![](\"https://img.shields.io/twitter/url/http/shields.io.svg?style=social\"/)
\n The Real First Universal Charset Detector
\n \n ![](\"https://img.shields.io/pypi/pyversions/charset_normalizer.svg?orange=blue\")
\n \n \n ![](\"https://codecov.io/gh/Ousret/charset_normalizer/branch/master/graph/badge.svg\"){kind=icon}
\n \n \n \n \n
\n >>>>> \ud83d\udc49 Try Me Online Now, Then Adopt Me \ud83d\udc48 <<<<<\n
\n\nThis project offers you an alternative to **Universal Charset Encoding Detector**, also known as **Chardet**.\n\n| Feature | [Chardet](https://github.com/chardet/chardet) | Charset Normalizer | [cChardet](https://github.com/PyYoshi/cChardet) |\n| ------------- | :-------------: | :------------------: | :------------------: |\n| `Fast` | \u274c\n![\"Reading](\"https://i.imgflip.com/373iay.gif\")
![\"Cat](\"https://media.tenor.com/images/c0180f70732a18b4965448d33adba3d0/tenor.gif\")
\n\n*\\*\\* : They are clearly using specific code for a specific encoding even if covering most of used one*
\nDid you got there because of the logs? See [https://charset-normalizer.readthedocs.io/en/latest/user/miscellaneous.html](https://charset-normalizer.readthedocs.io/en/latest/user/miscellaneous.html)\n\n## \u2b50 Your support\n\n*Fork, test-it, star-it, submit your ideas! We do listen.*\n \n## \u26a1 Performance\n\nThis package offer better performance than its counterpart Chardet. Here are some numbers.\n\n| Package | Accuracy | Mean per file (ms) | File per sec (est) |\n| ------------- | :-------------: | :------------------: | :------------------: |\n| [chardet](https://github.com/chardet/chardet) | 92 % | 220 ms | 5 file/sec |\n| charset-normalizer | **98 %** | **40 ms** | 25 file/sec |\n\n| Package | 99th percentile | 95th percentile | 50th percentile |\n| ------------- | :-------------: | :------------------: | :------------------: |\n| [chardet](https://github.com/chardet/chardet) | 1115 ms | 300 ms | 27 ms |\n| charset-normalizer | 460 ms | 240 ms | 18 ms |\n\nChardet's performance on larger file (1MB+) are very poor. Expect huge difference on large payload.\n\n> Stats are generated using 400+ files using default parameters. More details on used files, see GHA workflows.\n> And yes, these results might change at any time. The dataset can be updated to include more files.\n> The actual delays heavily depends on your CPU capabilities. The factors should remain the same.\n\n[cchardet](https://github.com/PyYoshi/cChardet) is a non-native (cpp binding) and unmaintained faster alternative with \na better accuracy than chardet but lower than this package. If speed is the most important factor, you should try it.\n\n## \u2728 Installation\n\nUsing PyPi for latest stable\n```sh\npip install charset-normalizer -U\n```\n\nIf you want a more up-to-date `unicodedata` than the one available in your Python setup.\n```sh\npip install charset-normalizer[unicode_backport] -U\n```\n\n## \ud83d\ude80 Basic Usage\n\n### CLI\nThis package comes with a CLI.\n\n```\nusage: normalizer [-h] [-v] [-a] [-n] [-m] [-r] [-f] [-t THRESHOLD]\n file [file ...]\n\nThe Real First Universal Charset Detector. Discover originating encoding used\non text file. Normalize text to unicode.\n\npositional arguments:\n files File(s) to be analysed\n\noptional arguments:\n -h, --help show this help message and exit\n -v, --verbose Display complementary information about file if any.\n Stdout will contain logs about the detection process.\n -a, --with-alternative\n Output complementary possibilities if any. Top-level\n JSON WILL be a list.\n -n, --normalize Permit to normalize input file. If not set, program\n does not write anything.\n -m, --minimal Only output the charset detected to STDOUT. Disabling\n JSON output.\n -r, --replace Replace file when trying to normalize it instead of\n creating a new one.\n -f, --force Replace file without asking if you are sure, use this\n flag with caution.\n -t THRESHOLD, --threshold THRESHOLD\n Define a custom maximum amount of chaos allowed in\n decoded content. 0. <= chaos <= 1.\n --version Show version information and exit.\n```\n\n```bash\nnormalizer ./data/sample.1.fr.srt\n```\n\n:tada: Since version 1.4.0 the CLI produce easily usable stdout result in JSON format.\n\n```json\n{\n \"path\": \"/home/default/projects/charset_normalizer/data/sample.1.fr.srt\",\n \"encoding\": \"cp1252\",\n \"encoding_aliases\": [\n \"1252\",\n \"windows_1252\"\n ],\n \"alternative_encodings\": [\n \"cp1254\",\n \"cp1256\",\n \"cp1258\",\n \"iso8859_14\",\n \"iso8859_15\",\n \"iso8859_16\",\n \"iso8859_3\",\n \"iso8859_9\",\n \"latin_1\",\n \"mbcs\"\n ],\n \"language\": \"French\",\n \"alphabets\": [\n \"Basic Latin\",\n \"Latin-1 Supplement\"\n ],\n \"has_sig_or_bom\": false,\n \"chaos\": 0.149,\n \"coherence\": 97.152,\n \"unicode_path\": null,\n \"is_preferred\": true\n}\n```\n\n### Python\n*Just print out normalized text*\n```python\nfrom charset_normalizer import from_path\n\nresults = from_path('./my_subtitle.srt')\n\nprint(str(results.best()))\n```\n\n*Normalize any text file*\n```python\nfrom charset_normalizer import normalize\ntry:\n normalize('./my_subtitle.srt') # should write to disk my_subtitle-***.srt\nexcept IOError as e:\n print('Sadly, we are unable to perform charset normalization.', str(e))\n```\n\n*Upgrade your code without effort*\n```python\nfrom charset_normalizer import detect\n```\n\nThe above code will behave the same as **chardet**. We ensure that we offer the best (reasonable) BC result possible.\n\nSee the docs for advanced usage : [readthedocs.io](https://charset-normalizer.readthedocs.io/en/latest/)\n\n## \ud83d\ude07 Why\n\nWhen I started using Chardet, I noticed that it was not suited to my expectations, and I wanted to propose a\nreliable alternative using a completely different method. Also! I never back down on a good challenge!\n\nI **don't care** about the **originating charset** encoding, because **two different tables** can\nproduce **two identical rendered string.**\nWhat I want is to get readable text, the best I can. \n\nIn a way, **I'm brute forcing text decoding.** How cool is that ? \ud83d\ude0e\n\nDon't confuse package **ftfy** with charset-normalizer or chardet. ftfy goal is to repair unicode string whereas charset-normalizer to convert raw file in unknown encoding to unicode.\n\n## \ud83c\udf70 How\n\n - Discard all charset encoding table that could not fit the binary content.\n - Measure chaos, or the mess once opened (by chunks) with a corresponding charset encoding.\n - Extract matches with the lowest mess detected.\n - Additionally, we measure coherence / probe for a language.\n\n**Wait a minute**, what is chaos/mess and coherence according to **YOU ?**\n\n*Chaos :* I opened hundred of text files, **written by humans**, with the wrong encoding table. **I observed**, then\n**I established** some ground rules about **what is obvious** when **it seems like** a mess.\n I know that my interpretation of what is chaotic is very subjective, feel free to contribute in order to\n improve or rewrite it.\n\n*Coherence :* For each language there is on earth, we have computed ranked letter appearance occurrences (the best we can). So I thought\nthat intel is worth something here. So I use those records against decoded text to check if I can detect intelligent design.\n\n## \u26a1 Known limitations\n\n - Language detection is unreliable when text contains two or more languages sharing identical letters. (eg. HTML (english tags) + Turkish content (Sharing Latin characters))\n - Every charset detector heavily depends on sufficient content. In common cases, do not bother run detection on very tiny content.\n\n## \ud83d\udc64 Contributing\n\nContributions, issues and feature requests are very much welcome.
\nFeel free to check [issues page](https://github.com/ousret/charset_normalizer/issues) if you want to contribute.\n\n## \ud83d\udcdd License\n\nCopyright \u00a9 2019 [Ahmed TAHRI @Ousret](https://github.com/Ousret).
\nThis project is [MIT](https://github.com/Ousret/charset_normalizer/blob/master/LICENSE) licensed.\n\nCharacters frequencies used in this project \u00a9 2012 [Denny Vrande\u010di\u0107](http://simia.net/letters/)\n\n\n",
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