| #!/usr/bin/env python |
| |
| r""" |
| Define variable manipulation functions. |
| """ |
| |
| import os |
| import re |
| |
| try: |
| from robot.utils import DotDict |
| except ImportError: |
| pass |
| |
| import collections |
| |
| import gen_print as gp |
| import gen_misc as gm |
| import func_args as fa |
| |
| |
| def create_var_dict(*args): |
| r""" |
| Create a dictionary whose keys/values are the arg names/arg values passed |
| to it and return it to the caller. |
| |
| Note: The resulting dictionary will be ordered. |
| |
| Description of argument(s): |
| *args An unlimited number of arguments to be processed. |
| |
| Example use: |
| |
| first_name = 'Steve' |
| last_name = 'Smith' |
| var_dict = create_var_dict(first_name, last_name) |
| |
| gp.print_var(var_dict) |
| |
| The print-out of the resulting var dictionary is: |
| var_dict: |
| var_dict[first_name]: Steve |
| var_dict[last_name]: Smith |
| """ |
| |
| try: |
| result_dict = collections.OrderedDict() |
| except AttributeError: |
| result_dict = DotDict() |
| |
| arg_num = 1 |
| for arg in args: |
| arg_name = gp.get_arg_name(None, arg_num, stack_frame_ix=2) |
| result_dict[arg_name] = arg |
| arg_num += 1 |
| |
| return result_dict |
| |
| |
| default_record_delim = ':' |
| default_key_val_delim = '.' |
| |
| |
| def join_dict(dict, |
| record_delim=default_record_delim, |
| key_val_delim=default_key_val_delim): |
| r""" |
| Join a dictionary's keys and values into a string and return the string. |
| |
| Description of argument(s): |
| dict The dictionary whose keys and values are |
| to be joined. |
| record_delim The delimiter to be used to separate |
| dictionary pairs in the resulting string. |
| key_val_delim The delimiter to be used to separate keys |
| from values in the resulting string. |
| |
| Example use: |
| |
| gp.print_var(var_dict) |
| str1 = join_dict(var_dict) |
| gp.print_var(str1) |
| |
| Program output. |
| var_dict: |
| var_dict[first_name]: Steve |
| var_dict[last_name]: Smith |
| str1: |
| first_name.Steve:last_name.Smith |
| """ |
| |
| format_str = '%s' + key_val_delim + '%s' |
| return record_delim.join([format_str % (key, value) for (key, value) in |
| dict.items()]) |
| |
| |
| def split_to_dict(string, |
| record_delim=default_record_delim, |
| key_val_delim=default_key_val_delim): |
| r""" |
| Split a string into a dictionary and return it. |
| |
| This function is the complement to join_dict. |
| |
| Description of argument(s): |
| string The string to be split into a dictionary. |
| The string must have the proper delimiters |
| in it. A string created by join_dict |
| would qualify. |
| record_delim The delimiter to be used to separate |
| dictionary pairs in the input string. |
| key_val_delim The delimiter to be used to separate |
| keys/values in the input string. |
| |
| Example use: |
| |
| gp.print_var(str1) |
| new_dict = split_to_dict(str1) |
| gp.print_var(new_dict) |
| |
| |
| Program output. |
| str1: |
| first_name.Steve:last_name.Smith |
| new_dict: |
| new_dict[first_name]: Steve |
| new_dict[last_name]: Smith |
| """ |
| |
| try: |
| result_dict = collections.OrderedDict() |
| except AttributeError: |
| result_dict = DotDict() |
| |
| raw_keys_values = string.split(record_delim) |
| for key_value in raw_keys_values: |
| key_value_list = key_value.split(key_val_delim) |
| try: |
| result_dict[key_value_list[0]] = key_value_list[1] |
| except IndexError: |
| result_dict[key_value_list[0]] = "" |
| |
| return result_dict |
| |
| |
| def create_file_path(file_name_dict, |
| dir_path="/tmp/", |
| file_suffix=""): |
| r""" |
| Create a file path using the given parameters and return it. |
| |
| Description of argument(s): |
| file_name_dict A dictionary with keys/values which are to |
| appear as part of the file name. |
| dir_path The dir_path that is to appear as part of |
| the file name. |
| file_suffix A suffix to be included as part of the |
| file name. |
| """ |
| |
| dir_path = gm.add_trailing_slash(dir_path) |
| return dir_path + join_dict(file_name_dict) + file_suffix |
| |
| |
| def parse_file_path(file_path): |
| r""" |
| Parse a file path created by create_file_path and return the result as a |
| dictionary. |
| |
| This function is the complement to create_file_path. |
| |
| Description of argument(s): |
| file_path The file_path. |
| |
| Example use: |
| gp.print_var(boot_results_file_path) |
| file_path_data = parse_file_path(boot_results_file_path) |
| gp.print_var(file_path_data) |
| |
| Program output. |
| |
| boot_results_file_path: |
| /tmp/pgm_name.obmc_boot_test:openbmc_nickname.beye6:master_pid.2039:boot_re |
| sults |
| file_path_data: |
| file_path_data[dir_path]: /tmp/ |
| file_path_data[pgm_name]: obmc_boot_test |
| file_path_data[openbmc_nickname]: beye6 |
| file_path_data[master_pid]: 2039 |
| file_path_data[boot_results]: |
| """ |
| |
| try: |
| result_dict = collections.OrderedDict() |
| except AttributeError: |
| result_dict = DotDict() |
| |
| dir_path = os.path.dirname(file_path) + os.sep |
| file_path = os.path.basename(file_path) |
| |
| result_dict['dir_path'] = dir_path |
| |
| result_dict.update(split_to_dict(file_path)) |
| |
| return result_dict |
| |
| |
| def parse_key_value(string, |
| delim=":", |
| strip=" ", |
| to_lower=1, |
| underscores=1): |
| r""" |
| Parse a key/value string and return as a key/value tuple. |
| |
| This function is useful for parsing a line of program output or data that |
| is in the following form: |
| <key or variable name><delimiter><value> |
| |
| An example of a key/value string would be as follows: |
| |
| Current Limit State: No Active Power Limit |
| |
| In the example shown, the delimiter is ":". The resulting key would be as |
| follows: |
| Current Limit State |
| |
| Note: If one were to take the default values of to_lower=1 and |
| underscores=1, the resulting key would be as follows: |
| current_limit_state |
| |
| The to_lower and underscores arguments are provided for those who wish to |
| have their key names have the look and feel of python variable names. |
| |
| The resulting value for the example above would be as follows: |
| No Active Power Limit |
| |
| Another example: |
| name=Mike |
| |
| In this case, the delim would be "=", the key is "name" and the value is |
| "Mike". |
| |
| Description of argument(s): |
| string The string to be parsed. |
| delim The delimiter which separates the key from |
| the value. |
| strip The characters (if any) to strip from the |
| beginning and end of both the key and the |
| value. |
| to_lower Change the key name to lower case. |
| underscores Change any blanks found in the key name to |
| underscores. |
| """ |
| |
| pair = string.split(delim) |
| |
| key = pair[0].strip(strip) |
| if len(pair) == 0: |
| value = "" |
| else: |
| value = delim.join(pair[1:]).strip(strip) |
| |
| if to_lower: |
| key = key.lower() |
| if underscores: |
| key = re.sub(r" ", "_", key) |
| |
| return key, value |
| |
| |
| def key_value_list_to_dict(list, |
| process_indent=0, |
| **args): |
| r""" |
| Convert a list containing key/value strings or tuples to a dictionary and |
| return it. |
| |
| See docstring of parse_key_value function for details on key/value strings. |
| |
| Example usage: |
| |
| For the following value of list: |
| |
| list: |
| list[0]: Current Limit State: No Active Power Limit |
| list[1]: Exception actions: Hard Power Off & Log Event to SEL |
| list[2]: Power Limit: 0 Watts |
| list[3]: Correction time: 0 milliseconds |
| list[4]: Sampling period: 0 seconds |
| |
| And the following call in python: |
| |
| power_limit = key_value_outbuf_to_dict(list) |
| |
| The resulting power_limit directory would look like this: |
| |
| power_limit: |
| [current_limit_state]: No Active Power Limit |
| [exception_actions]: Hard Power Off & Log Event to SEL |
| [power_limit]: 0 Watts |
| [correction_time]: 0 milliseconds |
| [sampling_period]: 0 seconds |
| |
| For the following list: |
| |
| headers: |
| headers[0]: |
| headers[0][0]: content-length |
| headers[0][1]: 559 |
| headers[1]: |
| headers[1][0]: x-xss-protection |
| headers[1][1]: 1; mode=block |
| |
| And the following call in python: |
| |
| headers_dict = key_value_list_to_dict(headers) |
| |
| The resulting headers_dict would look like this: |
| |
| headers_dict: |
| [content-length]: 559 |
| [x-xss-protection]: 1; mode=block |
| |
| Another example containing a sub-list (see process_indent description |
| below): |
| |
| Provides Device SDRs : yes |
| Additional Device Support : |
| Sensor Device |
| SEL Device |
| FRU Inventory Device |
| Chassis Device |
| |
| Note that the 2 qualifications for containing a sub-list are met: 1) |
| 'Additional Device Support' has no value and 2) The entries below it are |
| indented. In this case those entries contain no delimiters (":") so they |
| will be processed as a list rather than as a dictionary. The result would |
| be as follows: |
| |
| mc_info: |
| mc_info[provides_device_sdrs]: yes |
| mc_info[additional_device_support]: |
| mc_info[additional_device_support][0]: Sensor Device |
| mc_info[additional_device_support][1]: SEL Device |
| mc_info[additional_device_support][2]: FRU Inventory Device |
| mc_info[additional_device_support][3]: Chassis Device |
| |
| Description of argument(s): |
| list A list of key/value strings. (See |
| docstring of parse_key_value function for |
| details). |
| process_indent This indicates that indented |
| sub-dictionaries and sub-lists are to be |
| processed as such. An entry may have a |
| sub-dict or sub-list if 1) It has no value |
| other than blank 2) There are entries |
| below it that are indented. Note that |
| process_indent is not allowed for a list |
| of tuples (vs. a list of key/value |
| strings). |
| **args Arguments to be interpreted by |
| parse_key_value. (See docstring of |
| parse_key_value function for details). |
| """ |
| |
| try: |
| result_dict = collections.OrderedDict() |
| except AttributeError: |
| result_dict = DotDict() |
| |
| if not process_indent: |
| for entry in list: |
| if type(entry) is tuple: |
| key, value = entry |
| else: |
| key, value = parse_key_value(entry, **args) |
| result_dict[key] = value |
| return result_dict |
| |
| # Process list while paying heed to indentation. |
| delim = args.get("delim", ":") |
| # Initialize "parent_" indentation level variables. |
| parent_indent = len(list[0]) - len(list[0].lstrip()) |
| sub_list = [] |
| for entry in list: |
| key, value = parse_key_value(entry, **args) |
| |
| indent = len(entry) - len(entry.lstrip()) |
| |
| if indent > parent_indent and parent_value == "": |
| # This line is indented compared to the parent entry and the |
| # parent entry has no value. |
| # Append the entry to sub_list for later processing. |
| sub_list.append(str(entry)) |
| continue |
| |
| # Process any outstanding sub_list and add it to |
| # result_dict[parent_key]. |
| if len(sub_list) > 0: |
| if any(delim in word for word in sub_list): |
| # If delim is found anywhere in the sub_list, we'll process |
| # as a sub-dictionary. |
| result_dict[parent_key] = key_value_list_to_dict(sub_list, |
| **args) |
| else: |
| result_dict[parent_key] = map(str.strip, sub_list) |
| del sub_list[:] |
| |
| result_dict[key] = value |
| |
| parent_key = key |
| parent_value = value |
| parent_indent = indent |
| |
| # Any outstanding sub_list to be processed? |
| if len(sub_list) > 0: |
| if any(delim in word for word in sub_list): |
| # If delim is found anywhere in the sub_list, we'll process as a |
| # sub-dictionary. |
| result_dict[parent_key] = key_value_list_to_dict(sub_list, **args) |
| else: |
| result_dict[parent_key] = map(str.strip, sub_list) |
| |
| return result_dict |
| |
| |
| def key_value_outbuf_to_dict(out_buf, |
| **args): |
| r""" |
| Convert a buffer with a key/value string on each line to a dictionary and |
| return it. |
| |
| Each line in the out_buf should end with a \n. |
| |
| See docstring of parse_key_value function for details on key/value strings. |
| |
| Example usage: |
| |
| For the following value of out_buf: |
| |
| Current Limit State: No Active Power Limit |
| Exception actions: Hard Power Off & Log Event to SEL |
| Power Limit: 0 Watts |
| Correction time: 0 milliseconds |
| Sampling period: 0 seconds |
| |
| And the following call in python: |
| |
| power_limit = key_value_outbuf_to_dict(out_buf) |
| |
| The resulting power_limit directory would look like this: |
| |
| power_limit: |
| [current_limit_state]: No Active Power Limit |
| [exception_actions]: Hard Power Off & Log Event to SEL |
| [power_limit]: 0 Watts |
| [correction_time]: 0 milliseconds |
| [sampling_period]: 0 seconds |
| |
| Description of argument(s): |
| out_buf A buffer with a key/value string on each |
| line. (See docstring of parse_key_value |
| function for details). |
| **args Arguments to be interpreted by |
| parse_key_value. (See docstring of |
| parse_key_value function for details). |
| """ |
| |
| # Create key_var_list and remove null entries. |
| key_var_list = list(filter(None, out_buf.split("\n"))) |
| return key_value_list_to_dict(key_var_list, **args) |
| |
| |
| def create_field_desc_regex(line): |
| |
| r""" |
| Create a field descriptor regular expression based on the input line and |
| return it. |
| |
| This function is designed for use by the list_to_report function (defined |
| below). |
| |
| Example: |
| |
| Given the following input line: |
| |
| -------- ------------ ------------------ ------------------------ |
| |
| This function will return this regular expression: |
| |
| (.{8}) (.{12}) (.{18}) (.{24}) |
| |
| This means that other report lines interpreted using the regular |
| expression are expected to have: |
| - An 8 character field |
| - 3 spaces |
| - A 12 character field |
| - One space |
| - An 18 character field |
| - One space |
| - A 24 character field |
| |
| Description of argument(s): |
| line A line consisting of dashes to represent |
| fields and spaces to delimit fields. |
| """ |
| |
| # Split the line into a descriptors list. Example: |
| # descriptors: |
| # descriptors[0]: -------- |
| # descriptors[1]: |
| # descriptors[2]: |
| # descriptors[3]: ------------ |
| # descriptors[4]: ------------------ |
| # descriptors[5]: ------------------------ |
| descriptors = line.split(" ") |
| |
| # Create regexes list. Example: |
| # regexes: |
| # regexes[0]: (.{8}) |
| # regexes[1]: |
| # regexes[2]: |
| # regexes[3]: (.{12}) |
| # regexes[4]: (.{18}) |
| # regexes[5]: (.{24}) |
| regexes = [] |
| for descriptor in descriptors: |
| if descriptor == "": |
| regexes.append("") |
| else: |
| regexes.append("(.{" + str(len(descriptor)) + "})") |
| |
| # Join the regexes list into a regex string. |
| field_desc_regex = ' '.join(regexes) |
| |
| return field_desc_regex |
| |
| |
| def list_to_report(report_list, |
| to_lower=1, |
| field_delim=None): |
| r""" |
| Convert a list containing report text lines to a report "object" and |
| return it. |
| |
| The first entry in report_list must be a header line consisting of column |
| names delimited by white space. No column name may contain white space. |
| The remaining report_list entries should contain tabular data which |
| corresponds to the column names. |
| |
| A report object is a list where each entry is a dictionary whose keys are |
| the field names from the first entry in report_list. |
| |
| Example: |
| Given the following report_list as input: |
| |
| rl: |
| rl[0]: Filesystem 1K-blocks Used Available Use% Mounted on |
| rl[1]: dev 247120 0 247120 0% /dev |
| rl[2]: tmpfs 248408 79792 168616 32% /run |
| |
| This function will return a list of dictionaries as shown below: |
| |
| df_report: |
| df_report[0]: |
| [filesystem]: dev |
| [1k-blocks]: 247120 |
| [used]: 0 |
| [available]: 247120 |
| [use%]: 0% |
| [mounted]: /dev |
| df_report[1]: |
| [filesystem]: dev |
| [1k-blocks]: 247120 |
| [used]: 0 |
| [available]: 247120 |
| [use%]: 0% |
| [mounted]: /dev |
| |
| Notice that because "Mounted on" contains a space, "on" would be |
| considered the 7th field. In this case, there is never any data in field |
| 7 so things work out nicely. A caller could do some pre-processing if |
| desired (e.g. change "Mounted on" to "Mounted_on"). |
| |
| Example 2: |
| |
| If the 2nd line of report data is a series of dashes and spaces as in the |
| following example, that line will serve to delineate columns. |
| |
| The 2nd line of data is like this: |
| ID status size |
| tool,clientid,userid |
| -------- ------------ ------------------ ------------------------ |
| 20000001 in progress 0x7D0 ,, |
| |
| Description of argument(s): |
| report_list A list where each entry is one line of |
| output from a report. The first entry |
| must be a header line which contains |
| column names. Column names may not |
| contain spaces. |
| to_lower Change the resulting key names to lower |
| case. |
| field_delim Indicates that there are field delimiters |
| in report_list entries (which should be |
| removed). |
| """ |
| |
| if len(report_list) <= 1: |
| # If we don't have at least a descriptor line and one line of data, |
| # return an empty array. |
| return [] |
| |
| if field_delim is not None: |
| report_list = [re.sub("\\|", "", line) for line in report_list] |
| |
| header_line = report_list[0] |
| if to_lower: |
| header_line = header_line.lower() |
| |
| field_desc_regex = "" |
| if re.match(r"^-[ -]*$", report_list[1]): |
| # We have a field descriptor line (as shown in example 2 above). |
| field_desc_regex = create_field_desc_regex(report_list[1]) |
| field_desc_len = len(report_list[1]) |
| pad_format_string = "%-" + str(field_desc_len) + "s" |
| # The field descriptor line has served its purpose. Deleting it. |
| del report_list[1] |
| |
| # Process the header line by creating a list of column names. |
| if field_desc_regex == "": |
| columns = header_line.split() |
| else: |
| # Pad the line with spaces on the right to facilitate processing with |
| # field_desc_regex. |
| header_line = pad_format_string % header_line |
| columns = map(str.strip, re.findall(field_desc_regex, header_line)[0]) |
| |
| report_obj = [] |
| for report_line in report_list[1:]: |
| if field_desc_regex == "": |
| line = report_line.split() |
| else: |
| # Pad the line with spaces on the right to facilitate processing |
| # with field_desc_regex. |
| report_line = pad_format_string % report_line |
| line = map(str.strip, re.findall(field_desc_regex, report_line)[0]) |
| try: |
| line_dict = collections.OrderedDict(zip(columns, line)) |
| except AttributeError: |
| line_dict = DotDict(zip(columns, line)) |
| report_obj.append(line_dict) |
| |
| return report_obj |
| |
| |
| def outbuf_to_report(out_buf, |
| **args): |
| r""" |
| Convert a text buffer containing report lines to a report "object" and |
| return it. |
| |
| Refer to list_to_report (above) for more details. |
| |
| Example: |
| |
| Given the following out_buf: |
| |
| Filesystem 1K-blocks Used Available Use% Mounted |
| on |
| dev 247120 0 247120 0% /dev |
| tmpfs 248408 79792 168616 32% /run |
| |
| This function will return a list of dictionaries as shown below: |
| |
| df_report: |
| df_report[0]: |
| [filesystem]: dev |
| [1k-blocks]: 247120 |
| [used]: 0 |
| [available]: 247120 |
| [use%]: 0% |
| [mounted]: /dev |
| df_report[1]: |
| [filesystem]: dev |
| [1k-blocks]: 247120 |
| [used]: 0 |
| [available]: 247120 |
| [use%]: 0% |
| [mounted]: /dev |
| |
| Other possible uses: |
| - Process the output of a ps command. |
| - Process the output of an ls command (the caller would need to supply |
| column names) |
| |
| Description of argument(s): |
| out_buf A text report. The first line must be a |
| header line which contains column names. |
| Column names may not contain spaces. |
| **args Arguments to be interpreted by |
| list_to_report. (See docstring of |
| list_to_report function for details). |
| """ |
| |
| report_list = list(filter(None, out_buf.split("\n"))) |
| return list_to_report(report_list, **args) |
| |
| |
| def nested_get(key_name, structure): |
| r""" |
| Return a list of all values from the nested structure that have the given |
| key name. |
| |
| Example: |
| |
| Given a dictionary structure named "personnel" with the following contents: |
| |
| personnel: |
| [manager]: |
| [last_name]: Doe |
| [first_name]: John |
| [accountant]: |
| [last_name]: Smith |
| [first_name]: Will |
| |
| The following code... |
| |
| last_names = nested_get('last_name', personnel) |
| print_var(last_names) |
| |
| Would result in the following data returned: |
| |
| last_names: |
| last_names[0]: Doe |
| last_names[1]: Smith |
| |
| Description of argument(s): |
| key_name The key name (e.g. 'last_name'). |
| structure Any nested combination of lists or |
| dictionaries (e.g. a dictionary, a |
| dictionary of dictionaries, a list of |
| dictionaries, etc.). This function will |
| locate the given key at any level within |
| the structure and include its value in the |
| returned list. |
| """ |
| |
| result = [] |
| if type(structure) is list: |
| for entry in structure: |
| result += nested_get(key_name, entry) |
| return result |
| elif gp.is_dict(structure): |
| for key, value in structure.items(): |
| result += nested_get(key_name, value) |
| if key == key_name: |
| result.append(value) |
| |
| return result |
| |
| |
| def match_struct(structure, match_dict, regex=False): |
| r""" |
| Return True or False to indicate whether the structure matches the match |
| dictionary. |
| |
| Example: |
| |
| Given a dictionary structure named "personnel" with the following contents: |
| |
| personnel: |
| [manager]: |
| [last_name]: Doe |
| [first_name]: John |
| [accountant]: |
| [last_name]: Smith |
| [first_name]: Will |
| |
| The following call would return True. |
| |
| match_struct(personnel, {'last_name': '^Doe$'}, regex=True) |
| |
| Whereas the following call would return False. |
| |
| match_struct(personnel, {'last_name': 'Johnson'}, regex=True) |
| |
| Description of argument(s): |
| structure Any nested combination of lists or |
| dictionaries. See the prolog of |
| get_nested() for details. |
| match_dict Each key/value pair in match_dict must |
| exist somewhere in the structure for the |
| structure to be considered a match. A |
| match value of None is considered a |
| special case where the structure would be |
| considered a match only if the key in |
| question is found nowhere in the structure. |
| regex Indicates whether the values in the |
| match_dict should be interpreted as |
| regular expressions. |
| """ |
| |
| # The structure must match for each match_dict entry to be considered a |
| # match. Therefore, any failure to match is grounds for returning False. |
| for match_key, match_value in match_dict.items(): |
| struct_key_values = nested_get(match_key, structure) |
| if match_value is None: |
| # Handle this as special case. |
| if len(struct_key_values) != 0: |
| return False |
| else: |
| if len(struct_key_values) == 0: |
| return False |
| if regex: |
| matches = [x for x in struct_key_values |
| if re.search(match_value, str(x))] |
| if not matches: |
| return False |
| elif match_value not in struct_key_values: |
| return False |
| |
| return True |
| |
| |
| def filter_struct(structure, filter_dict, regex=False, invert=False): |
| r""" |
| Filter the structure by removing any entries that do NOT contain the |
| keys/values specified in filter_dict and return the result. |
| |
| The selection process is directed only at the first-level entries of the |
| structure. |
| |
| Example: |
| |
| Given a dictionary named "properties" that has the following structure: |
| |
| properties: |
| [/redfish/v1/Systems/system/Processors]: |
| [Members]: |
| [0]: |
| [@odata.id]: |
| /redfish/v1/Systems/system/Processors/cpu0 |
| [1]: |
| [@odata.id]: |
| /redfish/v1/Systems/system/Processors/cpu1 |
| [/redfish/v1/Systems/system/Processors/cpu0]: |
| [Status]: |
| [State]: Enabled |
| [Health]: OK |
| [/redfish/v1/Systems/system/Processors/cpu1]: |
| [Status]: |
| [State]: Enabled |
| [Health]: Bad |
| |
| The following call: |
| |
| properties = filter_struct(properties, "[('Health', 'OK')]") |
| |
| Would return a new properties dictionary that looks like this: |
| |
| properties: |
| [/redfish/v1/Systems/system/Processors/cpu0]: |
| [Status]: |
| [State]: Enabled |
| [Health]: OK |
| |
| Note that the first item in the original properties directory had no key |
| anywhere in the structure named "Health". Therefore, that item failed to |
| make the cut. The next item did have a key named "Health" whose value was |
| "OK" so it was included in the new structure. The third item had a key |
| named "Health" but its value was not "OK" so it also failed to make the |
| cut. |
| |
| Description of argument(s): |
| structure Any nested combination of lists or |
| dictionaries. See the prolog of |
| get_nested() for details. |
| filter_dict For each key/value pair in filter_dict, |
| each entry in structure must contain the |
| same key/value pair at some level. A |
| filter_dict value of None is treated as a |
| special case. Taking the example shown |
| above, [('State', None)] would mean that |
| the result should only contain records |
| that have no State key at all. |
| regex Indicates whether the values in the |
| filter_dict should be interpreted as |
| regular expressions. |
| invert Invert the results. Instead of including |
| only matching entries in the results, |
| include only NON-matching entries in the |
| results. |
| """ |
| |
| # Convert filter_dict from a string containing a python object definition |
| # to an actual python object (if warranted). |
| filter_dict = fa.source_to_object(filter_dict) |
| |
| # Determine whether structure is a list or a dictionary and process |
| # accordingly. The result returned will be of the same type as the |
| # structure. |
| if type(structure) is list: |
| result = [] |
| for element in structure: |
| if match_struct(element, filter_dict, regex) != invert: |
| result.append(element) |
| else: |
| try: |
| result = collections.OrderedDict() |
| except AttributeError: |
| result = DotDict() |
| for struct_key, struct_value in structure.items(): |
| if match_struct(struct_value, filter_dict, regex) != invert: |
| result[struct_key] = struct_value |
| |
| return result |