mojo_csv 1.5.0, supports mojo 25.5.0

recipes/mojo_csv/README.md

@@ -17,75 +17,60 @@ Add the Modular community channel (https://repo.prefix.dev/modular-community) to
 channels = ["conda-forge", "https://conda.modular.com/max", "https://repo.prefix.dev/modular-community"]
 ```
 
-`pixi add mojo_csv`
 
-##### Basic Usage
+```sh
+pixi add mojo_csv
+```
 
-```mojo
-from mojo_csv import CsvReader
-from pathlib import Path
+## Usage
 
-fn main():
-    var csv_path = Path("path/to/csv/file.csv")
-    var reader = CsvReader(csv_path)
-    for i in range(len(reader)):
-        print(reader[i])
-```
 
-##### Optional Usage
+By default uses all logical cores - 2
+```mojo
+ CsvReader(       
+    in_csv: Path,
+    delimiter: String = ",",
+    quotation_mark: String = '"',
+    num_threads: Int = 0, # default = 0 = use all available cores - 2
+ )
+```
 
 ```mojo
 from mojo_csv import CsvReader
 from pathlib import Path
+from sys import exit
 
-fn main():
+fn main() raises:
     var csv_path = Path("path/to/csv/file.csv")
-    var reader = CsvReader(csv_path, delimiter="|", quotation_mark='*')
+    try:
+        var reader = CsvReader(csv_path)
+    except:
+        exit()
     for i in range(len(reader)):
         print(reader[i])
 ```
 
-#### BETA
-1.4.0 will be the last version where this isn't the default
-
-```mojo
-ThreadedCsvReader(
-    file_path: Path,
-    delimiter: String = ",",
-    quotation_mark: String = '"',
-    num_threads: Int = 0 # 0 = use all available cores
-)
-```
 
-### Example 1: Default (All Cores)
+### Delimiters
 
 ```mojo
-var reader = ThreadedCsvReader(Path("large_file.csv"))
-// Uses all 16 cores on a 16-core system
+    CsvReader(csv_path, delimiter=";", quotation_mark='|')
 ```
 
-### Example 2: Custom Thread Count
-
+### Threads
+__force single threaded__
 ```mojo
-var reader = ThreadedCsvReader(Path("data.csv"), num_threads=4)
-// Uses exactly 4 threads
+CsvReader(csv_pash, num_threads = 1)
 ```
-
-### Example 3: Single-threaded
-
+__use all the threads__
 ```mojo
-var reader = ThreadedCsvReader(Path("data.csv"), num_threads=1)
-// Forces single-threaded execution (same as CsvReader)
-```
-
-### Example 4: Custom Delimiter
+from sys import num_logical_cores
 
-````mojo
-var reader = ThreadedCsvReader(
-    Path("pipe_separated.csv"),
-    delimiter="|",
-    num_threads=8
+var reader = CsvReader(
+    csv_path, num_threads = num_logical_cores()
 )
+```
+
 
 ### Attributes
 
@@ -99,7 +84,7 @@ reader.elements : List[String] # all delimited elements
 reader.length : Int # total number of elements
 ````
 
-##### Indexing
+### Indexing
 
 currently the array is only 1D, so indexing is fairly manual.
 
@@ -109,72 +94,73 @@ reader[0] # first element
 
 ### Performance
 
-- average times over 1k iterations
-- 7950x@5.8ghz (peak clock)
-- uncompiled
+- average times over 100-1k iterations
+- AMD 7950x@5.8ghz
 - single-threaded
 
-micro file benchmark (3 rows)
-mini (100 rows)
-small (1k rows)
-medium file benchmark (100k rows)
-large file benchmark (2m rows)
+micro file benchmark (3 rows) 
+mini (100 rows) 
+small (1k rows) 
+medium file benchmark (100k rows) 
+large file benchmark (2m rows) 
 
 ```log
-✨ Pixi task (bench): mojo bench.mojo
-running benchmark for micro csv:
+✨ Pixi task (bench): mojo bench.mojo                                                                                                                                                      running benchmark for micro csv:
 average time in ms for micro file:
-0.01875
+0.0094 ms
 -------------------------
 running benchmark for mini csv:
 average time in ms for mini file:
-0.07328
+0.0657 ms
 -------------------------
 running benchmark for small csv:
 average time in ms for small file:
-0.417368
+0.317 ms
 -------------------------
 running benchmark for medium csv:
 average time in ms for medium file:
-36.45899
+24.62 ms
 -------------------------
 running benchmark for large csv:
 average time in ms for large file:
-1253.19458
+878.6 ms
 ```
 
-=== ThreadedCsvReader Performance Comparison ===
+#### CSV Reader Performance Comparison
+```
+Small file benchmark (1,000 rows): 
+Single-threaded: 
+Average time: 0.455 ms 
+Multi-threaded: 
+Average time: 0.3744 ms 
+Speedup: 1.22 x 
+
+Medium file benchmark (100,000 rows): 
+Single-threaded: 
+Average time: 37.37 ms 
+Multi-threaded: 
+Average time: 24.46 ms 
+Speedup: 1.53 x 
+
+Large file benchmark (2,000,000 rows): 
+Single-threaded: 
+Average time: 1210.3 ms 
+Multi-threaded: 
+Average time: 863.9 ms 
+Speedup: 1.4 x 
 
-Small file benchmark (1,000 rows):
-Single-threaded:
-Average time: 0.500384 ms
-Multi-threaded:
-Average time: 0.451094 ms
-Speedup: 1.11 x
--------------------------
-Medium file benchmark (100,000 rows):
-Single-threaded:
-Average time: 38.124275 ms
-Multi-threaded:
-Average time: 24.650092 ms
-Speedup: 1.55 x
--------------------------
-Large file benchmark (2,000,000 rows):
-Single-threaded:
-Average time: 1175.345429 ms
-Multi-threaded:
-Average time: 830.02685 ms
-Speedup: 1.42 x
--------------------------
 Summary:
-Small file speedup: 1.11 x
-Medium file speedup: 1.55 x
-Large file speedup: 1.42 x
+Small file speedup: 1.22 x
+Medium file speedup: 1.53 x
+Large file speedup: 1.4 x
+```
 
-_Tested on AMD 7950x (16 cores) @ 5.8GHz_
 
 ## Future Improvements
 
+- [ ] 2D indexing
+- [ ] CsvWriter
+- [ ] CsvDictReader
 - [ ] SIMD optimization within each thread
 - [ ] Async Chunking
 - [ ] Streaming support for very large files

recipes/mojo_csv/recipe.yaml

@@ -1,15 +1,13 @@
 context:
-  version: 1.4.0
-
+  version: 1.5.0
 
 package:
   name: "mojo_csv"
   version: ${{ version }}
 
 source:
   - git: https://github.com/Phelsong/mojo_csv.git
-    rev: d92e7b72933445c71c463d3f9eb52404dd01edf2
-
+    rev: b3a9dc4422efbea7a94939e3a48ff4a3b03e3505
 
 build:
   number: 0
@@ -18,7 +16,7 @@ build:
 
 requirements:
   host:
-    - max >=25.1.0,<26
+    - max >=25.4.0,<26
   run:
     - ${{ pin_compatible('max') }}