cm"># O(k)</span>
<span class="kw">for</span> n <span class="kw">in</span> nums[k:]:
<span class="kw">if</span> n > h[<span class="nm">0</span>]:
heapq.heapreplace(h, n) <span class="cm"># evict smallest, add n</span>
<span class="kw">return</span> h[<span class="nm">0</span>] <span class="cm"># smallest of the k largest</span></pre>
</div>
<!-- ═══════════════════════════════ BUILTINS ══════════════════════════════════ -->
<div class="card c6" data-tags="enumerate zip map filter any all sum min max sorted reversed abs divmod pow range len">
<div class="card-header">
<div class="dot"></div>
<h2>Built-in Functions</h2>
<span class="type-badge">enumerate · zip · map · filter · reduce</span>
</div>
<pre>
<span class="cm"># ── enumerate — index + value together ──────────</span>
<span class="kw">for</span> i, val <span class="kw">in</span> <span class="bi">enumerate</span>(arr): <span class="cm"># 0-indexed</span>
<span class="kw">pass</span>
<span class="kw">for</span> i, val <span class="kw">in</span> <span class="bi">enumerate</span>(arr, <span class="nm">1</span>): <span class="cm"># 1-indexed</span>
<span class="kw">pass</span>
d = <span class="bi">dict</span>(<span class="bi">enumerate</span>(arr)) <span class="cm"># {0:a, 1:b, 2:c, ...}</span>
<span class="cm"># ── zip — pair up iterables ─────────────────────</span>
<span class="kw">for</span> a, b <span class="kw">in</span> <span class="bi">zip</span>(list1, list2): <span class="cm"># stops at shortest</span>
<span class="kw">pass</span>
<span class="kw">for</span> a, b <span class="kw">in</span> <span class="bi">zip</span>(s, s[<span class="nm">1</span>:]): <span class="cm"># sliding window pairs</span>
<span class="kw">pass</span>
<span class="bi">list</span>(<span class="bi">zip</span>(*matrix)) <span class="cm"># transpose 2D matrix</span>
<span class="bi">dict</span>(<span class="bi">zip</span>(keys, values)) <span class="cm"># build dict from two lists</span>
<span class="cm"># zip_longest fills shorter with a fill value</span>
<span class="kw">from</span> itertools <span class="kw">import</span> zip_longest
<span class="kw">for</span> a, b <span class="kw">in</span> zip_longest(l1, l2, fillvalue=<span class="nm">0</span>):
<span class="kw">pass</span>
<span class="cm"># ── map and filter ───────────────────────────────</span>
<span class="bi">list</span>(<span class="bi">map</span>(<span class="bi">int</span>, [<span class="st">'1'</span>,<span class="st">'2'</span>,<span class="st">'3'</span>])) <span class="cm"># convert types</span>
<span class="bi">list</span>(<span class="bi">map</span>(<span class="kw">lambda</span> x: x*<span class="nm">2</span>, arr)) <span class="cm"># apply fn to each</span>
<span class="bi">list</span>(<span class="bi">filter</span>(<span class="kw">lambda</span> x: x><span class="nm">0</span>, arr)) <span class="cm"># keep truthy results</span>
<span class="cm"># Prefer list comprehensions — more readable:</span>
[x*<span class="nm">2</span> <span class="kw">for</span> x <span class="kw">in</span> arr] <span class="cm"># equivalent to map</span>
[x <span class="kw">for</span> x <span class="kw">in</span> arr <span class="kw">if</span> x > <span class="nm">0</span>] <span class="cm"># equivalent to filter</span>
<span class="cm"># ── any / all — short-circuit evaluation ────────</span>
<span class="bi">any</span>(x > <span class="nm">0</span> <span class="kw">for</span> x <span class="kw">in</span> arr) <span class="cm"># True if ANY element > 0</span>
<span class="bi">all</span>(x > <span class="nm">0</span> <span class="kw">for</span> x <span class="kw">in</span> arr) <span class="cm"># True if ALL elements > 0</span>
<span class="bi">any</span>(c.isdigit() <span class="kw">for</span> c <span class="kw">in</span> s) <span class="cm"># string contains a digit?</span>
<span class="cm"># ── Numeric builtins ─────────────────────────────</span>
<span class="bi">abs</span>(-<span class="nm">5</span>) <span class="cm"># 5</span>
<span class="bi">pow</span>(<span class="nm">2</span>, <span class="nm">10</span>) <span class="cm"># 1024</span>
<span class="bi">pow</span>(<span class="nm">2</span>, <span class="nm">10</span>, <span class="nm">1000</span>) <span class="cm"># 2^10 mod 1000 — O(log n)!</span>
<span class="bi">divmod</span>(<span class="nm">17</span>, <span class="nm">5</span>) <span class="cm"># (3, 2) — quotient and remainder</span>
<span class="bi">round</span>(<span class="nm">3.14159</span>, <span class="nm">2</span>) <span class="cm"># 3.14</span>
<span class="cm"># ── min / max with key ───────────────────────────</span>
<span class="bi">min</span>(arr)
<span class="bi">max</span>(arr)
<span class="bi">min</span>(arr, key=<span class="kw">lambda</span> x: x[<span class="nm">1</span>]) <span class="cm"># min by second element</span>
<span class="bi">max</span>(d, key=d.get) <span class="cm"># key with highest dict value</span>
<span class="bi">min</span>(<span class="nm">3</span>, <span class="nm">7</span>, <span class="nm">2</span>) <span class="cm"># works on multiple args too</span>
<span class="cm"># ── Infinity as sentinel ─────────────────────────</span>
<span class="bi">float</span>(<span class="st">'inf'</span>) <span class="cm"># larger than any number</span>
<span class="bi">float</span>(<span class="st">'-inf'</span>) <span class="cm"># smaller than any number</span>
<span class="cm"># ── Type conversion ──────────────────────────────</span>
<span class="bi">int</span>(<span class="st">'42'</span>), <span class="bi">str</span>(<span class="nm">42</span>), <span class="bi">float</span>(<span class="st">'3.14'</span>)
<span class="bi">bin</span>(<span class="nm">10</span>), <span class="bi">hex</span>(<span class="nm">255</span>), <span class="bi">oct</span>(<span class="nm">8</span>) <span class="cm"># '0b1010', '0xff', '0o10'</span>
<span class="bi">int</span>(<span class="st">'1010'</span>, <span class="nm">2</span>) <span class="cm"># binary string → int: 10</span></pre>
</div>
<!-- ═══════════════════════════════ ITERTOOLS ═════════════════════════════════ -->
<div class="card c7" data-tags="itertools product permutations combinations accumulate groupby chain cycle islice">
<div class="card-header">
<div class="dot"></div>
<h2>Itertools & Sorting Recipes</h2>
<span class="type-badge">lazy iterators · combinatorics</span>
</div>
<pre>
<span class="kw">from</span> itertools <span class="kw">import</span> (
product, permutations, combinations, combinations_with_replacement,
accumulate, groupby, chain, cycle, islice, repeat
)
<span class="cm"># ── Combinatorics ────────────────────────────────</span>
<span class="bi">list</span>(permutations([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>])) <span class="cm"># all 6 orderings (tuples)</span>
<span class="bi">list</span>(permutations(<span class="st">'ABC'</span>, <span class="nm">2</span>)) <span class="cm"># 2-length permutations</span>
<span class="bi">list</span>(combinations([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>], <span class="nm">2</span>)) <span class="cm"># [(1,2),(1,3),(2,3)] no repeats</span>
<span class="bi">list</span>(combinations_with_replacement(<span class="st">'AB'</span>, <span class="nm">2</span>)) <span class="cm"># [AA, AB, BB]</span>
<span class="bi">list</span>(product([<span class="nm">0</span>,<span class="nm">1</span>], repeat=<span class="nm">3</span>)) <span class="cm"># all 3-bit strings (8 tuples)</span>
<span class="bi">list</span>(product(<span class="st">'AB'</span>, <span class="st">'xy'</span>)) <span class="cm"># cartesian product: Ax Ay Bx By</span>
<span class="cm"># ── accumulate — running computation ────────────</span>
<span class="bi">list</span>(accumulate([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>,<span class="nm">4</span>])) <span class="cm"># [1,3,6,10] prefix sums</span>
<span class="bi">list</span>(accumulate([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>], <span class="bi">max</span>)) <span class="cm"># [1,2,3] running max</span>
<span class="bi">list</span>(accumulate([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>], <span class="kw">lambda</span> a,b: a*b)) <span class="cm"># [1,2,6] running product</span>
<span class="cm"># ── chain — flatten one level ────────────────────</span>
<span class="bi">list</span>(chain([<span class="nm">1</span>,<span class="nm">2</span>], [<span class="nm">3</span>,<span class="nm">4</span>], [<span class="nm">5</span>])) <span class="cm"># [1,2,3,4,5]</span>
<span class="bi">list</span>(chain.from_iterable([[<span class="nm">1</span>,<span class="nm">2</span>],[<span class="nm">3</span>,<span class="nm">4</span>]])) <span class="cm"># flatten nested</span>
<span class="cm"># ── cycle & repeat ──────────────────────────────</span>
<span class="bi">list</span>(islice(cycle([<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>]), <span class="nm">7</span>)) <span class="cm"># [1,2,3,1,2,3,1]</span>
<span class="bi">list</span>(repeat(<span class="nm">0</span>, <span class="nm">5</span>)) <span class="cm"># [0,0,0,0,0] — lazy [0]*5</span>
<span class="cm"># ── Sorting patterns ─────────────────────────────</span>
<span class="cm"># Multi-key sort</span>
arr.sort(key=<span class="kw">lambda</span> x: (x[<span class="nm">1</span>], -x[<span class="nm">0</span>])) <span class="cm"># by [1] asc, [0] desc</span>
<span class="bi">sorted</span>(words, key=<span class="kw">lambda</span> w: (w.lower(), w)) <span class="cm"># case-insensitive</span>
<span class="bi">sorted</span>(words, key=<span class="bi">len</span>) <span class="cm"># by length</span>
<span class="bi">sorted</span>(words, key=<span class="kw">lambda</span> s: s[::-<span class="nm">1</span>]) <span class="cm"># by reversed string</span>
<span class="cm"># bisect — binary search on sorted list</span>
<span class="kw">import</span> bisect
bisect.bisect_left(nums, x) <span class="cm"># leftmost position x could insert</span>
bisect.bisect_right(nums, x) <span class="cm"># rightmost position x could insert</span>
bisect.insort(nums, x) <span class="cm"># insert x maintaining sort order</span>
<span class="cm"># bisect_left = first index where nums[i] >= x (lower bound)</span>
<span class="cm"># bisect_right = first index where nums[i] > x (upper bound)</span>
<span class="cm"># functools.reduce</span>
<span class="kw">from</span> functools <span class="kw">import</span> reduce
reduce(<span class="kw">lambda</span> a,b: a*b, [<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>,<span class="nm">4</span>]) <span class="cm"># 24 — running accumulation</span>
<span class="cm"># functools.lru_cache — memoization decorator</span>
<span class="kw">from</span> functools <span class="kw">import</span> lru_cache
<span class="kw">@</span>lru_cache(maxsize=<span class="kw">None</span>)
<span class="kw">def</span> fib(n):
<span class="kw">if</span> n <= <span class="nm">1</span>: <span class="kw">return</span> n
<span class="kw">return</span> fib(n-<span class="nm">1</span>) + fib(n-<span class="nm">2</span>) <span class="cm"># now O(n), was O(2^n)</span></pre>
</div>
<!-- ═══════════════════════════════ TUPLE & MISC ══════════════════════════════ -->
<div class="card c1" data-tags="tuple unpacking swap range slice assignment star walrus operator">
<div class="card-header">
<div class="dot"></div>
<h2>Pythonic Idioms & Tricks</h2>
<span class="type-badge">tuple · unpacking · walrus · assignment</span>
</div>
<pre>
<span class="cm"># ── Tuple ────────────────────────────────────────</span>
<span class="cm"># Immutable, hashable, can be dict key/set member</span>
t = (<span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">3</span>)
t = <span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">3</span> <span class="cm"># parentheses optional</span>
t = (<span class="nm">1</span>,) <span class="cm"># singleton — trailing comma required!</span>
t.count(x), t.index(x) <span class="cm"># only two methods — immutable!</span>
<span class="cm"># ── Unpacking ────────────────────────────────────</span>
a, b = b, a <span class="cm"># swap — no temp variable needed</span>
a, b, c = [<span class="nm">1</span>, <span class="nm">2</span>, <span class="nm">3</span>]
first, *rest = [<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>,<span class="nm">4</span>] <span class="cm"># first=1, rest=[2,3,4]</span>
*init, last = [<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>,<span class="nm">4</span>] <span class="cm"># init=[1,2,3], last=4</span>
a, *_, z = [<span class="nm">1</span>,<span class="nm">2</span>,<span class="nm">3</span>,<span class="nm">4</span>,<span class="nm">5</span>] <span class="cm"># a=1, z=5, middle discarded</span>
(a, b), c = (<span class="nm">1</span>, <span class="nm">2</span>), <span class="nm">3</span> <span class="cm"># nested unpacking</span>
<span class="cm"># ── Walrus operator := (Python 3.8+) ────────────</span>
<span class="cm"># Assign AND use in same expression</span>
<span class="kw">while</span> chunk := f.read(<span class="nm">8192</span>): <span class="cm"># read until empty</span>
process(chunk)
<span class="kw">if</span> (n := <span class="bi">len</span>(a)) > <span class="nm">10</span>: <span class="cm"># avoid computing len twice</span>
<span class="bi">print</span>(f<span class="st">"list is {n} items"</span>)
<span class="cm"># ── Conditional expression (ternary) ────────────</span>
val = x <span class="kw">if</span> condition <span class="kw">else</span> y
result = a <span class="kw">or</span> b <span class="cm"># b if a is falsy — common default pattern</span>
result = a <span class="kw">and</span> b <span class="cm"># b if a is truthy</span>
<span class="cm"># ── Falsy values to memorize ─────────────────────</span>
<span class="cm"># False, None, 0, 0.0, '', [], {}, set(), ()</span>
<span class="kw">if not</span> arr: <span class="kw">pass</span> <span class="cm"># empty list check — Pythonic</span>
<span class="cm"># ── is vs == ─────────────────────────────────────</span>
a == b <span class="cm"># value equality</span>
a <span class="kw">is</span> b <span class="cm"># identity (same object in memory)</span>
x <span class="kw">is None</span> <span class="cm"># ALWAYS use 'is' for None, True, False</span>
slow.next <span class="kw">is</span> fast.next <span class="cm"># linked list cycle check — must use 'is'</span>
<span class="cm"># ── range tricks ─────────────────────────────────</span>
<span class="bi">range</span>(<span class="nm">5</span>) <span class="cm"># 0,1,2,3,4</span>
<span class="bi">range</span>(<span class="nm">1</span>, <span class="nm">6</span>) <span class="cm"># 1,2,3,4,5</span>
<span class="bi">range</span>(<span class="nm">10</span>, <span class="nm">0</span>, -<span class="nm">1</span>) <span class="cm"># 10,9,...,1</span>
<span class="bi">range</span>(<span class="nm">0</span>, <span class="nm">10</span>, <span class="nm">2</span>) <span class="cm"># 0,2,4,6,8</span>
<span class="bi">list</span>(<span class="bi">reversed</span>(<span class="bi">range</span>(<span class="nm">5</span>))) <span class="cm"># [4,3,2,1,0]</span>
<span class="cm"># ── Comprehension patterns ───────────────────────</span>
{k: <span class="bi">len</span>(v) <span class="kw">for</span> k, v <span class="kw">in</span> d.items()} <span class="cm"># transform dict</span>
{v: k <span class="kw">for</span> k, v <span class="kw">in</span> d.items()} <span class="cm"># invert dict (assumes unique vals)</span>
[x <span class="kw">for</span> row <span class="kw">in</span> grid <span class="kw">for</span> x <span class="kw">in</span> row] <span class="cm"># flatten 2D</span>
[[row[i] <span class="kw">for</span> row <span class="kw">in</span> grid] <span class="kw">for</span> i <span class="kw">in</span> <span class="bi">range</span>(<span class="bi">len</span>(grid[<span class="nm">0</span>]))] <span class="cm"># transpose</span></pre>
</div>
<!-- ═══════════════════════════════ COMPLEXITY ════════════════════════════════ -->
<div class="card c2" data-tags="complexity big O time space list dict set string operations">
<div class="card-header">
<div class="dot"></div>
<h2>Complexity Quick-Reference</h2>
<span class="type-badge">time · space · when to use what</span>
</div>
<pre>
<span class="cm"># ── LIST ─────────────────────────────────────────</span>
<span class="cm"># append/pop right: O(1) amortized</span>
<span class="cm"># insert/pop left: O(n) — use deque!</span>
<span class="cm"># index access: O(1)</span>
<span class="cm"># search (in): O(n)</span>
<span class="cm"># sort: O(n log n)</span>
<span class="cm"># slice: O(k) where k = slice length</span>
<span class="cm"># ── DICT / SET ───────────────────────────────────</span>
<span class="cm"># get/set/delete: O(1) average</span>
<span class="cm"># membership (in): O(1) average ← this is why you use them</span>
<span class="cm"># iteration: O(n)</span>
<span class="cm"># set operations &|−: O(min(a,b)) or O(len(a)+len(b))</span>
<span class="cm"># ── STRING ───────────────────────────────────────</span>
<span class="cm"># index/slice: O(k)</span>
<span class="cm"># concatenation s+t: O(n+m) — creates new string</span>
<span class="cm"># join: O(n) total — always prefer join</span>
<span class="cm"># find/count/in: O(n) substring search</span>
<span class="cm"># split: O(n)</span>
<span class="cm"># ── DEQUE ────────────────────────────────────────</span>
<span class="cm"># append/pop both ends: O(1)</span>
<span class="cm"># index access [i]: O(n) — not like list!</span>
<span class="cm"># ── HEAP ─────────────────────────────────────────</span>
<span class="cm"># heappush/heappop: O(log n)</span>
<span class="cm"># heapify: O(n) ← not O(n log n)!</span>
<span class="cm"># peek (h[0]): O(1)</span>
<span class="cm"># nlargest/nsmallest: O(n log k)</span>
<span class="cm"># ── DECISION GUIDE ───────────────────────────────</span>
<span class="cm"># Need O(1) membership? → set</span>
<span class="cm"># Need O(1) key→value lookup? → dict</span>
<span class="cm"># Need O(1) on both ends? → deque</span>
<span class="cm"># Need min/max efficiently? → heap</span>
<span class="cm"># Need sorted order? → sort + bisect</span>
<span class="cm"># Need to count frequencies? → Counter</span>
<span class="cm"># Need graph adjacency? → defaultdict(list)</span>
<span class="cm"># Need hashable collection? → tuple or frozenset</span>
<span class="cm"># ── n² → n transformations ───────────────────────</span>
<span class="cm"># Two nested loops checking pairs → hash the complement</span>
<span class="cm"># Sorted array + two conditions → two pointers</span>
<span class="cm"># "Next greater element" → monotonic stack</span>
<span class="cm"># Subarray sum = k → prefix sum + hash</span>
<span class="cm"># "Is X reachable?" → BFS / DFS + visited set</span>
<span class="cm"># Repeated subproblem computation → memoize with @lru_cache</span></pre>
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