260409
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Why? Multi-tenant environments. First, we need to understand a few differences between environments:
So
Most people physically separate their tenancy, such as Claude Code, from their personal vs. work laptops. So in most cases, it's not a big deal.
But when you need multi-tenancy, it becomes super stressful. For example, say you have two different toolkits:
Most MCP auth states or code harnesses don't support profiles, so you can only log in to one.
So therefore... a natural evolution was to have both:
to physically isolate tenancies.
Now we've solved the multiple-profile issue, but the client's problems persist. Now let's get back to the environments:
All MCP auth or toolkit auth info should always be saved in the Agent Runtime Environment IMHO. However, a surprising number of harnesses tie them to the LLM server (such as Codex Apps or Claude.ai Plugins) or put them in the end-user UI (Claude Desktop or Codex Desktop).
Now the problem is:
The only way to reliably isolate different auth information is thus:
Then
are both isolated VPS, and
This way, you can provide different toolkits, creating multiple dev environments.
Solved at: 220904
Given an array of integers nums sorted in ascending order, and an integer target, write a function to search target in nums. If target exists, then return its index. Otherwise, return -1.
You must write an algorithm with O(log n) runtime complexity.
class Solution: def _search(self, nums: List[int], target:int, start:int, end:int) -> int: mid = (end + start) // 2 # print(start, end, target, mid, nums[mid]) if nums[mid] == target: return mid elif nums[mid] != target and end <= start: return -1 elif nums[mid] > target: return self._search(nums, target, start, mid-1) elif nums[mid] < target: return self._search(nums, target, mid+1, end) else: return -1
def search(self, nums: List[int], target: int) -> int: return self._search(nums, target, 0, len(nums)-1)O(n)
O(1)
class Solution: def _search(self, nums: List[int], target:int, start:int, end:int) -> int: mid = (end + start) // 2 # print(start, end, target, mid, nums[mid]) if nums[mid] == target: return mid elif nums[mid] != target and end <= start: return -1 elif nums[mid] > target: return self._search(nums, target, start, mid-1) elif nums[mid] < target: return self._search(nums, target, mid+1, end) else: return -1
def search(self, nums: List[int], target: int) -> int: return self._search(nums, target, 0, len(nums)-1)