Batch scrobble rule application by type to reduce N queries to 2 (#61)
* Implement optimized batch rule application - Add apply_all_album_rules/1 to batch apply all album rules in single query - Add apply_all_artist_rules/1 to batch apply all artist rules in single query - Update apply_all_rules/0 to use new batch functions - Add comprehensive tests for batch application - Use CASE statement in SQL to apply multiple rules efficiently Co-authored-by: cloud8421 <537608+cloud8421@users.noreply.github.com> * Add batch application support for track-filtered rules - Extend apply_all_album_rules/2 to support filtering by tracks - Extend apply_all_artist_rules/2 to support filtering by tracks - Update apply_all_rules/1 to use batch functions for track-filtered application - Remove duplicate function definitions - Ensures both main use cases (all tracks and specific tracks) are optimized Co-authored-by: cloud8421 <537608+cloud8421@users.noreply.github.com> * Add comprehensive documentation for optimization - Document the problem and solution approach - Explain SQL generation and performance impact - Detail trade-offs and backward compatibility - Include future considerations and scalability notes Co-authored-by: cloud8421 <537608+cloud8421@users.noreply.github.com> * Apply credo suggestions and format --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: cloud8421 <537608+cloud8421@users.noreply.github.com> Co-authored-by: Claudio Ortolina <cloud8421@gmail.com>
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@@ -0,0 +1,219 @@
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# Scrobble Rule Application Optimization
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## Overview
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This document describes the optimization made to the scrobble rule application system to improve performance when applying multiple rules.
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## Problem
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Previously, when applying all enabled scrobble rules, each rule was applied independently with a separate database UPDATE query. With N rules, this resulted in N separate database operations, which became inefficient as the number of rules grew.
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### Previous Implementation
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```elixir
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def apply_all_rules do
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list_enabled_rules()
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|> Enum.map(fn rule ->
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case apply_rule(rule) do
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{:ok, count} -> {:ok, {rule.type, rule.match_value, count}}
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{:error, reason} -> {:error, {rule.type, rule.match_value, reason}}
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end
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end)
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end
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```
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This approach meant:
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- 10 rules = 10 separate UPDATE queries
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- 100 rules = 100 separate UPDATE queries
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- Each query had to scan the entire `scrobbled_tracks` table
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## Solution
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The optimization groups rules by type (album/artist) and applies all rules of each type in a single database query using SQLite's CASE statement.
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### New Implementation
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```elixir
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def apply_all_rules do
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enabled_rules = list_enabled_rules()
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# Group rules by type
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{album_rules, artist_rules} =
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Enum.split_with(enabled_rules, fn rule -> rule.type == :album end)
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# Apply all album rules in one query
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apply_all_album_rules(album_rules)
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# Apply all artist rules in one query
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apply_all_artist_rules(artist_rules)
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end
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```
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This approach means:
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- 10 album rules + 10 artist rules = 2 total UPDATE queries (one for albums, one for artists)
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- 100 album rules + 100 artist rules = 2 total UPDATE queries
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- Each query still scans the table once, but updates all matching records in a single pass
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## Technical Details
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### SQL Generation
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The optimization dynamically builds a CASE statement for all rules of the same type:
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**Example for 2 album rules:**
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```sql
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UPDATE scrobbled_tracks
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SET album = CASE
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WHEN json_extract(album, '$.title') = 'Dark Side of the Moon'
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THEN json_set(album, '$.musicbrainz_id', '12345678-1234-1234-1234-123456789012')
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WHEN json_extract(album, '$.title') = 'Wish You Were Here'
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THEN json_set(album, '$.musicbrainz_id', 'abcdef12-3456-7890-abcd-ef1234567890')
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ELSE album
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END
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WHERE json_extract(album, '$.title') IN ('Dark Side of the Moon', 'Wish You Were Here')
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```
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The WHERE clause uses IN to filter only tracks that match any of the rules, avoiding unnecessary updates.
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### Functions Added
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#### 1. `apply_all_album_rules/1`
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Applies all album rules in a single query.
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```elixir
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@spec apply_all_album_rules([ScrobbleRule.t()]) :: {:ok, non_neg_integer()} | {:error, any()}
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```
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#### 2. `apply_all_artist_rules/1`
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Applies all artist rules in a single query.
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```elixir
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@spec apply_all_artist_rules([ScrobbleRule.t()]) :: {:ok, non_neg_integer()} | {:error, any()}
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```
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#### 3. `apply_all_album_rules/2`
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Applies all album rules to a specific set of tracks in a single query.
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```elixir
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@spec apply_all_album_rules([ScrobbleRule.t()], [Track.t()]) ::
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{:ok, non_neg_integer()} | {:error, any()}
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```
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#### 4. `apply_all_artist_rules/2`
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Applies all artist rules to a specific set of tracks in a single query.
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```elixir
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@spec apply_all_artist_rules([ScrobbleRule.t()], [Track.t()]) ::
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{:ok, non_neg_integer()} | {:error, any()}
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```
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### Use Cases
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The optimization handles two main use cases:
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#### 1. Periodic Full Application
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The `ApplyScrobbleRules` Oban worker runs every 30 minutes and applies all rules to all tracks:
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```elixir
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ScrobbleRules.apply_all_rules()
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```
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#### 2. Incremental Application on New Tracks
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When new tracks are inserted via `LastFm.Feed.update/1`, rules are applied to just those tracks:
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```elixir
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tracks
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|> ScrobbleRules.apply_all_rules()
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```
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Both use cases now benefit from batched rule application.
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## Performance Impact
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### Expected Improvements
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For a database with:
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- 10,000 scrobbled tracks
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- 20 enabled rules (10 album + 10 artist)
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**Before:**
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- 20 UPDATE queries
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- Each query scans ~10,000 rows
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- Total: ~200,000 row scans
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**After:**
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- 2 UPDATE queries (1 for albums, 1 for artists)
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- Each query scans ~10,000 rows
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- Total: ~20,000 row scans
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**Result:** ~10x reduction in database operations for this scenario.
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The benefit scales with the number of rules:
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- 5 rules: ~2.5x improvement
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- 10 rules: ~5x improvement
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- 20 rules: ~10x improvement
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- 100 rules: ~50x improvement
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## Trade-offs
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### Return Value Semantics
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With the batched approach, all rules of the same type report the same aggregate count (total rows updated) rather than individual per-rule counts:
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```elixir
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# Before: Each rule gets its own count
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[
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{:ok, {:album, "Album 1", 5}}, # 5 tracks updated
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{:ok, {:album, "Album 2", 3}}, # 3 tracks updated
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]
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# After: Both rules report the total updated
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[
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{:ok, {:album, "Album 1", 8}}, # 8 total tracks updated
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{:ok, {:album, "Album 2", 8}}, # 8 total tracks updated
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]
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```
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This is an acceptable trade-off because:
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1. The logging still shows how many rules were applied
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2. The total tracks updated is more meaningful for understanding impact
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3. Getting individual counts would require separate queries, negating the optimization
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### Backward Compatibility
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The API remains fully backward compatible:
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- All existing functions (`apply_rule/1`, `apply_album_rule/1`, etc.) still work
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- Return value format is unchanged: `{:ok, {type, match_value, count}}`
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- Error handling is unchanged
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- Tests continue to pass
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## Testing
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New tests were added to verify the optimization:
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1. `apply_all_album_rules/1` applies multiple album rules in one query
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2. `apply_all_artist_rules/1` applies multiple artist rules in one query
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3. Empty list handling returns `{:ok, 0}`
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4. `apply_all_rules/0` correctly batches rules by type
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5. All existing tests continue to pass
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## Future Considerations
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### Potential Enhancements
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1. **Parallel Execution**: Album and artist rule applications could run in parallel since they're independent
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2. **Query Optimization**: Could add indexes on `json_extract(album, '$.title')` and `json_extract(artist, '$.name')` if performance is still a concern
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3. **Metrics**: Add telemetry events to track batch sizes and execution times
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4. **Rule Ordering**: If rule priority matters in the future, the CASE statement naturally handles this (first match wins)
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### Scalability
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The current approach scales well up to ~100 rules per type. Beyond that, consider:
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- SQL query length limits (SQLite's default limit is 1MB, which allows ~10,000 rules)
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- Transaction size and memory usage
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- Potential chunking if needed (apply rules in batches of N)
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## Conclusion
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This optimization significantly improves the performance of scrobble rule application by reducing database operations from O(N) to O(1) per rule type, where N is the number of rules. The implementation maintains backward compatibility while providing substantial performance benefits that scale with the number of rules.
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@@ -326,9 +326,229 @@ defmodule MusicLibrary.ScrobbleRules do
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apply_artist_rule(rule, tracks)
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end
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@doc """
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Applies all album rules in a single query.
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Uses a CASE statement to update the musicbrainz_id for all matching albums
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in one database operation, which is more efficient than applying rules individually.
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## Examples
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iex> apply_all_album_rules([rule1, rule2])
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{:ok, 15}
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"""
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def apply_all_album_rules([]), do: {:ok, 0}
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def apply_all_album_rules(rules) when is_list(rules) do
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# Build CASE WHEN clauses dynamically
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{case_clauses, case_params} =
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rules
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|> Enum.reduce({"", []}, fn rule, {sql_acc, params_acc} ->
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clause =
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"WHEN json_extract(album, '$.title') = ? THEN json_set(album, '$.musicbrainz_id', ?) "
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{sql_acc <> clause, params_acc ++ [rule.match_value, rule.target_musicbrainz_id]}
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end)
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# Build complete UPDATE statement
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case_sql = "CASE #{case_clauses}ELSE album END"
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# Build WHERE IN clause
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match_values = Enum.map(rules, & &1.match_value)
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in_placeholders = Enum.map_join(match_values, ", ", fn _ -> "?" end)
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where_sql = "json_extract(album, '$.title') IN (#{in_placeholders})"
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# Complete SQL
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sql = """
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UPDATE scrobbled_tracks
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SET album = #{case_sql}
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WHERE #{where_sql}
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"""
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# All parameters: case params + where params
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all_params = case_params ++ match_values
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# Execute the query
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case Repo.query(sql, all_params) do
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{:ok, %{num_rows: count}} -> {:ok, count}
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{:error, reason} -> {:error, reason}
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end
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end
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@doc """
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Applies all album rules to a specific set of tracks in a single query.
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Uses a CASE statement to update the musicbrainz_id for all matching albums
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in one database operation, filtering by the provided tracks.
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## Examples
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iex> apply_all_album_rules([rule1, rule2], tracks)
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{:ok, 3}
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"""
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def apply_all_album_rules([], _tracks), do: {:ok, 0}
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def apply_all_album_rules(_rules, []), do: {:ok, 0}
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def apply_all_album_rules(rules, tracks) when is_list(rules) and is_list(tracks) do
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# Build CASE WHEN clauses dynamically
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{case_clauses, case_params} =
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rules
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|> Enum.reduce({"", []}, fn rule, {sql_acc, params_acc} ->
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clause =
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"WHEN json_extract(album, '$.title') = ? THEN json_set(album, '$.musicbrainz_id', ?) "
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{sql_acc <> clause, params_acc ++ [rule.match_value, rule.target_musicbrainz_id]}
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end)
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# Build complete UPDATE statement
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case_sql = "CASE #{case_clauses}ELSE album END"
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# Build WHERE IN clause for album titles
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match_values = Enum.map(rules, & &1.match_value)
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album_placeholders = Enum.map_join(match_values, ", ", fn _ -> "?" end)
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# Build WHERE IN clause for track timestamps
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track_scrobbled_at_uts = Enum.map(tracks, & &1.scrobbled_at_uts)
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track_placeholders = Enum.map_join(track_scrobbled_at_uts, ", ", fn _ -> "?" end)
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where_sql =
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"json_extract(album, '$.title') IN (#{album_placeholders}) AND " <>
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"scrobbled_at_uts IN (#{track_placeholders})"
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# Complete SQL
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sql = """
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UPDATE scrobbled_tracks
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SET album = #{case_sql}
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WHERE #{where_sql}
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"""
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# All parameters: case params + album match values + track timestamps
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all_params = case_params ++ match_values ++ track_scrobbled_at_uts
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# Execute the query
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case Repo.query(sql, all_params) do
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{:ok, %{num_rows: count}} -> {:ok, count}
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{:error, reason} -> {:error, reason}
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end
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end
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@doc """
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Applies all artist rules in a single query.
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Uses a CASE statement to update the musicbrainz_id for all matching artists
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in one database operation, which is more efficient than applying rules individually.
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## Examples
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iex> apply_all_artist_rules([rule1, rule2])
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{:ok, 25}
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"""
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def apply_all_artist_rules([]), do: {:ok, 0}
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def apply_all_artist_rules(rules) when is_list(rules) do
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# Build CASE WHEN clauses dynamically
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{case_clauses, case_params} =
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rules
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|> Enum.reduce({"", []}, fn rule, {sql_acc, params_acc} ->
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clause =
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"WHEN json_extract(artist, '$.name') = ? THEN json_set(artist, '$.musicbrainz_id', ?) "
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{sql_acc <> clause, params_acc ++ [rule.match_value, rule.target_musicbrainz_id]}
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end)
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# Build complete UPDATE statement
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case_sql = "CASE #{case_clauses}ELSE artist END"
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# Build WHERE IN clause
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match_values = Enum.map(rules, & &1.match_value)
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in_placeholders = Enum.map_join(match_values, ", ", fn _ -> "?" end)
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where_sql = "json_extract(artist, '$.name') IN (#{in_placeholders})"
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# Complete SQL
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sql = """
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UPDATE scrobbled_tracks
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SET artist = #{case_sql}
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WHERE #{where_sql}
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"""
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# All parameters: case params + where params
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all_params = case_params ++ match_values
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# Execute the query
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case Repo.query(sql, all_params) do
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{:ok, %{num_rows: count}} -> {:ok, count}
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{:error, reason} -> {:error, reason}
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end
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end
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@doc """
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Applies all artist rules to a specific set of tracks in a single query.
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Uses a CASE statement to update the musicbrainz_id for all matching artists
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in one database operation, filtering by the provided tracks.
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## Examples
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iex> apply_all_artist_rules([rule1, rule2], tracks)
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{:ok, 7}
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"""
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def apply_all_artist_rules([], _tracks), do: {:ok, 0}
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def apply_all_artist_rules(_rules, []), do: {:ok, 0}
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def apply_all_artist_rules(rules, tracks) when is_list(rules) and is_list(tracks) do
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# Build CASE WHEN clauses dynamically
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{case_clauses, case_params} =
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rules
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|> Enum.reduce({"", []}, fn rule, {sql_acc, params_acc} ->
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clause =
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"WHEN json_extract(artist, '$.name') = ? THEN json_set(artist, '$.musicbrainz_id', ?) "
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{sql_acc <> clause, params_acc ++ [rule.match_value, rule.target_musicbrainz_id]}
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end)
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# Build complete UPDATE statement
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case_sql = "CASE #{case_clauses}ELSE artist END"
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# Build WHERE IN clause for artist names
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match_values = Enum.map(rules, & &1.match_value)
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artist_placeholders = Enum.map_join(match_values, ", ", fn _ -> "?" end)
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# Build WHERE IN clause for track timestamps
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track_scrobbled_at_uts = Enum.map(tracks, & &1.scrobbled_at_uts)
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track_placeholders = Enum.map_join(track_scrobbled_at_uts, ", ", fn _ -> "?" end)
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where_sql =
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"json_extract(artist, '$.name') IN (#{artist_placeholders}) AND " <>
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"scrobbled_at_uts IN (#{track_placeholders})"
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# Complete SQL
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sql = """
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UPDATE scrobbled_tracks
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SET artist = #{case_sql}
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WHERE #{where_sql}
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"""
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# All parameters: case params + artist match values + track timestamps
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all_params = case_params ++ match_values ++ track_scrobbled_at_uts
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# Execute the query
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case Repo.query(sql, all_params) do
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{:ok, %{num_rows: count}} -> {:ok, count}
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{:error, reason} -> {:error, reason}
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end
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end
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@doc """
|
||||
Applies all enabled rules.
|
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|
||||
This optimized version groups rules by type and applies all rules of each type
|
||||
in a single database query, which is much more efficient than applying each rule
|
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individually.
|
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|
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## Examples
|
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|
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iex> apply_all_rules()
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@@ -337,14 +557,45 @@ defmodule MusicLibrary.ScrobbleRules do
|
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"""
|
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def apply_all_rules do
|
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:telemetry.span([:music_library, :scrobble_rules, :apply_all_rules], %{}, fn ->
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result =
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list_enabled_rules()
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|> Enum.map(fn rule ->
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case apply_rule(rule) do
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{:ok, count} -> {:ok, {rule.type, rule.match_value, count}}
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{:error, reason} -> {:error, {rule.type, rule.match_value, reason}}
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end
|
||||
end)
|
||||
enabled_rules = list_enabled_rules()
|
||||
|
||||
# Group rules by type
|
||||
{album_rules, artist_rules} =
|
||||
Enum.split_with(enabled_rules, fn rule -> rule.type == :album end)
|
||||
|
||||
# Apply all album rules in one query
|
||||
album_result =
|
||||
case apply_all_album_rules(album_rules) do
|
||||
{:ok, count} ->
|
||||
# Return the count for each album rule (total updated)
|
||||
# Note: this returns the same count for each rule since they're applied together
|
||||
Enum.map(album_rules, fn rule ->
|
||||
{:ok, {rule.type, rule.match_value, count}}
|
||||
end)
|
||||
|
||||
{:error, reason} ->
|
||||
Enum.map(album_rules, fn rule ->
|
||||
{:error, {rule.type, rule.match_value, reason}}
|
||||
end)
|
||||
end
|
||||
|
||||
# Apply all artist rules in one query
|
||||
artist_result =
|
||||
case apply_all_artist_rules(artist_rules) do
|
||||
{:ok, count} ->
|
||||
# Return the count for each artist rule (total updated)
|
||||
# Note: this returns the same count for each rule since they're applied together
|
||||
Enum.map(artist_rules, fn rule ->
|
||||
{:ok, {rule.type, rule.match_value, count}}
|
||||
end)
|
||||
|
||||
{:error, reason} ->
|
||||
Enum.map(artist_rules, fn rule ->
|
||||
{:error, {rule.type, rule.match_value, reason}}
|
||||
end)
|
||||
end
|
||||
|
||||
result = album_result ++ artist_result
|
||||
|
||||
{result, %{scrobble_track_count: :all}}
|
||||
end)
|
||||
@@ -353,6 +604,9 @@ defmodule MusicLibrary.ScrobbleRules do
|
||||
@doc """
|
||||
Applies all enabled rules to a specific set of tracks.
|
||||
|
||||
This optimized version groups rules by type and applies all rules of each type
|
||||
in a single database query, filtering by the provided tracks.
|
||||
|
||||
## Examples
|
||||
|
||||
iex> apply_all_rules(tracks)
|
||||
@@ -368,14 +622,41 @@ defmodule MusicLibrary.ScrobbleRules do
|
||||
|
||||
def apply_all_rules(tracks) do
|
||||
:telemetry.span([:music_library, :scrobble_rules, :apply_all_rules], %{}, fn ->
|
||||
result =
|
||||
list_enabled_rules()
|
||||
|> Enum.map(fn rule ->
|
||||
case apply_rule(rule, tracks) do
|
||||
{:ok, count} -> {:ok, {rule.type, rule.match_value, count}}
|
||||
{:error, reason} -> {:error, {rule.type, rule.match_value, reason}}
|
||||
end
|
||||
end)
|
||||
enabled_rules = list_enabled_rules()
|
||||
|
||||
# Group rules by type
|
||||
{album_rules, artist_rules} =
|
||||
Enum.split_with(enabled_rules, fn rule -> rule.type == :album end)
|
||||
|
||||
# Apply all album rules in one query
|
||||
album_result =
|
||||
case apply_all_album_rules(album_rules, tracks) do
|
||||
{:ok, count} ->
|
||||
Enum.map(album_rules, fn rule ->
|
||||
{:ok, {rule.type, rule.match_value, count}}
|
||||
end)
|
||||
|
||||
{:error, reason} ->
|
||||
Enum.map(album_rules, fn rule ->
|
||||
{:error, {rule.type, rule.match_value, reason}}
|
||||
end)
|
||||
end
|
||||
|
||||
# Apply all artist rules in one query
|
||||
artist_result =
|
||||
case apply_all_artist_rules(artist_rules, tracks) do
|
||||
{:ok, count} ->
|
||||
Enum.map(artist_rules, fn rule ->
|
||||
{:ok, {rule.type, rule.match_value, count}}
|
||||
end)
|
||||
|
||||
{:error, reason} ->
|
||||
Enum.map(artist_rules, fn rule ->
|
||||
{:error, {rule.type, rule.match_value, reason}}
|
||||
end)
|
||||
end
|
||||
|
||||
result = album_result ++ artist_result
|
||||
|
||||
{result, %{scrobble_track_count: Enum.count(tracks)}}
|
||||
end)
|
||||
|
||||
@@ -287,5 +287,141 @@ defmodule MusicLibrary.ScrobbleRulesTest do
|
||||
|
||||
assert ScrobbleRules.count_artist_matches(rule) == 2
|
||||
end
|
||||
|
||||
test "apply_all_album_rules/1 applies multiple album rules in one query" do
|
||||
# Create two album rules
|
||||
rule1 = scrobble_rule_fixture(@valid_album_attrs)
|
||||
|
||||
rule2 =
|
||||
scrobble_rule_fixture(%{
|
||||
match_value: "Wish You Were Here",
|
||||
target_musicbrainz_id: "abcdef12-3456-7890-abcd-ef1234567890"
|
||||
})
|
||||
|
||||
# Create tracks matching each rule
|
||||
track1 =
|
||||
scrobbled_track_fixture(%{
|
||||
album: %{musicbrainz_id: "", title: "Dark Side of the Moon"}
|
||||
})
|
||||
|
||||
track2 =
|
||||
scrobbled_track_fixture(%{
|
||||
scrobbled_at_uts: System.system_time(:second) + 1,
|
||||
album: %{musicbrainz_id: "", title: "Wish You Were Here"}
|
||||
})
|
||||
|
||||
# Create a non-matching track
|
||||
_track3 =
|
||||
scrobbled_track_fixture(%{
|
||||
scrobbled_at_uts: System.system_time(:second) + 2,
|
||||
album: %{musicbrainz_id: "", title: "The Wall"}
|
||||
})
|
||||
|
||||
# Apply both rules at once
|
||||
assert {:ok, 2} = ScrobbleRules.apply_all_album_rules([rule1, rule2])
|
||||
|
||||
# Verify both tracks were updated by fetching them again
|
||||
updated_track1 = Repo.get(Track, track1.scrobbled_at_uts)
|
||||
assert updated_track1.album.musicbrainz_id == rule1.target_musicbrainz_id
|
||||
|
||||
updated_track2 = Repo.get(Track, track2.scrobbled_at_uts)
|
||||
assert updated_track2.album.musicbrainz_id == rule2.target_musicbrainz_id
|
||||
end
|
||||
|
||||
test "apply_all_artist_rules/1 applies multiple artist rules in one query" do
|
||||
# Create two artist rules
|
||||
rule1 = scrobble_rule_fixture(@valid_artist_attrs)
|
||||
|
||||
rule2 =
|
||||
scrobble_rule_fixture(%{
|
||||
type: :artist,
|
||||
match_value: "Led Zeppelin",
|
||||
target_musicbrainz_id: "fedcba98-7654-3210-fedc-ba9876543210"
|
||||
})
|
||||
|
||||
# Create tracks matching each rule
|
||||
track1 =
|
||||
scrobbled_track_fixture(%{
|
||||
artist: %{musicbrainz_id: "", name: "Pink Floyd"}
|
||||
})
|
||||
|
||||
track2 =
|
||||
scrobbled_track_fixture(%{
|
||||
scrobbled_at_uts: System.system_time(:second) + 1,
|
||||
artist: %{musicbrainz_id: "", name: "Led Zeppelin"}
|
||||
})
|
||||
|
||||
# Create a non-matching track
|
||||
_track3 =
|
||||
scrobbled_track_fixture(%{
|
||||
scrobbled_at_uts: System.system_time(:second) + 2,
|
||||
artist: %{musicbrainz_id: "", name: "The Beatles"}
|
||||
})
|
||||
|
||||
# Apply both rules at once
|
||||
assert {:ok, 2} = ScrobbleRules.apply_all_artist_rules([rule1, rule2])
|
||||
|
||||
# Verify both tracks were updated by fetching them again
|
||||
updated_track1 = Repo.get(Track, track1.scrobbled_at_uts)
|
||||
assert updated_track1.artist.musicbrainz_id == rule1.target_musicbrainz_id
|
||||
|
||||
updated_track2 = Repo.get(Track, track2.scrobbled_at_uts)
|
||||
assert updated_track2.artist.musicbrainz_id == rule2.target_musicbrainz_id
|
||||
end
|
||||
|
||||
test "apply_all_album_rules/1 with empty list returns 0" do
|
||||
assert {:ok, 0} = ScrobbleRules.apply_all_album_rules([])
|
||||
end
|
||||
|
||||
test "apply_all_artist_rules/1 with empty list returns 0" do
|
||||
assert {:ok, 0} = ScrobbleRules.apply_all_artist_rules([])
|
||||
end
|
||||
|
||||
test "apply_all_rules/0 batches rules by type" do
|
||||
# Create multiple rules of each type
|
||||
_album_rule1 = scrobble_rule_fixture(@valid_album_attrs)
|
||||
|
||||
_album_rule2 =
|
||||
scrobble_rule_fixture(%{
|
||||
match_value: "Wish You Were Here",
|
||||
target_musicbrainz_id: "abcdef12-3456-7890-abcd-ef1234567890"
|
||||
})
|
||||
|
||||
_artist_rule1 = scrobble_rule_fixture(@valid_artist_attrs)
|
||||
|
||||
_artist_rule2 =
|
||||
scrobble_rule_fixture(%{
|
||||
type: :artist,
|
||||
match_value: "Led Zeppelin",
|
||||
target_musicbrainz_id: "fedcba98-7654-3210-fedc-ba9876543210"
|
||||
})
|
||||
|
||||
# Create tracks matching the rules
|
||||
_track1 =
|
||||
scrobbled_track_fixture(%{
|
||||
album: %{musicbrainz_id: "", title: "Dark Side of the Moon"},
|
||||
artist: %{musicbrainz_id: "", name: "Pink Floyd"}
|
||||
})
|
||||
|
||||
_track2 =
|
||||
scrobbled_track_fixture(%{
|
||||
scrobbled_at_uts: System.system_time(:second) + 1,
|
||||
album: %{musicbrainz_id: "", title: "Wish You Were Here"},
|
||||
artist: %{musicbrainz_id: "", name: "Led Zeppelin"}
|
||||
})
|
||||
|
||||
# Apply all rules
|
||||
results = ScrobbleRules.apply_all_rules()
|
||||
|
||||
# Should have 4 results (one for each rule)
|
||||
assert length(results) == 4
|
||||
|
||||
# All results should be successful
|
||||
Enum.each(results, fn result ->
|
||||
assert {:ok, {_type, _match_value, count}} = result
|
||||
# Count should be > 0 since we have matching tracks
|
||||
assert count > 0
|
||||
end)
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
Reference in New Issue
Block a user