300 Real Time SQL Interview.pdf
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300 Real Time SQL Interview practical Questions Asked at multiple companies
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Anyone who's preparing for an interview just reading theoretical concept will not help definitely you need to have practical hands on in #sql so create table with some data and try this queries running by your self so can help you to understand the logic of similar kind of queries
If you're preparing for an interview this doc will help a lot in the perpetration If you're experienced also freshers can also get hands on by practicing these queries and get confidence.
••••••••••••••••••••••••••••••••••••••••••••••••••••••
Anyone who's preparing for an interview just reading theoretical concept will not help definitely you need to have practical hands on in #sql so create table with some data and try this queries running by your self so can help you to understand the logic of similar kind of queries
If you're preparing for an interview this doc will help a lot in the perpetration If you're experienced also freshers can also get hands on by practicing these queries and get confidence.
https://t.iss.one/DataScienceQ
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What do you know about NoSQL databases?
Answer:
These databases scale well horizontally: data is distributed across cluster nodes, which helps handle high loads and large volumes. Different storage models are supported — key-value, document, columnar, and graph. This allows choosing the appropriate structure for a specific task.
Common systems include MongoDB (documents), Cassandra (columns), Redis (key-value), and Neo4j (graphs). They are used where scalability, speed, and data flexibility are important.
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What does it mean that a QuerySet in Django is "lazy"?
Answer:
The actual database access happens only when the results are really needed: when iterating over the QuerySet, calling list(), count(), first(), exists(), and other methods that require data.
This approach helps avoid unnecessary database hits and improves performance — queries are executed only at the moment of real necessity.
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Forwarded from Machine Learning with Python
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Can you turn $100 into $5,000 in just 7 days?
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What is the difference between calling
start() and run() on threading.Thread?Answer:
If you call run() directly, it will execute in the current thread like a normal function — without creating a new thread and without parallelism.
This is the key difference: start() launches a separate execution thread, while run() just runs the code in the same thread.
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What does
nonlocal do and where can it be used?Answer:
This is often used in closures to maintain and update state between calls to the nested function.
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🐍 Tricky Python Interview Question
> What will this code output and why?
❓Question: Why are list1 and list3 the same?
🔍 Explanation:
Default arguments in Python are evaluated once — at function definition, not at each call.
So lst=[] is created once and preserved between calls if you don't explicitly pass your own list.
🧠 What happens:
- extend_list(10) → uses the shared list [], now it is [10]
- extend_list(123, []) → creates a new list [123]
- extend_list('a') → again uses the shared list → [10, 'a']
👉 Result:
✅ How to fix:
If you want a new list created by default on each call, do this:
This is a classic Python interview trap — mutable default arguments.
It tests if you understand how default values and memory scope work.
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> What will this code output and why?
def extend_list(val, lst=[]):
lst.append(val)
return lst
list1 = extend_list(10)
list2 = extend_list(123, [])
list3 = extend_list('a')
print(list1, list2, list3)
❓Question: Why are list1 and list3 the same?
🔍 Explanation:
Default arguments in Python are evaluated once — at function definition, not at each call.
So lst=[] is created once and preserved between calls if you don't explicitly pass your own list.
🧠 What happens:
- extend_list(10) → uses the shared list [], now it is [10]
- extend_list(123, []) → creates a new list [123]
- extend_list('a') → again uses the shared list → [10, 'a']
👉 Result:
[10, 'a'] [123] [10, 'a']✅ How to fix:
If you want a new list created by default on each call, do this:
def extend_list(val, lst=None):
if lst is None:
lst = []
lst.append(val)
return lst
This is a classic Python interview trap — mutable default arguments.
It tests if you understand how default values and memory scope work.
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⛓️ Tricky Python Interview Question
> What will this code output and why?
❓ Question: Why does this code print 2, 2, 2 instead of 0, 1, 2?
🔍 Explanation:
This is a classic example of late binding in Python closures. The lambda functions don't capture the value of
🧠 What happens:
• The
• The
• When you call each function
👉 Result:
2
2
2
✅ How to fix:
You can force the lambda to capture the value of
This trick works because default arguments are evaluated when the function is defined, not when it's called. This will correctly print:
0
1
2
This is a common interview question that tests your understanding of closures, scope, and late binding in Python.
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By: @DataScienceQ ✨
> What will this code output and why?
funcs = []
for i in range(3):
funcs.append(lambda: print(i))
for f in funcs:
f()
❓ Question: Why does this code print 2, 2, 2 instead of 0, 1, 2?
🔍 Explanation:
This is a classic example of late binding in Python closures. The lambda functions don't capture the value of
i at each step of the loop. Instead, they all hold a reference to the same variable i.🧠 What happens:
• The
for loop completes. By the end of the loop, the variable i holds the value 2.• The
funcs list contains three functions, but each one is defined to print the value of whatever i is at the time of execution.• When you call each function
f(), it looks up the current value of i in its enclosing scope, which is 2.👉 Result:
2
2
2
✅ How to fix:
You can force the lambda to capture the value of
i at the time of definition by using a default argument.funcs = []
for i in range(3):
# The default argument captures i's value at definition time
funcs.append(lambda num=i: print(num))
for f in funcs:
f()
This trick works because default arguments are evaluated when the function is defined, not when it's called. This will correctly print:
0
1
2
This is a common interview question that tests your understanding of closures, scope, and late binding in Python.
━━━━━━━━━━━━━━━
By: @DataScienceQ ✨
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