Generate configs for all language pairs. Remove lang1 and lang2 as parameters.

Also add the undocumented max_train_samples parameter. This parameter is useful if you want to download
only the top-n samples from the train split. Since this parameter is
New version without the 500 parts. Also includes wiki created from wiki dump instead of CC

README.md

@@ -158,14 +158,15 @@ This corpus has been extracted from web crawls using the margin-based bitext min
 
 ### Supported Tasks and Leaderboards
 [More Information Needed]
+
 ### Languages
 
-To load a language pair which isn't part of the config, all you need to do is specify the language code as pairs.
+Configs are generated for all language pairs in both directions.
 You can find the valid pairs in Homepage section of Dataset Description: https://opus.nlpl.eu/CCMatrix.php
 E.g.
 
 ```
-dataset = load_dataset("yhavinga/ccmatrix", lang1="en", lang2="nl")
+dataset = load_dataset("yhavinga/ccmatrix", config="en-nl")
 ```
 
 ## Dataset Structure

ccmatrix.py

@@ -1,5 +1,5 @@
 # coding=utf-8
-# Copyright 2020 HuggingFace Datasets Authors.
+# Copyright 2022 HuggingFace Datasets Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -15,8 +15,11 @@
 
 # Lint as: python3
 import os
+import re
+import warnings
 
 import datasets
+import requests
 
 _DESCRIPTION = """\
 CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
@@ -52,26 +55,51 @@ _CITATION = """\
 
 _VERSION = "1.0.0"
 _FILE = "CCMatrix.{}.{}"  # E.g. CCMatrix.en-nl.nl
+_URL = "https://opus.nlpl.eu/CCMatrix.php"
 _DOWNLOAD_URL = "https://opus.nlpl.eu/download.php?f=CCMatrix/v1/moses/{}.txt.zip"
 
-_LANGUAGES = ["nl", "en", "de", "fr", "es", "lt", "it"]
 
-_LANGUAGE_PAIRS = [(l1, l2) for l1 in _LANGUAGES for l2 in _LANGUAGES if l1 != l2]
-_SIZES = ["", "1000_000", "25_000_000"]
+def get_language_pairs():
+    try:
+        response = requests.get(_URL)
+    except requests.exceptions.RequestException:
+        warnings.warn(
+            "Unable to download language pairs from '{}'. Using cached version".format(
+                _URL
+            )
+        )
+        from language_pairs_cache import language_pairs
+
+        return language_pairs
+
+    html = response.text
+
+    ccmatrix_hrefs = [
+        href
+        for href in re.findall(r'href=[\'"]?([^\'" >]+)', html)
+        if href.startswith("CCMatrix/")
+    ]
 
-_CONFIGS = [(l1, l2, size) for (l1, l2) in _LANGUAGE_PAIRS for size in _SIZES]
+    language_pairs = []
+    for href in ccmatrix_hrefs:
+        match = re.search(r"CCMatrix/v1/(\w+-\w+)_sample.html", href)
+        if match:
+            language1, language2 = match.group(1).split("-")
+            language_pairs.append((language1, language2))
+            language_pairs.append((language2, language1))
+    language_pairs.sort()
+    return language_pairs
+
+
+_CONFIGS = get_language_pairs()
 
 
 class CCMatrixConfig(datasets.BuilderConfig):
-    def __init__(self, *args, lang1=None, lang2=None, size=None, **kwargs):
-        super().__init__(
-            *args,
-            name=f"{lang1}-{lang2}{'-' + size if size else ''}",
-            **kwargs,
-        )
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        lang1, lang2 = kwargs["name"].split("-")
         self.lang1 = lang1
         self.lang2 = lang2
-        self.size = size
         x, y = (lang1, lang2) if lang1 < lang2 else (lang2, lang1)
         self.download_pair = f"{x}-{y}"
 
@@ -79,16 +107,30 @@ class CCMatrixConfig(datasets.BuilderConfig):
 class CCMatrix(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
         CCMatrixConfig(
-            lang1=lang1,
-            lang2=lang2,
-            size=size,
-            description=f"Translating {lang1} to {lang2} or vice versa{ ' ' + size + ' rows' if size else ''}",
+            name=f"{lang1}-{lang2}",
+            description=f"Translating {lang1} to {lang2} or vice versa",
             version=datasets.Version(_VERSION),
         )
-        for lang1, lang2, size in _CONFIGS
+        for lang1, lang2 in _CONFIGS
     ]
     BUILDER_CONFIG_CLASS = CCMatrixConfig
 
+    def __init__(self, *args, **kwargs):
+        if "max_train_samples" in kwargs and kwargs.get("cache_dir", None) is None:
+            kwargs["cache_dir"] = os.path.join(
+                str(datasets.config.HF_DATASETS_CACHE),
+                "trainsamples_{}".format(kwargs["max_train_samples"]),
+            )
+        self.max_samples = {
+            "train": kwargs.get("max_train_samples", 2**64),
+        }
+        kwargs = {
+            k: v
+            for k, v in kwargs.items()
+            if k not in ["max_train_samples", "id_filter"]
+        }
+        super().__init__(*args, **kwargs)
+
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
@@ -112,11 +154,11 @@ class CCMatrix(datasets.GeneratorBasedBuilder):
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"datapath": path},
+                gen_kwargs={"datapath": path, "max_samples": self.max_samples["train"]},
             )
         ]
 
-    def _generate_examples(self, datapath):
+    def _generate_examples(self, datapath, max_samples):
         l1_path = os.path.join(
             datapath, _FILE.format(self.config.download_pair, self.config.lang1)
         )
@@ -130,7 +172,7 @@ class CCMatrix(datasets.GeneratorBasedBuilder):
             l2_path, encoding="utf-8"
         ) as f2, open(scores_path, encoding="utf-8") as f3:
             for sentence_counter, (x, y, score) in enumerate(zip(f1, f2, f3)):
-                if self.config.size and sentence_counter == int(self.config.size):
+                if sentence_counter == max_samples:
                     return
                 result = (
                     sentence_counter,

language_pairs_cache.py

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+string = """af-da
+af-de
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+zh-fi
+zh-fr
+zh-he
+zh-hi
+zh-hr
+zh-hu
+zh-id
+zh-it
+zh-ja
+zh-ko
+zh-lb
+zh-lt
+zh-lv
+zh-mg
+zh-mk
+zh-ml
+zh-ms
+zh-nl
+zh-no
+zh-pl
+zh-pt
+zh-ro
+zh-ru
+zh-sk
+zh-sl
+zh-sr
+zh-sv
+zh-sw
+zh-ta
+zh-tl
+zh-tr
+zh-uk
+zh-vi
+zh-yi
+zu-ar
+zu-hu
+zu-sw
+"""
+
+language_pairs = []
+for pair in string.splitlines():
+    lang1, lang2 = pair.split("-")
+    language_pairs.append((lang1, lang2))

test_ccmatrix.py

@@ -2,10 +2,10 @@ from datasets import load_dataset
 
 
 def test_streaming_dataset():
-    datasets = load_dataset("./ccmatrix.py", lang1="nl", lang2="en", streaming=True)
-    assert list(datasets.keys()) == ["train"]
+    dataset = load_dataset("./ccmatrix.py", "nl-en", streaming=True)
+    assert list(dataset.keys()) == ["train"]
 
-    train_ds = datasets["train"]
+    train_ds = dataset["train"]
 
     i = iter(train_ds)
     e = next(i)
@@ -34,10 +34,10 @@ def test_streaming_dataset():
 
 
 def test_streaming_dataset_2():
-    datasets = load_dataset("./ccmatrix.py", "nl-en", streaming=True)
-    assert list(datasets.keys()) == ["train"]
+    dataset = load_dataset("./ccmatrix.py", "nl-en", streaming=True)
+    assert list(dataset.keys()) == ["train"]
 
-    train_ds = datasets["train"]
+    train_ds = dataset["train"]
 
     i = iter(train_ds)
     e = next(i)
@@ -65,12 +65,12 @@ def test_streaming_dataset_2():
     }
 
 
-def test_small_config():
-    datasets = load_dataset("./ccmatrix.py", "nl-en-1000_000")
-    assert list(datasets.keys()) == ["train"]
+def test_max_train_samples_1():
+    dataset = load_dataset("./ccmatrix.py", "nl-en", max_train_samples=123)
+    assert list(dataset.keys()) == ["train"]
 
-    train_ds = datasets["train"]
-    assert len(train_ds) == 1000000
+    train_ds = dataset["train"]
+    assert len(train_ds) == 123
 
     i = iter(train_ds)
     e = next(i)
@@ -98,11 +98,12 @@ def test_small_config():
     }
 
 
-def test_medium_config():
-    datasets = load_dataset("./ccmatrix.py", "nl-en-25_000_000", streaming=True)
-    assert list(datasets.keys()) == ["train"]
+def test_max_train_samples_2():
+    dataset = load_dataset("./ccmatrix.py", "nl-en", max_train_samples=256)
+    assert list(dataset.keys()) == ["train"]
 
-    train_ds = datasets["train"]
+    train_ds = dataset["train"]
+    assert len(train_ds) == 256
 
     i = iter(train_ds)
     e = next(i)