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populating cache only if there is any cache
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@ -454,9 +454,10 @@ def process_repos_parallel(
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archive_destination: Directory for archives
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cache: Optional cache of previously processed PR entries
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"""
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for pr2entry in tqdm(cache.values(), desc="Adding cache in dataset"):
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dataset.entries.extend(pr2entry.values())
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dataset.to_json(args.output)
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if len(cache) > 0:
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for pr2entry in tqdm(list(cache.values()), desc="Adding cache in dataset"):
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dataset.entries.extend(pr2entry.values())
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dataset.to_json(args.output)
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repo_names = df["name"]
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free_positions = list(range(1, n_workers + 1))
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@ -529,9 +530,10 @@ def process_repos(
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Passing it by reference in order have the latest information, in case of an error
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verbose (bool): Whether to be verbose or not
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"""
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for pr2entry in tqdm(cache.values(), desc="Adding cache in dataset"):
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dataset.entries.extend(pr2entry.values())
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dataset.to_json(args.output)
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if len(cache) > 0:
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for pr2entry in tqdm(list(cache.values()), desc="Adding cache in dataset"):
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dataset.entries.extend(pr2entry.values())
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dataset.to_json(args.output)
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with tqdm(total=len(df), desc="Processing repos") as pbar:
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for _, row in df.iterrows():
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