from __future__ import print_function import collections import re import sys import gzip import zlib _COMPRESSED_MARKER = 0xFF def check_non_ascii(msg): for c in msg: if ord(c) >= 0x80: print( 'Unable to generate compressed data: message "{}" contains a non-ascii character "{}".'.format( msg, c ), file=sys.stderr, ) sys.exit(1) # Replace with . # Trivial scheme to demo/test. def space_compression(error_strings): for line in error_strings: check_non_ascii(line) result = "" for i in range(len(line)): if i > 0 and line[i] == " ": result = result[:-1] result += "\\{:03o}".format(ord(line[i - 1])) else: result += line[i] error_strings[line] = result return None # Replace common words with <0x80 | index>. # Index is into a table of words stored as aaaaa<0x80|a>bbb<0x80|b>... # Replaced words are assumed to have spaces either side to avoid having to store the spaces in the compressed strings. def word_compression(error_strings): topn = collections.Counter() for line in error_strings.keys(): check_non_ascii(line) for word in line.split(" "): topn[word] += 1 # Order not just by frequency, but by expected saving. i.e. prefer a longer string that is used less frequently. # Use the word itself for ties so that compression is deterministic. def bytes_saved(item): w, n = item return -((len(w) + 1) * (n - 1)), w top128 = sorted(topn.items(), key=bytes_saved)[:128] index = [w for w, _ in top128] index_lookup = {w: i for i, w in enumerate(index)} for line in error_strings.keys(): result = "" need_space = False for word in line.split(" "): if word in index_lookup: result += "\\{:03o}".format(0b10000000 | index_lookup[word]) need_space = False else: if need_space: result += " " need_space = True result += word error_strings[line] = result.strip() return "".join(w[:-1] + "\\{:03o}".format(0b10000000 | ord(w[-1])) for w in index) # Replace chars in text with variable length bit sequence. # For comparison only (the table is not emitted). def huffman_compression(error_strings): # https://github.com/tannewt/huffman import huffman all_strings = "".join(error_strings) cb = huffman.codebook(collections.Counter(all_strings).items()) for line in error_strings: b = "1" for c in line: b += cb[c] n = len(b) if n % 8 != 0: n += 8 - (n % 8) result = "" for i in range(0, n, 8): result += "\\{:03o}".format(int(b[i : i + 8], 2)) if len(result) > len(line) * 4: result = line error_strings[line] = result # TODO: This would be the prefix lengths and the table ordering. return "_" * (10 + len(cb)) # Replace common N-letter sequences with <0x80 | index>, where # the common sequences are stored in a separate table. # This isn't very useful, need a smarter way to find top-ngrams. def ngram_compression(error_strings): topn = collections.Counter() N = 2 for line in error_strings.keys(): check_non_ascii(line) if len(line) < N: continue for i in range(0, len(line) - N, N): topn[line[i : i + N]] += 1 def bytes_saved(item): w, n = item return -(len(w) * (n - 1)) top128 = sorted(topn.items(), key=bytes_saved)[:128] index = [w for w, _ in top128] index_lookup = {w: i for i, w in enumerate(index)} for line in error_strings.keys(): result = "" for i in range(0, len(line) - N + 1, N): word = line[i : i + N] if word in index_lookup: result += "\\{:03o}".format(0b10000000 | index_lookup[word]) else: result += word if len(line) % N != 0: result += line[len(line) - len(line) % N :] error_strings[line] = result.strip() return "".join(index) def main(collected_path, fn): error_strings = collections.OrderedDict() max_uncompressed_len = 0 num_uses = 0 # Read in all MP_ERROR_TEXT strings. with open(collected_path, "r") as f: for line in f: line = line.strip() if not line: continue num_uses += 1 error_strings[line] = None max_uncompressed_len = max(max_uncompressed_len, len(line)) # So that objexcept.c can figure out how big the buffer needs to be. print("#define MP_MAX_UNCOMPRESSED_TEXT_LEN ({})".format(max_uncompressed_len)) # Run the compression. compressed_data = fn(error_strings) # Print the data table. print('MP_COMPRESSED_DATA("{}")'.format(compressed_data)) # Print the replacements. for uncomp, comp in error_strings.items(): if uncomp == comp: prefix = "" else: prefix = "\\{:03o}".format(_COMPRESSED_MARKER) print('MP_MATCH_COMPRESSED("{}", "{}{}")'.format(uncomp, prefix, comp)) # Used to calculate the "true" length of the (escaped) compressed strings. def unescape(s): return re.sub(r"\\\d\d\d", "!", s) # Stats. Note this doesn't include the cost of the decompressor code. uncomp_len = sum(len(s) + 1 for s in error_strings.keys()) comp_len = sum(1 + len(unescape(s)) + 1 for s in error_strings.values()) data_len = len(compressed_data) + 1 if compressed_data else 0 print("// Total input length: {}".format(uncomp_len)) print("// Total compressed length: {}".format(comp_len)) print("// Total data length: {}".format(data_len)) print("// Predicted saving: {}".format(uncomp_len - comp_len - data_len)) # Somewhat meaningless comparison to zlib/gzip. all_input_bytes = "\\0".join(error_strings.keys()).encode() print() if hasattr(gzip, "compress"): gzip_len = len(gzip.compress(all_input_bytes)) + num_uses * 4 print("// gzip length: {}".format(gzip_len)) print("// Percentage of gzip: {:.1f}%".format(100 * (comp_len + data_len) / gzip_len)) if hasattr(zlib, "compress"): zlib_len = len(zlib.compress(all_input_bytes)) + num_uses * 4 print("// zlib length: {}".format(zlib_len)) print("// Percentage of zlib: {:.1f}%".format(100 * (comp_len + data_len) / zlib_len)) if __name__ == "__main__": main(sys.argv[1], word_compression)