{
    "info": {
        "author": "Antonio Su\u00e1rez Jim\u00e9nez",
        "author_email": "pherkad13@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: System Administrators",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Programming Language :: Python :: 3",
            "Topic :: Utilities"
        ],
        "description": "Pysaurio\n========\n\nThis package contains two tools: Raptor & Reptar\n\nRaptor\n------\n\n**Raptor** for extracting and displaying information from a set of files of the same type; and creating a single file with all the selected information.\n\nThe information in the files may be in multiple rows::\n\n    PC01.txt:\n    User=ms123\n    Name=Mayra Sanz\n    OS=GNU/Linux\n    IP=10.226.140.1\n\nBut, also, the information may be in several columns. It is possible to read data from multiple fields in a single line::\n\n    PC01.log:\n    User: ms123     Name: Mayra Sanz\n    OS: GNU/Linux   IP: 10.226.140.1        \n\n**Example:** data from the following files::\n\n    PC01.txt:\n    User=ms123\n    Name=Mayra Sanz\n    OS=GNU/Linux\n    IP=10.226.140.1\n\n    PC02.txt:\n    User=lt001\n    Name=Luis Toribio\n    OS=GNU/Linux\n    IP=10.226.140.2\n\n    PC03.txt:\n    User=co205\n    Name=Clara Osto\n    OS=Win\n    IP=10.226.140.3\n\n... You can create a CSV file with the following information::\n\n    users.csv:\n    User,Name,OS,IP\n    MS123,Mayra Sanz,GNU/linux,10.226.140.1\n    LT001,Luis Toribio,GNU/linux,10.226.140.2\n    CO205,Clara Osto,Win,10.226.140.3\n\nTo achieve this you need to create a template (.rap) with Raptor, which is similar to an INI file with the following information::\n\n    users.rap:\n    [General]\n    description = Get list of users\n    extension = txt\n    prefix = PC\n    output_folder = txt\n    input_folder = txt\n    output_file = users.csv\n    delimiter = ,\n    quotechar = \"\n    include_header = 1\n    include_file = 0\n    include_record_num = 0\n    include_empty_record = 0    \n    search_multiple = 0\n    alternate_header =\n    search_multiple = 0\n\n    [Fields]\n    user = User=\n    name = Name=\n    os = OS=\n    ip = IP=\n\n    [Rules]\n    rule1 = ('user', 'UPPER')                                       \n\nTo create .rap template (If the .rap template exists it is not saved). (Caution: field names must be lowercase)::\n\n    from pysaurio import Raptor  \n    rap1 = Raptor()       \n    rap1.description = 'Get list of users'\n    rap1.extension = 'txt'\n    rap1.prefix = 'PC'\n    rap1.input_folder = 'txt'\n    rap1.output_folder = 'txt'\n    rap1.output_file = 'users.csv'\n    rap1.delimiter = ','\n    rap1.quotechar = '\"'\n    rap1.include_header = '1'\n    rap1.include_file = '1'\n    rap1.include_record_num = '1'\n    rap1.include_empty_record = '0'\n    rap1.search_multiple = '0'\n    rap1.alternate_header = ''\n    rap1.fields['user'] = 'User='\n    rap1.fields['name'] = 'Name='\n    rap1.fields['os'] = 'OS='\n    rap1.fields['ip'] = 'IP='\n    rap1.rules.append(('user', 'UPPER'))\n    rap1.rules.append(('name', 'REMOVEFROM', ' '))     \n    rap1.Save(\"users.rap\")  \n    del rap1\n\n\n**Attribute List:**\n\n- description: short descripton of .rap template\n- extension: extension of the files to read\n- prefix: files must begin with this string\n- input_folder: folder of files to read\n- output_folder: output folder to save file with result\n- output_file: output filename\n- delimiter: delimiter character\n- quotechar: quote character\n- include_header: '0' or '1'\n- include_file: '0' or '1'\n- inclide_file_datetime: '0' or '1' (file creation & modification date/time)\n- include_record_num: '0' or '1'\n- include_empty_record: '0' or '1'\n- search_multiple: '0' or '1'\n- alternate_header: alternative text of the report header\n- fields: dictionary with fieldnames and search string (read template)\n- record: dictionary with fieldnames and values (read template)\n- rules: list of rules (read template)\n- list_files: list of filenames to read (auto)\n- record_counter: number of records (auto) \n- errors: list of errors (auto)\n- number_errors: number of errors after you open or save a template                 \n\n**Functions available for rules:**\n\n- rule1 = (fieldname, 'SUBSTR', postion_initial, lenght)\n- rule1 = (fieldname, 'REPLACE', 'search_string', 'replace_string')\n- rule1 = (fieldname, 'REPLACEALL', 'search_string', 'replace_string')\n- rule1 = (fieldname, 'UPPER')\n- rule1 = (fieldname, 'LOWER')\n- rule1 = (fieldname, 'REVERSE')\n- rule1 = (fieldname, 'REMOVE')\n- rule1 = (fieldname, 'FIELDISDATA')\n- rule1 = (fieldname, 'REMOVEFROM', 'string')\n- rule1 = (fieldname, 'REMOVETO', 'string')\n\nOpens template (.rap) and creates (.csv) file from the data read from multiple text files::\n\n    from pysaurio import Raptor\n    import csv\n\n    rap2 = Raptor()\n    rap2.Open('users.rap')\n    if rap2.number_errors == 0:         \n        file_csv = open(rap2.output_file, 'w', newline='')\n        csv_output = csv.writer(file_csv, \n                                delimiter=rap2.delimiter,\n                                quotechar=rap2.quotechar, \n                                quoting=csv.QUOTE_MINIMAL)\n        if rap2.include_header == '1':\n            fields_list = rap2.BuildHeader()\n            print(fields_list)\n            csv_output.writerow(fields_list)\n\n        for row in rap2.list_files:\n            valid_record, new_record = rap2.BuildRow(row)\n            new_record = rap2.ApplyRules(new_record)\n            if valid_record:\n                new_record = list(new_record.values())\n                print(new_record)\n                csv_output.writerow(new_record)         \n        file_csv.close()            \n    else:\n        print(rap2.ShowError())\n    del rap2\n\n\nReptar\n------\n\n**Reptar** allows merge files, including only the necessary lines.\n\n**Example:** data from the following files::\n\n    PCS01.txt:\n    User,Name,OS,IP\n    ms123,Mayra Sanz,GNU/Linux,10.226.140.1\n    lt001,Luis Toribio,GNU/Linux,10.226.140.2\n    co205,Clara Osto,Win,10.226.140.3\n\n    PCS02.txt:\n    User,Name,OS,IP\n    nn345,Nadia Pacheco,Win,10.226.140.4\n    jm401,Juan Madrid,GNU/Linux,10.226.140.5\n\n... You can create a file with the following information::\n\n    Linux.csv:\n    User,Name,OS,IP\n    MS124,MAYRA SANZ,GNU/LINUX,10.226.140.1\n    LT001,LUIS TORIBIO,GNU/LINUX,10.226.140.2\n    CO205,CLARA OSTO,WIN,10.226.140.3\n    JM401,JUAN MADRID,GNU/LINUX,10.226.140.5\n\nIn this example, lines that contain the text \"Linux\" or beginning with the text \"co205\" are included::\n\n    from pysaurio import Reptar\n    rep1 = Reptar()       \n    rep1.description = 'Get list of Linux users'\n    rep1.extension = 'txt'\n    rep1.prefix = 'PCS'\n    rep1.input_folder = 'txt'\n    rep1.output_folder = 'txt'\n    rep1.output_file = 'Linux.csv'\n    rep1.include_header = '1'\n    rep1.include_file = '0'\n    rep1.include_record_num = '0'\n    rep1.alternate_header = ''\n    rep1.lines.append(('INCLUDE', 'Linux'))\n    rep1.lines.append(('INCLUDRE', '^co205'))\n    rep1.rules.append(('line', 'UPPER'))            \n    rep1.Save(\"linux.rep\")\n    del rep1\n\n    # Opens .rep template and create file with output information\n\n    rep2 = Reptar()\n    rep2.Open('linux.rep')\n    if rep2.number_errors == 0:         \n        file_csv = open(rep2.output_file, 'w')\n        if rep2.include_header == '1':\n            header = rep2.BuildHeader(rep2.list_files[0])\n            print(header)\n            file_csv.write(header + '\\n')\n\n        for row in rep2.list_files:\n            current_file = open(rep2.input_folder + row, 'rb')\n            while True:\n                new_record = current_file.readline()\n                new_record = new_record.decode(\"utf-8\", \"ignore\")\n                if not new_record: break\n                valid_record, new_record = rep2.BuildRow(new_record, row)\n                if valid_record:\n                    new_record = rep2.ApplyRules(new_record)\n                    print(new_record)\n                    file_csv.write(new_record + '\\n')\n            current_file.close()\n        file_csv.close()            \n    else:\n        print(rep2.ShowError())\n    del rep2\n\n\n**Functions available for including and excluding lines:**\n\n- line1 = ('EXCLUDE', 'string')\n- line1 = ('INCLUDE', 'string')\n- line1 = ('EXCLUDEND', 'string')\n- line1 = ('INCLUDEND', 'string')\n- line1 = ('EXCLUDRE', 'regex', '0'|'1')  # '1' not case sensitive\n- line1 = ('INCLUDRE', 'regex', '0'|'1')  # (See module re)\n\nThe package contains more examples and data files to test.\n\nChangelog\n---------\n\n- Pysaurio 0.2.6 - 2018-09-14 - Corrected error in function REMOVECOL\n- Pysaurio 0.2.5 - 2016-09-09 - new attribute: include_file_datetime = '0' or '1'\n- Pysaurio 0.2.4 - Reptar include new rule: 'REMOVECOL', remove column\n- Pysaurio 0.2.3 - New functions: 'INCLUDEND' and 'EXCLUDEND'\n- Pysaurio 0.2.2 - New argument in the 'INCLUDRE' and 'EXCLUDRE' functions\n- Pysaurio 0.2.1 - Reptar includes rules and the section 'Lines' you can use regular expressions.\n- Pysaurio 0.2.0 - Initial release (continued \"Pyraptor\").\n\n\n",
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        "keywords": "pysaurio search extract text csv collect data merge join pyraptor",
        "license": "GNU GPLv3",
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        "name": "pysaurio",
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