Upload source/scrape_and_upload_v3.py with huggingface_hub

source/scrape_and_upload_v3.py

@@ -0,0 +1,181 @@
+#!/usr/bin/env python3
+"""Download data from HuggingFace datasets and upload to OpenTransformer/web-crawl-2026
+V3: Large chunks (1M rows, ~1GB compressed) to reduce number of uploads"""
+import os
+import json
+import gzip
+import time
+import traceback
+from datasets import load_dataset
+from huggingface_hub import HfApi, login
+
+HF_TOKEN = "HF_TOKEN_REDACTED"
+TARGET_REPO = "OpenTransformer/web-crawl-2026"
+OUTPUT_DIR = "/workspace/scraped_data"
+CHUNK_SIZE = 1000000  # 1M rows per chunk (~1GB compressed)
+STATE_FILE = "/workspace/scrape_state.json"
+
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+login(token=HF_TOKEN)
+api = HfApi(token=HF_TOKEN)
+
+SOURCES = [
+    ("HuggingFaceFW/fineweb-edu", "sample-10BT", "train", "text"),
+    ("allenai/c4", "en", "train", "text"),
+    ("cerebras/SlimPajama-627B", None, "train", "text"),
+    ("uonlp/CulturaX", "en", "train", "text"),
+]
+
+def load_state():
+    if os.path.exists(STATE_FILE):
+        with open(STATE_FILE) as f:
+            return json.load(f)
+    return {}
+
+def save_state(state):
+    with open(STATE_FILE, "w") as f:
+        json.dump(state, f)
+
+def upload_chunk(filepath, remote_name):
+    fsize = os.path.getsize(filepath) / (1024*1024)
+    print("  Uploading %s (%.1f MB)..." % (remote_name, fsize), flush=True)
+    for attempt in range(5):
+        try:
+            api.upload_file(
+                path_or_fileobj=filepath,
+                path_in_repo="data/" + remote_name,
+                repo_id=TARGET_REPO,
+                repo_type="dataset",
+            )
+            print("  Uploaded %s (%.1f MB)" % (remote_name, fsize), flush=True)
+            return True
+        except Exception as e:
+            print("  Upload attempt %d failed: %s" % (attempt+1, e), flush=True)
+            time.sleep(30 * (attempt+1))
+    return False
+
+def process_source(name, config, split, text_field):
+    sep = "=" * 60
+    print("\n" + sep, flush=True)
+    print("Source: %s (%s)" % (name, config or "default"), flush=True)
+    print(sep, flush=True)
+
+    state = load_state()
+    source_tag = name.replace("/", "_")
+    if config:
+        source_tag += "_" + config.replace("-", "_")
+    state_key = source_tag
+
+    start_chunk = state.get(state_key, {}).get("next_chunk_v3", 0)
+    skip_rows = state.get(state_key, {}).get("total_rows_v3", 0)
+    print("  V3 resuming from chunk %d (skipping %d rows)" % (start_chunk, skip_rows), flush=True)
+
+    try:
+        if config:
+            ds = load_dataset(name, config, split=split, streaming=True)
+        else:
+            ds = load_dataset(name, split=split, streaming=True)
+    except Exception as e:
+        print("  Failed to load: %s" % e, flush=True)
+        return
+
+    chunk_num = start_chunk
+    total_rows = 0
+    skipped = 0
+    
+    # Stream directly to gzip file to save memory
+    chunk_name = "%s_big_chunk%04d.jsonl.gz" % (source_tag, chunk_num)
+    chunk_path = os.path.join(OUTPUT_DIR, chunk_name)
+    f = gzip.open(chunk_path, "wt", encoding="utf-8")
+    rows_in_chunk = 0
+
+    for example in ds:
+        if skipped < skip_rows:
+            skipped += 1
+            if skipped % 1000000 == 0:
+                print("  Skipping... %d/%d" % (skipped, skip_rows), flush=True)
+            continue
+
+        text = example.get(text_field) or example.get("text") or example.get("content") or ""
+        if len(text) < 100:
+            continue
+
+        row = json.dumps({
+            "text": text,
+            "source": name,
+            "url": example.get("url", ""),
+        }, ensure_ascii=False)
+        f.write(row + "\n")
+        rows_in_chunk += 1
+        total_rows += 1
+
+        if rows_in_chunk % 100000 == 0:
+            print("  Chunk %d progress: %dk rows, total: %dk" % (chunk_num, rows_in_chunk//1000, (total_rows+skip_rows)//1000), flush=True)
+
+        if rows_in_chunk >= CHUNK_SIZE:
+            f.close()
+            print("  Chunk %d complete: %d rows" % (chunk_num, rows_in_chunk), flush=True)
+
+            if upload_chunk(chunk_path, chunk_name):
+                os.remove(chunk_path)
+                chunk_num += 1
+                state[state_key] = state.get(state_key, {})
+                state[state_key]["next_chunk_v3"] = chunk_num
+                state[state_key]["total_rows_v3"] = total_rows + skip_rows
+                save_state(state)
+            else:
+                print("  Upload failed, will retry next run", flush=True)
+                try: os.remove(chunk_path)
+                except: pass
+                return
+
+            # Start new chunk
+            chunk_name = "%s_big_chunk%04d.jsonl.gz" % (source_tag, chunk_num)
+            chunk_path = os.path.join(OUTPUT_DIR, chunk_name)
+            f = gzip.open(chunk_path, "wt", encoding="utf-8")
+            rows_in_chunk = 0
+
+    # Final partial chunk
+    f.close()
+    if rows_in_chunk > 0:
+        print("  Final chunk %d: %d rows" % (chunk_num, rows_in_chunk), flush=True)
+        if upload_chunk(chunk_path, chunk_name):
+            os.remove(chunk_path)
+            chunk_num += 1
+            state[state_key] = state.get(state_key, {})
+            state[state_key]["next_chunk_v3"] = chunk_num
+            state[state_key]["total_rows_v3"] = total_rows + skip_rows
+            state[state_key]["done"] = True
+            save_state(state)
+    else:
+        try: os.remove(chunk_path)
+        except: pass
+        state[state_key] = state.get(state_key, {})
+        state[state_key]["done"] = True
+        save_state(state)
+
+    print("  Done: %s total rows from %s" % ("{:,}".format(total_rows + skip_rows), name), flush=True)
+
+if __name__ == "__main__":
+    print("Web Crawl Data Collector V3 (Large Chunks)", flush=True)
+    print("Target: %s" % TARGET_REPO, flush=True)
+    print("Chunk size: %d rows" % CHUNK_SIZE, flush=True)
+    start = time.time()
+
+    for name, config, split, text_field in SOURCES:
+        state = load_state()
+        source_tag = name.replace("/", "_")
+        if config:
+            source_tag += "_" + config.replace("-", "_")
+        if state.get(source_tag, {}).get("done"):
+            print("Skipping %s (already done)" % name, flush=True)
+            continue
+        try:
+            process_source(name, config, split, text_field)
+        except Exception as e:
+            print("Error processing %s: %s" % (name, e), flush=True)
+            traceback.print_exc()
+            continue
+
+    elapsed = time.time() - start
+    print("\nFinished in %.1f hours" % (elapsed/3600), flush=True)