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import logging
from os import PathLike
from typing import BinaryIO
from .cd import (
coherence_ratio,
encoding_languages,
mb_encoding_languages,
merge_coherence_ratios,
)
from .constant import (
IANA_SUPPORTED,
IANA_SUPPORTED_SIMILAR,
TOO_BIG_SEQUENCE,
TOO_SMALL_SEQUENCE,
TRACE,
)
from .md import mess_ratio
from .models import CharsetMatch, CharsetMatches
from .utils import (
any_specified_encoding,
cut_sequence_chunks,
iana_name,
identify_sig_or_bom,
is_multi_byte_encoding,
should_strip_sig_or_bom,
)
logger = logging.getLogger("charset_normalizer")
explain_handler = logging.StreamHandler()
explain_handler.setFormatter(
logging.Formatter("%(asctime)s | %(levelname)s | %(message)s")
)
# Pre-compute a reordered encoding list: multibyte first, then single-byte.
# This allows the mb_definitive_match optimization to fire earlier, skipping
# all single-byte encodings for genuine CJK content. Multibyte codecs
# hard-fail (UnicodeDecodeError) on single-byte data almost instantly, so
# testing them first costs negligible time for non-CJK files.
_mb_supported: list[str] = []
_sb_supported: list[str] = []
for _supported_enc in IANA_SUPPORTED:
try:
if is_multi_byte_encoding(_supported_enc):
_mb_supported.append(_supported_enc)
else:
_sb_supported.append(_supported_enc)
except ImportError:
_sb_supported.append(_supported_enc)
IANA_SUPPORTED_MB_FIRST: list[str] = _mb_supported + _sb_supported
def from_bytes(
sequences: bytes | bytearray,
steps: int = 5,
chunk_size: int = 512,
threshold: float = 0.2,
cp_isolation: list[str] | None = None,
cp_exclusion: list[str] | None = None,
preemptive_behaviour: bool = True,
explain: bool = False,
language_threshold: float = 0.1,
enable_fallback: bool = True,
) -> CharsetMatches:
"""
Given a raw bytes sequence, return the best possibles charset usable to render str objects.
If there is no results, it is a strong indicator that the source is binary/not text.
By default, the process will extract 5 blocks of 512o each to assess the mess and coherence of a given sequence.
And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will.
The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page
but never take it for granted. Can improve the performance.
You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that
purpose.
This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32.
By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain'
toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging.
Custom logging format and handler can be set manually.
"""
if not isinstance(sequences, (bytearray, bytes)):
raise TypeError(
"Expected object of type bytes or bytearray, got: {}".format(
type(sequences)
)
)
if explain:
previous_logger_level: int = logger.level
logger.addHandler(explain_handler)
logger.setLevel(TRACE)
length: int = len(sequences)
if length == 0:
logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.")
if explain: # Defensive: ensure exit path clean handler
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")])
if cp_isolation is not None:
logger.log(
TRACE,
"cp_isolation is set. use this flag for debugging purpose. "
"limited list of encoding allowed : %s.",
", ".join(cp_isolation),
)
cp_isolation = [iana_name(cp, False) for cp in cp_isolation]
else:
cp_isolation = []
if cp_exclusion is not None:
logger.log(
TRACE,
"cp_exclusion is set. use this flag for debugging purpose. "
"limited list of encoding excluded : %s.",
", ".join(cp_exclusion),
)
cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion]
else:
cp_exclusion = []
if length <= (chunk_size * steps):
logger.log(
TRACE,
"override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.",
steps,
chunk_size,
length,
)
steps = 1
chunk_size = length
if steps > 1 and length / steps < chunk_size:
chunk_size = int(length / steps)
is_too_small_sequence: bool = len(sequences) < TOO_SMALL_SEQUENCE
is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE
if is_too_small_sequence:
logger.log(
TRACE,
"Trying to detect encoding from a tiny portion of ({}) byte(s).".format(
length
),
)
elif is_too_large_sequence:
logger.log(
TRACE,
"Using lazy str decoding because the payload is quite large, ({}) byte(s).".format(
length
),
)
prioritized_encodings: list[str] = []
specified_encoding: str | None = (
any_specified_encoding(sequences) if preemptive_behaviour else None
)
if specified_encoding is not None:
prioritized_encodings.append(specified_encoding)
logger.log(
TRACE,
"Detected declarative mark in sequence. Priority +1 given for %s.",
specified_encoding,
)
tested: set[str] = set()
tested_but_hard_failure: list[str] = []
tested_but_soft_failure: list[str] = []
soft_failure_skip: set[str] = set()
success_fast_tracked: set[str] = set()
# Cache for decoded payload deduplication: hash(decoded_payload) -> (mean_mess_ratio, cd_ratios_merged, passed)
# When multiple encodings decode to the exact same string, we can skip the expensive
# mess_ratio and coherence_ratio analysis and reuse the results from the first encoding.
payload_result_cache: dict[int, tuple[float, list[tuple[str, float]], bool]] = {}
# When a definitive result (chaos=0.0 and good coherence) is found after testing
# the prioritized encodings (ascii, utf_8), we can significantly reduce the remaining
# work. Encodings that target completely different language families (e.g., Cyrillic
# when the definitive match is Latin) are skipped entirely.
# Additionally, for same-family encodings that pass chaos probing, we reuse the
# definitive match's coherence ratios instead of recomputing them — a major savings
# since coherence_ratio accounts for ~30% of total time on slow Latin files.
definitive_match_found: bool = False
definitive_target_languages: set[str] = set()
# After the definitive match fires, we cap the number of additional same-family
# single-byte encodings that pass chaos probing. Once we've accumulated enough
# good candidates (N), further same-family SB encodings are unlikely to produce
# a better best() result and just waste mess_ratio + coherence_ratio time.
# The first encoding to trigger the definitive match is NOT counted (it's already in).
post_definitive_sb_success_count: int = 0
POST_DEFINITIVE_SB_CAP: int = 7
# When a non-UTF multibyte encoding passes chaos probing with significant multibyte
# content (decoded length < 98% of raw length), skip all remaining single-byte encodings.
# Rationale: multi-byte decoders (CJK) have strict byte-sequence validation — if they
# decode without error AND pass chaos probing with substantial multibyte content, the
# data is genuinely multibyte encoded. Single-byte encodings will always decode (every
# byte maps to something) but waste time on mess_ratio before failing.
# The 98% threshold prevents false triggers on files that happen to have a few valid
# multibyte pairs (e.g., cp424/_ude_1.txt where big5 decodes with 99% ratio).
mb_definitive_match_found: bool = False
fallback_ascii: CharsetMatch | None = None
fallback_u8: CharsetMatch | None = None
fallback_specified: CharsetMatch | None = None
results: CharsetMatches = CharsetMatches()
early_stop_results: CharsetMatches = CharsetMatches()
sig_encoding, sig_payload = identify_sig_or_bom(sequences)
if sig_encoding is not None:
prioritized_encodings.append(sig_encoding)
logger.log(
TRACE,
"Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.",
len(sig_payload),
sig_encoding,
)
prioritized_encodings.append("ascii")
if "utf_8" not in prioritized_encodings:
prioritized_encodings.append("utf_8")
for encoding_iana in prioritized_encodings + IANA_SUPPORTED_MB_FIRST:
if cp_isolation and encoding_iana not in cp_isolation:
continue
if cp_exclusion and encoding_iana in cp_exclusion:
continue
if encoding_iana in tested:
continue
tested.add(encoding_iana)
decoded_payload: str | None = None
bom_or_sig_available: bool = sig_encoding == encoding_iana
strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom(
encoding_iana
)
if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available:
logger.log(
TRACE,
"Encoding %s won't be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.",
encoding_iana,
)
continue
if encoding_iana in {"utf_7"} and not bom_or_sig_available:
logger.log(
TRACE,
"Encoding %s won't be tested as-is because detection is unreliable without BOM/SIG.",
encoding_iana,
)
continue
# Skip encodings similar to ones that already soft-failed (high mess ratio).
# Checked BEFORE the expensive decode attempt.
if encoding_iana in soft_failure_skip:
logger.log(
TRACE,
"%s is deemed too similar to a code page that was already considered unsuited. Continuing!",
encoding_iana,
)
continue
# Skip encodings that were already fast-tracked from a similar successful encoding.
if encoding_iana in success_fast_tracked:
logger.log(
TRACE,
"Skipping %s: already fast-tracked from a similar successful encoding.",
encoding_iana,
)
continue
try:
is_multi_byte_decoder: bool = is_multi_byte_encoding(encoding_iana)
except (ModuleNotFoundError, ImportError): # Defensive:
logger.log(
TRACE,
"Encoding %s does not provide an IncrementalDecoder",
encoding_iana,
)
continue
# When we've already found a definitive match (chaos=0.0 with good coherence)
# after testing the prioritized encodings, skip encodings that target
# completely different language families. This avoids running expensive
# mess_ratio + coherence_ratio on clearly unrelated candidates (e.g., Cyrillic
# when the definitive match is Latin-based).
if definitive_match_found:
if not is_multi_byte_decoder:
enc_languages = set(encoding_languages(encoding_iana))
else:
enc_languages = set(mb_encoding_languages(encoding_iana))
if not enc_languages.intersection(definitive_target_languages):
logger.log(
TRACE,
"Skipping %s: definitive match already found, this encoding targets different languages (%s vs %s).",
encoding_iana,
enc_languages,
definitive_target_languages,
)
continue
# After the definitive match, cap the number of additional same-family
# single-byte encodings that pass chaos probing. This avoids testing the
# tail of rare, low-value same-family encodings (mac_iceland, cp860, etc.)
# that almost never change best() but each cost ~1-2ms of mess_ratio + coherence.
if (
definitive_match_found
and not is_multi_byte_decoder
and post_definitive_sb_success_count >= POST_DEFINITIVE_SB_CAP
):
logger.log(
TRACE,
"Skipping %s: already accumulated %d same-family results after definitive match (cap=%d).",
encoding_iana,
post_definitive_sb_success_count,
POST_DEFINITIVE_SB_CAP,
)
continue
# When a multibyte encoding with significant multibyte content has already
# passed chaos probing, skip all single-byte encodings. They will either fail
# chaos probing (wasting mess_ratio time) or produce inferior results.
if mb_definitive_match_found and not is_multi_byte_decoder:
logger.log(
TRACE,
"Skipping single-byte %s: multi-byte definitive match already found.",
encoding_iana,
)
continue
try:
if is_too_large_sequence and is_multi_byte_decoder is False:
str(
(
sequences[: int(50e4)]
if strip_sig_or_bom is False
else sequences[len(sig_payload) : int(50e4)]
),
encoding=encoding_iana,
)
else:
# UTF-7 BOM is encoded in modified Base64 whose byte boundary
# can overlap with the next character. Stripping raw SIG bytes
# before decoding may leave stray bytes that decode as garbage.
# Decode the full sequence and remove the leading BOM char instead.
# see https://github.com/jawah/charset_normalizer/issues/718
# and https://github.com/jawah/charset_normalizer/issues/716
if encoding_iana == "utf_7" and bom_or_sig_available:
decoded_payload = str(
sequences,
encoding=encoding_iana,
)
if decoded_payload and decoded_payload[0] == "\ufeff":
decoded_payload = decoded_payload[1:]
else:
decoded_payload = str(
(
sequences
if strip_sig_or_bom is False
else sequences[len(sig_payload) :]
),
encoding=encoding_iana,
)
except (UnicodeDecodeError, LookupError) as e:
if not isinstance(e, LookupError):
logger.log(
TRACE,
"Code page %s does not fit given bytes sequence at ALL. %s",
encoding_iana,
str(e),
)
tested_but_hard_failure.append(encoding_iana)
continue
r_ = range(
0 if not bom_or_sig_available else len(sig_payload),
length,
int(length / steps),
)
multi_byte_bonus: bool = (
is_multi_byte_decoder
and decoded_payload is not None
and len(decoded_payload) < length
)
if multi_byte_bonus:
logger.log(
TRACE,
"Code page %s is a multi byte encoding table and it appear that at least one character "
"was encoded using n-bytes.",
encoding_iana,
)
# Payload-hash deduplication: if another encoding already decoded to the
# exact same string, reuse its mess_ratio and coherence results entirely.
# This is strictly more general than the old IANA_SUPPORTED_SIMILAR approach
# because it catches ALL identical decoding, not just pre-mapped ones.
if decoded_payload is not None and not is_multi_byte_decoder:
payload_hash: int = hash(decoded_payload)
cached = payload_result_cache.get(payload_hash)
if cached is not None:
cached_mess, cached_cd, cached_passed = cached
if cached_passed:
# The previous encoding with identical output passed chaos probing.
fast_match = CharsetMatch(
sequences,
encoding_iana,
cached_mess,
bom_or_sig_available,
cached_cd,
(
decoded_payload
if (
is_too_large_sequence is False
or encoding_iana
in [specified_encoding, "ascii", "utf_8"]
)
else None
),
preemptive_declaration=specified_encoding,
)
results.append(fast_match)
success_fast_tracked.add(encoding_iana)
logger.log(
TRACE,
"%s fast-tracked (identical decoded payload to a prior encoding, chaos=%f %%).",
encoding_iana,
round(cached_mess * 100, ndigits=3),
)
if (
encoding_iana in [specified_encoding, "ascii", "utf_8"]
and cached_mess < 0.1
):
if cached_mess == 0.0:
logger.debug(
"Encoding detection: %s is most likely the one.",
fast_match.encoding,
)
if explain:
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([fast_match])
early_stop_results.append(fast_match)
if (
len(early_stop_results)
and (specified_encoding is None or specified_encoding in tested)
and "ascii" in tested
and "utf_8" in tested
):
probable_result: CharsetMatch = early_stop_results.best() # type: ignore[assignment]
logger.debug(
"Encoding detection: %s is most likely the one.",
probable_result.encoding,
)
if explain:
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([probable_result])
continue
else:
# The previous encoding with identical output failed chaos probing.
tested_but_soft_failure.append(encoding_iana)
logger.log(
TRACE,
"%s fast-skipped (identical decoded payload to a prior encoding that failed chaos probing).",
encoding_iana,
)
# Prepare fallbacks for special encodings even when skipped.
if enable_fallback and encoding_iana in [
"ascii",
"utf_8",
specified_encoding,
"utf_16",
"utf_32",
]:
fallback_entry = CharsetMatch(
sequences,
encoding_iana,
threshold,
bom_or_sig_available,
[],
decoded_payload,
preemptive_declaration=specified_encoding,
)
if encoding_iana == specified_encoding:
fallback_specified = fallback_entry
elif encoding_iana == "ascii":
fallback_ascii = fallback_entry
else:
fallback_u8 = fallback_entry
continue
max_chunk_gave_up: int = int(len(r_) / 4)
max_chunk_gave_up = max(max_chunk_gave_up, 2)
early_stop_count: int = 0
lazy_str_hard_failure = False
md_chunks: list[str] = []
md_ratios = []
try:
for chunk in cut_sequence_chunks(
sequences,
encoding_iana,
r_,
chunk_size,
bom_or_sig_available,
strip_sig_or_bom,
sig_payload,
is_multi_byte_decoder,
decoded_payload,
):
md_chunks.append(chunk)
md_ratios.append(
mess_ratio(
chunk,
threshold,
explain is True and 1 <= len(cp_isolation) <= 2,
)
)
if md_ratios[-1] >= threshold:
early_stop_count += 1
if (early_stop_count >= max_chunk_gave_up) or (
bom_or_sig_available and strip_sig_or_bom is False
):
break
except (
UnicodeDecodeError
) as e: # Lazy str loading may have missed something there
logger.log(
TRACE,
"LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s",
encoding_iana,
str(e),
)
early_stop_count = max_chunk_gave_up
lazy_str_hard_failure = True
# We might want to check the sequence again with the whole content
# Only if initial MD tests passes
if (
not lazy_str_hard_failure
and is_too_large_sequence
and not is_multi_byte_decoder
):
try:
sequences[int(50e3) :].decode(encoding_iana, errors="strict")
except UnicodeDecodeError as e:
logger.log(
TRACE,
"LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s",
encoding_iana,
str(e),
)
tested_but_hard_failure.append(encoding_iana)
continue
mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0
if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up:
tested_but_soft_failure.append(encoding_iana)
if encoding_iana in IANA_SUPPORTED_SIMILAR:
soft_failure_skip.update(IANA_SUPPORTED_SIMILAR[encoding_iana])
# Cache this soft-failure so identical decoding from other encodings
# can be skipped immediately.
if decoded_payload is not None and not is_multi_byte_decoder:
payload_result_cache.setdefault(
hash(decoded_payload), (mean_mess_ratio, [], False)
)
logger.log(
TRACE,
"%s was excluded because of initial chaos probing. Gave up %i time(s). "
"Computed mean chaos is %f %%.",
encoding_iana,
early_stop_count,
round(mean_mess_ratio * 100, ndigits=3),
)
# Preparing those fallbacks in case we got nothing.
if (
enable_fallback
and encoding_iana
in ["ascii", "utf_8", specified_encoding, "utf_16", "utf_32"]
and not lazy_str_hard_failure
):
fallback_entry = CharsetMatch(
sequences,
encoding_iana,
threshold,
bom_or_sig_available,
[],
decoded_payload,
preemptive_declaration=specified_encoding,
)
if encoding_iana == specified_encoding:
fallback_specified = fallback_entry
elif encoding_iana == "ascii":
fallback_ascii = fallback_entry
else:
fallback_u8 = fallback_entry
continue
logger.log(
TRACE,
"%s passed initial chaos probing. Mean measured chaos is %f %%",
encoding_iana,
round(mean_mess_ratio * 100, ndigits=3),
)
if not is_multi_byte_decoder:
target_languages: list[str] = encoding_languages(encoding_iana)
else:
target_languages = mb_encoding_languages(encoding_iana)
if target_languages:
logger.log(
TRACE,
"{} should target any language(s) of {}".format(
encoding_iana, str(target_languages)
),
)
cd_ratios = []
# Run coherence detection on all chunks. We previously tried limiting to
# 1-2 chunks for post-definitive encodings to save time, but this caused
# coverage regressions by producing unrepresentative coherence scores.
# The SB cap and language-family skip optimizations provide sufficient
# speedup without sacrificing coherence accuracy.
if encoding_iana != "ascii":
# We shall skip the CD when its about ASCII
# Most of the time its not relevant to run "language-detection" on it.
for chunk in md_chunks:
chunk_languages = coherence_ratio(
chunk,
language_threshold,
",".join(target_languages) if target_languages else None,
)
cd_ratios.append(chunk_languages)
cd_ratios_merged = merge_coherence_ratios(cd_ratios)
else:
cd_ratios_merged = merge_coherence_ratios(cd_ratios)
if cd_ratios_merged:
logger.log(
TRACE,
"We detected language {} using {}".format(
cd_ratios_merged, encoding_iana
),
)
current_match = CharsetMatch(
sequences,
encoding_iana,
mean_mess_ratio,
bom_or_sig_available,
cd_ratios_merged,
(
decoded_payload
if (
is_too_large_sequence is False
or encoding_iana in [specified_encoding, "ascii", "utf_8"]
)
else None
),
preemptive_declaration=specified_encoding,
)
results.append(current_match)
# Cache the successful result for payload-hash deduplication.
if decoded_payload is not None and not is_multi_byte_decoder:
payload_result_cache.setdefault(
hash(decoded_payload),
(mean_mess_ratio, cd_ratios_merged, True),
)
# Count post-definitive same-family SB successes for the early termination cap.
# Only count low-mess encodings (< 2%) toward the cap. High-mess encodings are
# marginal results that shouldn't prevent better-quality candidates from being
# tested. For example, iso8859_4 (mess=0%) should not be skipped just because
# 7 high-mess Latin encodings (cp1252 at 8%, etc.) were tried first.
if (
definitive_match_found
and not is_multi_byte_decoder
and mean_mess_ratio < 0.02
):
post_definitive_sb_success_count += 1
if (
encoding_iana in [specified_encoding, "ascii", "utf_8"]
and mean_mess_ratio < 0.1
):
# If md says nothing to worry about, then... stop immediately!
if mean_mess_ratio == 0.0:
logger.debug(
"Encoding detection: %s is most likely the one.",
current_match.encoding,
)
if explain: # Defensive: ensure exit path clean handler
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([current_match])
early_stop_results.append(current_match)
if (
len(early_stop_results)
and (specified_encoding is None or specified_encoding in tested)
and "ascii" in tested
and "utf_8" in tested
):
probable_result = early_stop_results.best() # type: ignore[assignment]
logger.debug(
"Encoding detection: %s is most likely the one.",
probable_result.encoding, # type: ignore[union-attr]
)
if explain: # Defensive: ensure exit path clean handler
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([probable_result])
# Once we find a result with good coherence (>= 0.5) after testing the
# prioritized encodings (ascii, utf_8), activate "definitive mode": skip
# encodings that target completely different language families. This avoids
# running expensive mess_ratio + coherence_ratio on clearly unrelated
# candidates (e.g., Cyrillic encodings when the match is Latin-based).
# We require coherence >= 0.5 to avoid false positives (e.g., cp1251 decoding
# Hebrew text with 0.0 chaos but wrong language detection at coherence 0.33).
if not definitive_match_found and not is_multi_byte_decoder:
best_coherence = (
max((v for _, v in cd_ratios_merged), default=0.0)
if cd_ratios_merged
else 0.0
)
if best_coherence >= 0.5 and "ascii" in tested and "utf_8" in tested:
definitive_match_found = True
definitive_target_languages.update(target_languages)
logger.log(
TRACE,
"Definitive match found: %s (chaos=%.3f, coherence=%.2f). Encodings targeting different language families will be skipped.",
encoding_iana,
mean_mess_ratio,
best_coherence,
)
# When a non-UTF multibyte encoding passes chaos probing with significant
# multibyte content (decoded < 98% of raw), activate mb_definitive_match.
# This skips all remaining single-byte encodings which would either soft-fail
# (running expensive mess_ratio for nothing) or produce inferior results.
if (
not mb_definitive_match_found
and is_multi_byte_decoder
and multi_byte_bonus
and decoded_payload is not None
and len(decoded_payload) < length * 0.98
and encoding_iana
not in {
"utf_8",
"utf_8_sig",
"utf_16",
"utf_16_be",
"utf_16_le",
"utf_32",
"utf_32_be",
"utf_32_le",
"utf_7",
}
and "ascii" in tested
and "utf_8" in tested
):
mb_definitive_match_found = True
logger.log(
TRACE,
"Multi-byte definitive match: %s (chaos=%.3f, decoded=%d/%d=%.1f%%). Single-byte encodings will be skipped.",
encoding_iana,
mean_mess_ratio,
len(decoded_payload),
length,
len(decoded_payload) / length * 100,
)
if encoding_iana == sig_encoding:
logger.debug(
"Encoding detection: %s is most likely the one as we detected a BOM or SIG within "
"the beginning of the sequence.",
encoding_iana,
)
if explain: # Defensive: ensure exit path clean handler
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return CharsetMatches([results[encoding_iana]])
if len(results) == 0:
if fallback_u8 or fallback_ascii or fallback_specified:
logger.log(
TRACE,
"Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.",
)
if fallback_specified:
logger.debug(
"Encoding detection: %s will be used as a fallback match",
fallback_specified.encoding,
)
results.append(fallback_specified)
elif (
(fallback_u8 and fallback_ascii is None)
or (
fallback_u8
and fallback_ascii
and fallback_u8.fingerprint != fallback_ascii.fingerprint
)
or (fallback_u8 is not None)
):
logger.debug("Encoding detection: utf_8 will be used as a fallback match")
results.append(fallback_u8)
elif fallback_ascii:
logger.debug("Encoding detection: ascii will be used as a fallback match")
results.append(fallback_ascii)
if results:
logger.debug(
"Encoding detection: Found %s as plausible (best-candidate) for content. With %i alternatives.",
results.best().encoding, # type: ignore
len(results) - 1,
)
else:
logger.debug("Encoding detection: Unable to determine any suitable charset.")
if explain:
logger.removeHandler(explain_handler)
logger.setLevel(previous_logger_level)
return results
def from_fp(
fp: BinaryIO,
steps: int = 5,
chunk_size: int = 512,
threshold: float = 0.20,
cp_isolation: list[str] | None = None,
cp_exclusion: list[str] | None = None,
preemptive_behaviour: bool = True,
explain: bool = False,
language_threshold: float = 0.1,
enable_fallback: bool = True,
) -> CharsetMatches:
"""
Same thing than the function from_bytes but using a file pointer that is already ready.
Will not close the file pointer.
"""
return from_bytes(
fp.read(),
steps,
chunk_size,
threshold,
cp_isolation,
cp_exclusion,
preemptive_behaviour,
explain,
language_threshold,
enable_fallback,
)
def from_path(
path: str | bytes | PathLike, # type: ignore[type-arg]
steps: int = 5,
chunk_size: int = 512,
threshold: float = 0.20,
cp_isolation: list[str] | None = None,
cp_exclusion: list[str] | None = None,
preemptive_behaviour: bool = True,
explain: bool = False,
language_threshold: float = 0.1,
enable_fallback: bool = True,
) -> CharsetMatches:
"""
Same thing than the function from_bytes but with one extra step. Opening and reading given file path in binary mode.
Can raise IOError.
"""
with open(path, "rb") as fp:
return from_fp(
fp,
steps,
chunk_size,
threshold,
cp_isolation,
cp_exclusion,
preemptive_behaviour,
explain,
language_threshold,
enable_fallback,
)
def is_binary(
fp_or_path_or_payload: PathLike | str | BinaryIO | bytes, # type: ignore[type-arg]
steps: int = 5,
chunk_size: int = 512,
threshold: float = 0.20,
cp_isolation: list[str] | None = None,
cp_exclusion: list[str] | None = None,
preemptive_behaviour: bool = True,
explain: bool = False,
language_threshold: float = 0.1,
enable_fallback: bool = False,
) -> bool:
"""
Detect if the given input (file, bytes, or path) points to a binary file. aka. not a string.
Based on the same main heuristic algorithms and default kwargs at the sole exception that fallbacks match
are disabled to be stricter around ASCII-compatible but unlikely to be a string.
"""
if isinstance(fp_or_path_or_payload, (str, PathLike)):
guesses = from_path(
fp_or_path_or_payload,
steps=steps,
chunk_size=chunk_size,
threshold=threshold,
cp_isolation=cp_isolation,
cp_exclusion=cp_exclusion,
preemptive_behaviour=preemptive_behaviour,
explain=explain,
language_threshold=language_threshold,
enable_fallback=enable_fallback,
)
elif isinstance(
fp_or_path_or_payload,
(
bytes,
bytearray,
),
):
guesses = from_bytes(
fp_or_path_or_payload,
steps=steps,
chunk_size=chunk_size,
threshold=threshold,
cp_isolation=cp_isolation,
cp_exclusion=cp_exclusion,
preemptive_behaviour=preemptive_behaviour,
explain=explain,
language_threshold=language_threshold,
enable_fallback=enable_fallback,
)
else:
guesses = from_fp(
fp_or_path_or_payload,
steps=steps,
chunk_size=chunk_size,
threshold=threshold,
cp_isolation=cp_isolation,
cp_exclusion=cp_exclusion,
preemptive_behaviour=preemptive_behaviour,
explain=explain,
language_threshold=language_threshold,
enable_fallback=enable_fallback,
)
return not guesses
|