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+.. _faq:
+
+FAQ
+===
+
+This part of the documentation answers some common questions. If you want to add some questions you can simply open an issue `here <https://github.com/camelot-dev/camelot/issues/new>`_.
+
+
+How to reduce memory usage for long PDFs?
+---------------------------------------------------
+
+During table extraction from long PDF documents, RAM usage can grow significantly.
+ 
+A simple workaround is to divide the extraction into some chunks (for example, chunks of 50 pages); at the end of every chunk extraction, data are saved to disk.
+
+For more information, refer to this code snippet from `@anakin87 <https://github.com/anakin87>`_:
+
+.. code-block:: python3
+
+    import camelot
+    
+    def chunks(l, n):
+        """Yield successive n-sized chunks from l."""
+        for i in range(0, len(l), n):
+            yield l[i:i + n]
+    		
+    def extract_tables_with_less_memory_usage(filepath, pages, params={}, 
+ export_path='.', chunks_length=50):
+        """
+        Control page number
+        and subdivide the extraction work into n-pages parts (chunks_length).
+        At the end of every part, save the data on disk and free ram
+        """
+    
+        # get list of document pages from Camelot handler
+        handler=camelot.handlers.PDFHandler(filepath)
+        pages_list=handler._get_pages(filepath,pages=pages)
+        
+        # chunk pages list
+        pages_chunks=list(chunks(pages_list,chunks_length))
+    
+        # extraction and export
+        for chunk in pages_chunks:
+            pages_string=str(chunk).replace('[','').replace(']','')
+            tables = camelot.read_pdf(filepath, pages=pages_string,**params)
+            tables.export(f'{export_path}/tables.json',f='json')