fix: allow dynamic updating when hosted anywhere #5999
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@ogabrielluiz this one is not urgent, but will be nice for our next bugfix release. The component now has no "special" DSLF functionality, which comes at a very small performance hit when (right now) RUNNING on DSLF, but at the benefit of making the component behave consistently across any other hosted environment. |
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…73% in PR #5999 (`bugfix-astra-host`) To optimize this python program for faster runtime, we will make changes to minimize repeated operations and ensure efficient lookups. We'll refactor the way data from the database list is accessed and streamline conditional checks. Here's the optimized version of the provided code. ### Optimization Details. 1. **Conditional Checks**. - Combining multiple conditional checks whenever possible to reduce the number of checks the interpreter has to do. - Directly returning `database_name` if it's already a URL. - Returning `None` early if `database_name` is not provided. 2. **Efficient Lookup**. - Storing the result of `get_database_list_static` in a variable `db_info` reduces redundant calls to `.get()`. - Directly return `None` if `database_name` isn't found in the database list. 3. **Streamlined Method Parameters**. - Simplified how the `api_endpoint` is chosen when calling `get_api_endpoint_static` from `get_api_endpoint` method. With these changes, the code should operate more efficiently, especially in environments with large data sets or multiple function calls, as the chances for redundant operations and overly complex condition checks are minimized.
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…by 12% in PR #5999 (`bugfix-astra-host`) To optimize the given code, we'll focus on reducing redundant computations, optimizing the sequence of operations, and using more efficient data structures if applicable. Let's enhance the performance of the `AstraDBVectorStoreComponent.get_database_object` method by reusing the `client` object optimally. We'll also simplify the logging mechanism in the `Component` class. Here's the refactored code. ### Optimizations Applied. 1. **Reused DataAPIClient**: Introduced a `_client_cache` to store and reuse the `DataAPIClient` instance instead of creating a new instance every time `get_database_object` is called. 2. **Simplified `get_keyspace`**: Simplified the `get_keyspace` method by removing redundant checks. 3. **Optimized `log` Method**. - Merged `name` assignment with a single line. - Used dictionary unpacking to create the `data` dictionary for the event manager, which could be more efficient than multiple assignments. These improvements should reduce the time complexity where applicable and improve the efficiency of object reusability.
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…31% in PR #5999 (`bugfix-astra-host`) ### Key Optimizations.
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…by 37% in PR #5999 (`bugfix-astra-host`) To optimize the given Python program for better performance, we can follow several strategies. One effective approach is to minimize redundant operations and streamline data processing. Here are the changes made to achieve this. 1. **Caching Database Options**: Fetching database and collection options can be an expensive operation. We can cache these options within the instance to avoid repetitive calls. 2. **Minimizing Object Creation**: By avoiding the creation of unnecessary objects within loops and functions, we can reduce the overall memory footprint. 3. **Error Handling**: Avoid logging exceptions multiple times for the same operations. This reduces the overhead caused by excessive logging. Here's the optimized version of the provided program. Key optimizations include caching the database and collection options, minimizing object creation within loops, and streamlining error handling to avoid redundant logging. These changes should make the program run faster and more efficiently.
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…by 161% in PR #5999 (`bugfix-astra-host`) Sure, here is an optimized version of your Python program. In the optimizations below. 1. `get_api_endpoint` leverages memoization to avoid redundant API endpoint lookups. 2. The function `get_keyspace` is simplified. 3. `get_database_object` minimizes attribute access lookups and only logs when tracing is enabled. 4. The `log` method reduces conditional checks and avoids repeated attribute access. ### Explanation. 1. **Memoization in `get_api_endpoint`**. - Cache the API endpoint result with `_api_endpoints_cache` to avoid repeated computations for the same parameters. 2. **Simplified `get_keyspace`**. - Directly return the stripped keyspace or None. 3. **Optimized `get_database_object`**. - Reduced attribute lookups and only log errors if tracing is enabled. 4. **Optimized `log` method**. - Moved message logging logic to a helper `_log_individual_message` to avoid redundant code when processing lists. - Utilizes `data.update()` for updating dictionary only once. These changes will improve the program by reducing redundant computations and streamlining attribute accesses, enhancing both performance and readability.
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…n_options` by 64% in PR #5999 (`bugfix-astra-host`) 2. Avoid redundant object creations. 3. Used `getattr` to avoid nested attribute checks.
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…by 954% in PR #5999 (`bugfix-astra-host`) To optimize the given Python program for faster performance, we need to focus on improving the efficiency of the operations within the methods and reduce repetitive calls where possible. The use of caching and streamlined error handling can also contribute to the performance improvement. Here is an optimized version of the program. ### Changes Made. 1. **Caching with lru_cache**: Added `lru_cache` to `get_api_endpoint` and `get_database_object` methods to avoid repetitive computation and API calls for the same inputs, thus optimizing the performance. 2. **String Manipulation Efficiency**: Simplified the `get_keyspace` method to a single return statement. 3. **Error Logging**: Kept the exception handling concise. 4. **Logging Improvement**: Minor simplification with conditional for the `log` method, ensuring that `name` is set to the default value if not provided. These changes should contribute to a more efficient execution of the program, particularly by caching repeated calls and optimizing string operations.
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This small update removes a condition on the dynamic form updating, which relied on a particular ENV variable being set in order to improve performance in DataStax Langflow. The motivation behind this change is that, when users deploy Langflow in their own hosted environment and use the Astra DB component, the form (thinking it was on hosted DS LF) doesn't have some of the auto-updating features that make the user experience better.