Effective Environment After Layered ENV Instructions

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Problem Statement

A Dockerfile sets environment variables across several ENV instructions; later ones override earlier keys. Compute the final environment.

Background

Each ENV instruction contributes one or more KEY=VALUE pairs. Applied top to bottom, a later assignment to the same key replaces the earlier value. The result is the merged mapping.

Your Task

def resolve_env(env_layers):

env_layers: list of dicts, each a set of KEY: VALUE from one ENV line, in order.
Return the final merged dict.

Input Format

env_layers (list of dicts).

Output Format

A dict.

Sample

print(resolve_env([{"A": "1", "B": "2"}, {"B": "9"}]))

Output:

{'A': '1', 'B': '9'}

Example

Input

print(resolve_env([{"A": "1", "B": "2"}, {"B": "9"}]))

Output

{'A': '1', 'B': '9'}

Reasoning

Start with an empty environment mapping to accumulate the final state.
Process the first layer $\{A: 1, B: 2\}$ by merging its key-value pairs into the current mapping, resulting in $\{A: 1, B: 2\}$ .
Process the second layer $\{B: 9\}$ by updating the existing mapping; since key $B$ already exists, its value is overridden from $2$ to $9$ , while key $A$ remains unchanged.
The merged mapping after all layers is applied is $\{A: 1, B: 9\}$ .
The final output is {'A': '1', 'B': '9'}

Constraints

Apply layers in order; later keys overwrite earlier ones.
Keys absent in later layers keep their earlier value.
Return the merged dict.

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Concept primerPREVIEW

1. Background Knowledge

In containerized workflows, a Dockerfile defines how an image is built. One of the most common instructions is ENV, which sets environment variables that persist for all subsequent instructions and for the running container. Because a Dockerfile is processed top to bottom, each ENV line is applied sequentially. If a later ENV line assigns a value to a key that was already set by an earlier line, the later value overrides the earlier one. This behavior mirrors how shell variable assignment works: the last assignment wins.

The problem models this by representing each ENV instruction as a dictionary of KEY: VALUE pairs. The list of dictionaries preserves the order in which the instructions appear in the Dockerfile. Your job is to simulate the sequential application of these assignments and produce the final merged mapping. This is a straightforward state accumulation problem: you start with an empty state and update it as you process each layer.

Understanding this concept is foundational for debugging container builds, where unexpected environment values often stem from an earlier ENV being overridden (or not) by a later one. It also connects to broader ideas in configuration management, where layered configuration files are merged with a defined precedence order.

2. Algorithm Approach

The core pattern here is sequential merge with last-write-wins semantics. You iterate through the list of dictionaries in order, and for each dictionary, you update a single accumulator dictionary. Because Python dictionaries support direct key assignment (d[key] = value), updating an existing key automatically replaces its value, which is exactly the override behavior you need.

This is not a complex algorithm; it is a single pass with constant-time updates per key. The key insight is that you do not need to track which layer a value came from or perform any conflict resolution beyond simple replacement. The order of the input list is the only thing that matters.

3. Step-by-Step Strategy

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solution.py

Python 3.13

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