{
    "info": {
        "author": "The University of Iowa Internet Research Lab",
        "author_email": "john-cook@uiowa.edu",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
        ],
        "description": "\n# IRL Utilities\n# Installation\n## git\n\n```\ngit clone https://github.com/uiowa-irl/uiowa-irl-utils.git\ncd uiowa-irl-utils\npip install --user .\n```\n\n## pypi\n\n```\npip install irlutils\n``` \n\nimport the  module: \n\n```\nimport irlutils\n```\n\n\n# Documentation\n\n\n## file_utils\n```\nFUNCTIONS\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string . \n            root (str): top level folder to begin search from. \n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference: \n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs. \n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_unpacker(**kwargs)\n        unpacks tar to a tmp directory. \n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(file_pattern=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(file_pattern=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\nAUTHOR\n    senorchow\n\nFILE\n    irlutils/file/file_utils.py\n```\n## database_utils\n```\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    irlutils/url/crawl/database_utils.py\n```\n\n## domain_utils\n\n```\nFUNCTIONS\n    get_hostname(url)\n        strips out the hostname from a url\n\n    get_ps_plus_1(url, **kwargs)\n        Returns the PS+1 of the url. This will also return\n        an IP address if the hostname of the url is a valid\n        IP address.\n\n        An (optional) PublicSuffixList object can be passed with keyword arg 'psl',\n        otherwise a version cached in the system temp directory is used.\n\n    get_psl(location='public_suffix_list.dat')\n        Grabs an updated public suffix list.\n\n    get_stripped_query_string(url)\n\n    get_stripped_url(url, scheme=False)\n        Returns a url stripped to (scheme)?+hostname+path\n\n    get_stripped_urls(urls, scheme=False)\n        Returns a set (or list) of urls stripped to (scheme)?+hostname+path\n\n    hostname_subparts(url, include_ps=False, **kwargs)\n        Returns a list of slices of a url's hostname down to the PS+1\n\n        If `include_ps` is set, the hostname slices will include the public suffix\n\n        For example: http://a.b.c.d.com/path?query#frag would yield:\n            [a.b.c.d.com, b.c.d.com, c.d.com, d.com] if include_ps == False\n            [a.b.c.d.com, b.c.d.com, c.d.com, d.com, com] if include_ps == True\n\n        An (optional) PublicSuffixList object can be passed with keyword arg 'psl'.\n        otherwise a version cached in the system temp directory is used.\n\n    is_ip_address(hostname)\n        Check if the given string is a valid IP address\n\n    load_psl(function)\n\nDATA\n    PSL_CACHE_LOC = 'public_suffix_list.dat'\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    irlutils/url/crawl/domain_utils.py\n```\n\n## blocklist_utils\n\n```\nFUNCTIONS\n    get_option_dict(request)\n        Build an options dict for BlockListParser\n\n        Parameters\n        ----------\n        request : sqlite3.Row\n            A single HTTP request record pulled from OpenWPM's http_requests table\n        public_suffix_list : PublicSuffixList\n            An instance of PublicSuffixList()\n\n               BINARY_OPTIONS = [\n            \"script\",\n            \"image\",\n            \"stylesheet\",\n            \"object\",\n            \"xmlhttprequest\",\n            \"object-subrequest\",\n            \"subdocument\",\n            \"document\",\n            \"elemhide\",\n            \"other\",\n            \"background\",\n            \"xbl\",\n            \"ping\",\n            \"dtd\",\n            \"media\",\n            \"third-party\",\n            \"match-case\",\n            \"collapse\",\n            \"donottrack\",\n        ]\n\n        Returns\n        -------\n        dict\n            An \"options\" dictionary for use with BlockListParser\n            refs: [1] https://github.com/MoonchildProductions/UXP/blob/master/dom/base/nsIContentPolicyBase.idl\n                  [2] https://adblockplus.org/en/filters#options\n                  [3]\n\nFILE\n    irlutils/url/crawl/blocklist_utils.py\n```\n\n## analysis_utils\n\n```\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    irlutils/url/crawl/analysis_utils.py\n```\n\n## chi2_proportions\n\n```\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    irlutils/stats/tests/proportions/chi2_proportions.py\n```\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chownUser(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string . \n            root (str): top level folder to begin search from. \n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference: \n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs. \n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(self, d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory \n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>> \n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory. \n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(self, d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chownUser(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string . \n            root (str): top level folder to begin search from. \n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference: \n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs. \n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory \n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>> \n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory. \n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chownUser(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string . \n            root (str): top level folder to begin search from. \n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference: \n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs. \n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory \n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>> \n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory. \n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nDATA\n    DBG = <lcdk.lcdk.lcdk object>\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module chi2_proportions:\n\nNAME\n    chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. If this is \n            array_like, then the assumption is that this represents the number of successes \n            for each independent sample \n\n\n            nobs (:obj `list` of :obj`int` or a single `int`):  The number of trials or observations, with the same length as count. \n\n        Returns: \n            chi2  (:obj `float`): The test statistic.\n\n            p (:obj `float`): The p-value of the test\n\n            dof (int) : Degrees of freedom\n\n            expected (:obj `list`): list same shape as observed. The expected frequencies, based on the marginal sums of the table\n\n\n        References: \n        [1] \"scipy.stats.chi2_contingency\" https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.chi2_contingency.html\n        [2] \"statsmodels.stats.proportion.proportions_chisquare\"  https://www.statsmodels.org/dev/generated/statsmodels.stats.proportion.proportions_chisquare.html\n        [3] (1, 2) \u201cContingency table\u201d, https://en.wikipedia.org/wiki/Contingency_table\n        [4] (1, 2) \u201cPearson\u2019s chi-squared test\u201d, https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test\n        [5] (1, 2) Cressie, N. and Read, T. R. C., \u201cMultinomial Goodness-of-Fit Tests\u201d, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440-464.\n\n        Sample use: \n            input: \n            [10,10,20] - number of successes in trial \n            [20,20,20] - number of trials \n            chi2Proportions([10,10,20], [20,20,20])\n\n            output: \n            (2.7777777777777777,\n            0.24935220877729619,\n            2,\n            array([[ 12.,  12.,  16.],\n                [ 18.,  18.,  24.]]))\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/stats/tests/proportions/chi2_proportions.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nAUTHOR\n    johncook\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/file/file_utils.py\n\n\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in scripts\n\n        Args: \n            script_urls (list): A list of urls extracted from javascripts\n            du (list): A domain utilities instance\n\n        Returns:\n             psls(set): a set of tld+1(string)\n\n    get_set_of_script_urls_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack as a\n        string.\n\n    parse_headers(header)\n        parses http header into kv pairs\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             kv(dict): name value pairs of http headers\n\n    strip_scheme_www_and_query(url)\n        Remove the scheme and query section of a URL.\n\nDATA\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/url/crawl/analysis_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/url/crawl/database_utils.py\n\n\nHelp on module blocklist_utils:\n\nNAME\n    blocklist_utils\n\nFUNCTIONS\n    get_option_dict(request)\n        Build an options dict for BlockListParser\n\n        Parameters\n        ----------\n        request : sqlite3.Row\n            A single HTTP request record pulled from OpenWPM's http_requests table\n        public_suffix_list : PublicSuffixList\n            An instance of PublicSuffixList()\n\n               BINARY_OPTIONS = [\n            \"script\",\n            \"image\",\n            \"stylesheet\",\n            \"object\",\n            \"xmlhttprequest\",\n            \"object-subrequest\",\n            \"subdocument\",\n            \"document\",\n            \"elemhide\",\n            \"other\",\n            \"background\",\n            \"xbl\",\n            \"ping\",\n            \"dtd\",\n            \"media\",\n            \"third-party\",\n            \"match-case\",\n            \"collapse\",\n            \"donottrack\",\n        ]\n\n        Returns\n        -------\n        dict\n            An \"options\" dictionary for use with BlockListParser\n            refs: [1] https://github.com/MoonchildProductions/UXP/blob/master/dom/base/nsIContentPolicyBase.idl\n                  [2] https://adblockplus.org/en/filters#options\n                  [3]\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/url/crawl/blocklist_utils.py\n\n\nHelp on module domain_utils:\n\nNAME\n    domain_utils\n\nFUNCTIONS\n    get_hostname(url)\n        strips out the hostname from a url\n\n    get_ps_plus_1(url, **kwargs)\n        Returns the PS+1 of the url. This will also return\n        an IP address if the hostname of the url is a valid\n        IP address.\n\n        An (optional) PublicSuffixList object can be passed with keyword arg 'psl',\n        otherwise a version cached in the system temp directory is used.\n\n    get_psl(location='public_suffix_list.dat')\n        Grabs an updated public suffix list.\n\n    get_stripped_query_string(url)\n\n    get_stripped_url(url, scheme=False)\n        Returns a url stripped to (scheme)?+hostname+path\n\n    get_stripped_urls(urls, scheme=False)\n        Returns a set (or list) of urls stripped to (scheme)?+hostname+path\n\n    hostname_subparts(url, include_ps=False, **kwargs)\n        Returns a list of slices of a url's hostname down to the PS+1\n\n        If `include_ps` is set, the hostname slices will include the public suffix\n\n        For example: http://a.b.c.d.com/path?query#frag would yield:\n            [a.b.c.d.com, b.c.d.com, c.d.com, d.com] if include_ps == False\n            [a.b.c.d.com, b.c.d.com, c.d.com, d.com, com] if include_ps == True\n\n        An (optional) PublicSuffixList object can be passed with keyword arg 'psl'.\n        otherwise a version cached in the system temp directory is used.\n\n    is_ip_address(hostname)\n        Check if the given string is a valid IP address\n\n    load_psl(function)\n\nDATA\n    PSL_CACHE_LOC = 'public_suffix_list.dat'\n    absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0...\n    print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0)...\n\nFILE\n    /home/john/git/uiowa-irl/uiowa-irl-utils/irlutils/irlutils/url/crawl/domain_utils.py\n\n\nHelp on module file_utils:\n\nNAME\n    file_utils\n\nFUNCTIONS\n    chmod(path, mode=777, recursive=False)\n\n    chown(path, recursive=False, owner='user', group='user')\n\n    compress_path(path)\n\n    cp(s, d)\n\n    file_ext(path, **kwargs)\n        file extension finder\n        kwargs:\n            path (str): path or file name\n        Returns:\n            dotted file extension of a file\n        Examples:\n\n            >>> file_ext('/path/to_file/with_ext/test.py')\n                .py\n\n    gen_find_files(**kwargs)\n        returns filenames that matches the given pattern under() a given dir\n\n\n        Kwargs:\n            file_pattern (str): a regex style string .\n            root (str): top level folder to begin search from.\n\n        Yields:\n            path (generator): matching path str\n\n        Examples:\n            gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).\n\n            >>> gen_find_files(file_pattern=\"*.sql\", root=\"/mnt/data/).__next__()\n            /mnt/data/first_folder/last_folder/file.sqlite\n\n        Reference:\n            [1] http://www.dabeaz.com/generators/\n\n    json_flatten(y)\n        flattens nested structures within a json file\n\n\n        Kwargs:\n\n            data (dict): data from nested dictionary\n            kv (dict): dictionary containing key,value pairs.\n\n        returns:\n\n            kv (dict): a dictionary object containing flattened structures\n\n        Examples:\n            data = {'k1':{'kv1':['v1', 'v2'], 'kv2': 'v3'}}\n\n            >>> json_flatten(data)\n                {'k1_kv1_0': 'v1', 'k1_kv1_1': 'v2', 'k1_kv2': 'v3'}\n\n    mkdir(d, mode=511, exist_ok=True)\n\n    mv(s, d)\n\n    rm(d)\n\n    rmsubtree(**kwargs)\n        Clears all subfolders and files in location\n        kwargs:\n            location (str): target directory to remove\n        Examples:\n\n            >>> rmsubtree(location=\"/path/to/target_dir\").\n\n    tar_packer(tar_dir, **kwargs)\n        tars up  directory\n\n\n        Kwargs:\n\n            dir (str): top level dir\n            compression (bool): compression type. gz, xz supported now\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tar_path (generator): path to tar file\n\n        Examples:\n\n            tar_packer(dir=\"/path/to/top_level_dir\", [compression=gz|xz]\n\n            >>>\n                /tmp/FZ4245_Zb/top_level_dir.tar\n\n    tar_unpacker(tar_path, **kwargs)\n        unpacks tar to a tmp directory.\n\n\n        Kwargs:\n\n            tar_path (str): tar file path\n            versbose (bool): True enables verbose\n\n        returns:\n\n            tmp_path (generator): extracted contents path\n\n        Examples:\n\n            tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n\n            >>> tar_unpacker(tar_path=\"/mnt/data/tarfile.tar.gz\").\n            /tmp/FZ4245_Zb/\n\n    touch(d)\n\nAUTHOR\n    johncook\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/file/file_utils.py\n\n\nHelp on module database_utils:\n\nNAME\n    database_utils\n\nFUNCTIONS\n    build_index(cursor, column, tables)\n        Build an index on `column` for each table in `tables`\n\n    drop_tables(sqlite_con, tables=[])\n\n    fetchiter(cursor, arraysize=10000)\n        Generator for cursor results\n\n    get_channel_content(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_channel_content_with_hash(visit_id, channel_id, sqlite_cur, ldb_con, beautify=True)\n        Return javascript content for given channel_id.\n        Parameters\n        ----------\n        visit_id : int\n            `visit_id` of the page visit where this URL was loaded\n        channel_id : string\n            `channel_id` to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n\n    get_content(db, content_hash, compression='snappy', beautify=True)\n        Returns decompressed content from javascript leveldb database\n\n    get_ldb_content(ldb_addr, content_hash)\n\n    get_leveldb(db_path, compression='snappy')\n        Returns an open handle for a leveldb database\n        with proper configuration settings.\n\n    get_url_content(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    get_url_content_with_hash(url, sqlite_cur, ldb_con, beautify=True, visit_id=None)\n        Return javascript content for given url.\n        Parameters\n        ----------\n        url : string\n            url to search content hash for\n        sqlite_cur : sqlite3.Cursor\n            cursor for crawl database\n        ldb_con : plyvel.DB\n            leveldb database storing javascript content\n        beautify : boolean\n            Control weather or not to beautify output\n        visit_id : int\n            (optional) `visit_id` of the page visit where this URL was loaded\n\n    list_placeholder(length, is_pg=False)\n        Returns a (?,?,?,?...) string of the desired length\n\n    optimize_db(cursor)\n        Set options to make sqlite more efficient on a high memory machine\n\nFILE\n    /Users/johncook/git/uiowa-irl-utils/irlutils/url/crawl/database_utils.py\n\n\nproblem in irlutils/url/crawl/domain_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nproblem in irlutils/url/crawl/blocklist_utils.py - ModuleNotFoundError: No module named 'publicsuffix2'\nHelp on module analysis_utils:\n\nNAME\n    analysis_utils\n\nFUNCTIONS\n    add_col_bare_script_url(js_df)\n        Add a col for script URL without scheme, www and query.\n\n    add_col_set_of_script_ps1s_from_call_stack(js_df)\n        map psls to call stack in scripts\n\n        Args: \n            js_df (pandas dataFrame): javascript table\n\n    add_col_set_of_script_urls_from_call_stack(js_df)\n\n    add_col_unix_timestamp(df)\n\n    datetime_from_iso(iso_date)\n        Convert from ISO.\n\n    get_cookie(headers)\n        A special case of parse headers that extracts only the cookie. \n\n        Args: \n            headers (list): http request headers\n\n        Returns:\n\n            item(string): name value pairs of a cookie\n\n    get_func_and_script_url_from_initiator(initiator)\n        Remove line number and column number from the initiator.\n\n    get_host_from_url(url)\n\n    get_initiator_from_call_stack(call_stack)\n        Return the bottom element of the call stack.\n\n    get_initiator_from_req_call_stack(req_call_stack)\n        Return the bottom element of a request call stack.\n        Request call stacks have an extra field (async_cause) at the end.\n\n    get_requests_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http requests\n\n    get_responses_from_visits(con, visit_ids)\n        Extact http requests matching visit_ids\n\n        Args: \n            con (sqlite3.connection): A connection to a sqlite data base\n            visit_ids (list): A list of ids for from each web visit\n\n        Returns:\n             df(pandas DataFrame): A table containing visits that conincide with http responses\n\n    get_script_url_from_initiator(initiator)\n        Remove the scheme and query section of a URL.\n\n    get_script_urls_from_call_stack_as_set(call_stack)\n        Return the urls of the scripts involved in the call stack as a set.\n\n    get_set_cookie(header)\n        A special case of parse headers that returns 'Set-Cookies'\n\n        Args: \n            headers (string): http request headers\n\n        Returns:\n             item(string): name value pairs of Set Cookie field\n\n    get_set_of_script_hosts_from_call_stack(call_stack)\n        Return the urls of the scripts involved in the call stack.\n\n    get_set_of_script_ps1s_from_call_stack(script_urls, du)\n        extract a unique set of urls from a list of urls detected in 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chi2_proportions\n\nFUNCTIONS\n    chi2Proportions(count, nobs)\n        A wrapper for the chi2 testing proportions based upon the chi-square test\n\n        Args:\n            count (:obj `list` of :obj`int` or a single `int`):  the number of successes in nobs trials. 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