Catalog Products with Isolated Three-Digit Blocks

Easy

A merchandising analytics team is validating product naming conventions before a catalog release. Table: Products product_id: unique product identifier name: product display name A product is considered a match if its name contains at least one isolated block of exactly three digits. A three-digit block is isolated when: It has exactly three consecutive characters in [0-9]. The character immediately before the block (if it exists) is not a digit. The character immediately after the block (if it exists) is not a digit. Examples: "AXE123PRO" is a match (contains isolated block "123"). "Pack1234" is not a match (the digit run has length 4, not exactly 3). "003" is a match (length-3 run at full-string boundaries). Task: Return every row from Products that matches this rule. Output requirements: Return columns in this exact order: product_id name Sort by product_id in ascending order. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

Products:
| product_id | name              |
|------------|-------------------|
| 1          | AXE123PRO         |
| 2          | A12B34C           |
| 3          | Mega56789Pack     |
| 4          | 789Starter        |
| 5          | Item003Label      |
| 6          | NoDigitsHere      |

Output

[
  {"product_id":1,"name":"AXE123PRO"},
  {"product_id":4,"name":"789Starter"},
  {"product_id":5,"name":"Item003Label"}
]

Explanation

Rows 1, 4, and 5 each contain at least one isolated 3-digit block. Rows 2 and 6 have no 3-digit run, and row 3 has a 5-digit run.

Example 2

Input

Products:
| product_id | name           |
|------------|----------------|
| 10         | X123Y456Z      |
| 11         | X1234Y         |
| 12         | AB001-CD       |
| 13         | 99123A         |
| 14         | A1B2C3         |

Output

[
  {"product_id":10,"name":"X123Y456Z"},
  {"product_id":12,"name":"AB001-CD"}
]

Explanation

Rows 10 and 12 have isolated 3-digit runs. Rows 11 and 13 contain longer digit runs, and row 14 never reaches three consecutive digits.

Example 3

Input

Products:
| product_id | name      |
|------------|-----------|
| 21         | 123       |
| 22         | 1234      |
| 23         | A000B     |
| 24         | A0000B    |
| 25         | AB12      |

Output

[
  {"product_id":21,"name":"123"},
  {"product_id":23,"name":"A000B"}
]

Explanation

Full-string boundaries still count as isolated boundaries. Any 4-digit run is rejected.

Constraints

1 <= number of rows in Products <= 200000
product_id is unique within a test case
1 <= product_id <= 1000000000
name is a non-null text value
1 <= LENGTH(name) <= 120
Digit checks are ASCII-based ([0-9])
A matching run must be exactly length 3 with non-digit boundaries (or string boundaries)
Output columns must be exactly: product_id, name
Final order must be product_id ASC
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with columns [product_id, name]

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Catalog Products with Isolated Three-Digit Blocks

Easy

A merchandising analytics team is validating product naming conventions before a catalog release. Table: Products product_id: unique product identifier name: product display name A product is considered a match if its name contains at least one isolated block of exactly three digits. A three-digit block is isolated when: It has exactly three consecutive characters in [0-9]. The character immediately before the block (if it exists) is not a digit. The character immediately after the block (if it exists) is not a digit. Examples: "AXE123PRO" is a match (contains isolated block "123"). "Pack1234" is not a match (the digit run has length 4, not exactly 3). "003" is a match (length-3 run at full-string boundaries). Task: Return every row from Products that matches this rule. Output requirements: Return columns in this exact order: product_id name Sort by product_id in ascending order. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

Products:
| product_id | name              |
|------------|-------------------|
| 1          | AXE123PRO         |
| 2          | A12B34C           |
| 3          | Mega56789Pack     |
| 4          | 789Starter        |
| 5          | Item003Label      |
| 6          | NoDigitsHere      |

Output

[
  {"product_id":1,"name":"AXE123PRO"},
  {"product_id":4,"name":"789Starter"},
  {"product_id":5,"name":"Item003Label"}
]

Explanation

Rows 1, 4, and 5 each contain at least one isolated 3-digit block. Rows 2 and 6 have no 3-digit run, and row 3 has a 5-digit run.

Example 2

Input

Products:
| product_id | name           |
|------------|----------------|
| 10         | X123Y456Z      |
| 11         | X1234Y         |
| 12         | AB001-CD       |
| 13         | 99123A         |
| 14         | A1B2C3         |

Output

[
  {"product_id":10,"name":"X123Y456Z"},
  {"product_id":12,"name":"AB001-CD"}
]

Explanation

Rows 10 and 12 have isolated 3-digit runs. Rows 11 and 13 contain longer digit runs, and row 14 never reaches three consecutive digits.

Example 3

Input

Products:
| product_id | name      |
|------------|-----------|
| 21         | 123       |
| 22         | 1234      |
| 23         | A000B     |
| 24         | A0000B    |
| 25         | AB12      |

Output

[
  {"product_id":21,"name":"123"},
  {"product_id":23,"name":"A000B"}
]

Explanation

Full-string boundaries still count as isolated boundaries. Any 4-digit run is rejected.

Constraints

1 <= number of rows in Products <= 200000
product_id is unique within a test case
1 <= product_id <= 1000000000
name is a non-null text value
1 <= LENGTH(name) <= 120
Digit checks are ASCII-based ([0-9])
A matching run must be exactly length 3 with non-digit boundaries (or string boundaries)
Output columns must be exactly: product_id, name
Final order must be product_id ASC
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with columns [product_id, name]