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"description": "\n# Young Tools\n\nThis package contains several useful tools, some of which deal with the problems in Natrual Language Processing.\n\n## Installation\n\n1. Through pip\n```\npip install young-tools\n```\n\n2. Clone it to local\n```\ngit clone https://github.com/Jason-Young-NLP/YoungTools.git\ncd YoungTools\npython setup.py build develop\n```\n\n## Main Framework\n\n* [Pedestal Modules](#PedestalModules)\n* [Executable Modules](#ExecutableModuels)\n * [Compilers](#Compilers)\n * [Metrics](#Metrics)\n\n\n\n## Executable Moduels\nAll the executable modules can be executed by running command `young-tools-{module_name}`.\n\nUntil now, young-tools provides three Executable Moduels:\n * young-tools-corpus\n * young-tools-levenshtein\n * young-tools-xml\n\n\n### Compilers\n\n#### Corpus\nIt is a corpus compiler which can be executed by running `young-tools-corpus`. The command only recieve 1 argument `-p` or `--configuration-path` that contains all the parameters you set. The configuration file is wrote in a basic configuration language which provides a structure similar to what\u2019s found in Microsoft Windows INI files.\n\nYou must provide the `main` section in which you should to configure:\n * `pipeline`\n * `corpus_directory`\n * `corpora_names`\n * `languages`\n * `encodings`\n\nBefore each running, `young-tools-corpus` will read the `configuration-path` and parse the `main` section. `young-tools-corpus` can deal with multiple corpus with different settings in one time. The configuration of different corpus in `main` section are seperated by seperator `|`.\n\n`pipeline` indicates the running order of the sub-corpus-compiler modules. Each name of different modules are seperated by the seperator `&`. If there is another instance of a module have a different configuration, just define a new section whitch name is appended by the suffix `_{index}` like `moduel_name_10`. module_name must be one of names of sub-corpus-compiler-modules.\n\n`corpus_directory` specifies where the raw and compiled corpus are.\n\nIn each `corpus_directory`, there may contains several corpora(`corpora_names`), and each corpora may have several languages(`languages`) whose compiled file encodings can be detemained by `encodings`.\n\n\n`young-tools-corpus` has 5 **sub-corpus-compiler-modules**:\n 1. **Cleaner**\n\n Which can remove the dumplicate_lines(`remove_dumplicate_lines`) and lowercase the corpora(`lowercase`).\n `granularity` can be set as *sentence* or *document*. When `granularity` is *document*, the document index which indicates the start point of each document in the corpora are write the `corpora_names`+`document_index_suffix`.\n 2. **Normalizer**\n\n Normalize punctuations of the corpora.\n\n 3. **Segmenter**\n\n Segment the Chinese sentence using [THULAC](https://github.com/thunlp/THULAC-Python). If you need POS tagging, set `part_of_speech_tagging` to be true. `traditional_to_simplified` may useful in some situation.\n\n 4. **Tokenizer**\n\n Tokenize the sentences in different languages, you may need to convert the hyphen `-` char to `@-@` by setting `split_aggressive_hyphen` to be True.\n\n 5. **Subword**\n\n This is a simple encapsulation of [subword-nmt](https://github.com/rsennrich/subword-nmt). `learn_file_index` and `apply_file_indices` indicate the index of which corpus should be learn/apply in the `corpora_names`, and `subword_indices` indicates which language of the corpora should be executed by BPE. `symbols_number` is the number of the merge operation and `joint_learn` is whether learn the BPE jointly among the `subword_indices` at `learn_file_index` of the `corpora_names`.\n\n**Normalizer** and **Tokenizer** are reimplementation of the scripts of the [mosesdecoder](https://github.com/moses-smt/mosesdecoder).\n\n#### Leveshtein\nIt can generate the manipulation sequences between corpora hypothesis and references by calculating the levenshtein distance , and synthetise the hypothesis of the references by getting the rules of the aligned hypothesis and references. These functions can be executed by running `young-tools-corpus` with a subcommand of `get-rules`, `apply-rules` and `gen-seqs`.\n\n#### XML\n`young-tools-xml` can convert a XML file into a plain file or escape/deescape the file by specifing the subcommand as `xml2plain` or `scape` respectively.\n\n\n### Metrics\nTo be done.\n\n\n\n## Pedestal Moduels\nUsing it by simply import the `pedestal` package:\n\n```\nimport young_tools.pedestal as pedestal\n```\n\nThe usage of each module in the `pedestal` package is described as follows:\n\n##### Timer\nTimer record the system/process elapsed time.\n\n##### Constant\nConstant is a type of class with which stores unlimited number of constants.\n\n##### InstancesChecker\nInstancesChecker is a basic decorator that can check whether parameters that are passed to the method is legal.\n\n##### ANSIFormatter\nANSIFormatter controls the ANSI color string. One use this class to format the terminal output string.\n\n##### Logger\nLogger records the logging of the process and sends it to log file or terminal.\n\n##### Argument\nArgument is a simple encapsulation of the argparser.\n\n##### Configurator\nConfigurator is a simple encapsulation of the configparser, but Configurator is case *sensitive*.\n\n##### UnicodeHandler\nUnicodeHandler has several methods that deal with the unicode string and detect the encoding type.\n\n##### RedirectStream\nA simple class can redirect the stdout/stderr stream to a file.\n\n\n",
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