pyats.utils package¶
Subpackages¶
- pyats.utils.fileutils package
- Subpackages
- pyats.utils.fileutils.bases package
- pyats.utils.fileutils.core package
- pyats.utils.fileutils.plugins package
- Submodules
- Subpackages
- pyats.utils.import_utils package
- pyats.utils.yaml package
Submodules¶
- pyats.utils.ansi.escape(line)¶
escape ansi by removing escape sequences.
Utilities to help with tricky CLI command parsing
- pyats.utils.cli_parse_helpers.expand_nargs_list(nargs_list)¶
Expands an argparse nargs list of strings.
Any single or double quotes are stripped from the items.
NOTE: The ordering of the output list is not guaranteed to match the ordering of the input list.
Duplicates are removed from the list.
If the input list is empty, it is just returned without further processing.
Example
>>> import argparse >>> from pyats.utils.cli_parse_helpers import expand_nargs_list >>> parser = argparse.ArgumentParser() >>> parser.add_argument('--foo', nargs='*') >>> p = parser.parse_args('--foo 4 5 6 "1 2 3 4" x y 5 '.split()) >>> sorted(expand_nargs_list(p.foo)) ['1', '2', '3', '4', '5', '6', 'x', 'y']
- pyats.utils.cli_parse_helpers.remove_dups_from_multiple_nargs_list(multiple_nargs_list)¶
Ensure dups are removed from a list of nargs lists. Empty lists are removed.
>>> import argparse >>> from pyats.utils.cli_parse_helpers import expand_nargs_list, remove_dups_from_multiple_nargs_list >>> parser = argparse.ArgumentParser() >>> parser.add_argument('--foo', nargs='*', action='append') >>> p = parser.parse_args('--foo 4 5 6 "1 2 3 4" x y 5 --foo 2 4 6 8'.split()) >>> remove_dups_from_multiple_nargs_list([sorted(expand_nargs_list(foo)) for foo in p.foo]) [['1', '2', '3', '4', '5', '6', 'x', 'y'], ['8']]
- class pyats.utils.commands.DecodeSecret(*args, **kwargs)¶
Bases:
pyats.cli.base.Subcommand
- description = '\nDecodes an encoded string into plaintext form.\n\nThe decoding used may be changed by specifying the pyats configuration:\n[secrets] string.representer = representer_module.representer_class\n\nOtherwise, a default cipher encoding is expected.\n\nThe decoding may be personalized by using the pyats configuration:\n[secrets] string.key = <generated_key>\n\nwhere <generated_key> refers to the key generated with the "pyats secret keygen"\ncommand.\n\nIf specified, --prefix selects other representers defined in the pyats\nconfiguration. The following keys are expected to be present:\n[secrets] <prefix>.representer\n[secrets] <prefix>.key\n '¶
- help = 'decode an encoded string'¶
- name = 'decode'¶
- run(args)¶
runs this subcommand
- usage = '{prog} [string] [options]'¶
- class pyats.utils.commands.EncodeSecret(*args, **kwargs)¶
Bases:
pyats.cli.base.Subcommand
- description = '\nEncodes a plaintext string into an encoded form. By default, it will ask to\ninput password as prompt(Recommended).\nInstead, `--string` can be given with plaintext password.\n\nThe encoding used may be changed by specifying the pyats configuration:\n[secrets] string.representer = representer_module.representer_class\n\nOtherwise, a default cipher encoding is used.\n\nThe encoding may be personalized by using the pyats configuration:\n[secrets] string.key = <generated_key>\n\nwhere <generated_key> refers to the key generated with the "pyats secret keygen"\ncommand.\n\nIf specified, --prefix selects other representers defined in the pyats\nconfiguration. The following keys are expected to be present:\n[secrets] <prefix>.representer\n[secrets] <prefix>.key\n '¶
- help = 'encode a plaintext string'¶
- name = 'encode'¶
- run(args)¶
runs this subcommand
- usage = '{prog} [options]'¶
- class pyats.utils.commands.KeyGenSecret(*args, **kwargs)¶
Bases:
pyats.cli.base.Subcommand
- description = '\nGenerates a new personalized key used to encode/decode a secret string.\n\nThis key, once generated, would typically be manually placed in the pyats\nconfiguration:\n[secrets] string.key = <generated_key>\n\nThe chosen representer controls the format of the returned key.\nThe format of the returned key depends upon the representer specified\nvia the pyats configuration:\n[secrets] string.representer = representer_module.representer_class\n\nIMPORTANT: Please ensure any pyats configuration file(s) containing this key\nare locked down with appropriate permissions to ensure only authorized parties\nmay read it.\n\nIf specified, --prefix selects other representers defined in the pyats\nconfiguration. The following key is expected to be present:\n[secrets] <prefix>.representer\n '¶
- help = 'generate a key used to encode/decode a secret string'¶
- name = 'keygen'¶
- run(args)¶
runs this subcommand
- usage = '{prog} [options]'¶
- class pyats.utils.commands.ValidateDatafile(*args, **kwargs)¶
Bases:
pyats.cli.base.Subcommand
Validates that a testbed file is loadable
- description = "\nValidates the provided YAML datafile for syntax and content completeness.\n\nNote:\n This command also understands the pyATS datafile 'extends:' syntax, and\n returns the complete, full data content with extensions fulfilled.\n "¶
- help = 'validate your YAML-based datafile syntax'¶
- name = 'datafile'¶
- run(args)¶
runs this subcommand
- usage = '{prog} [file] [options]'¶
- pyats.utils.commands.do_lint(yaml_file, silent=False)¶
- pyats.utils.dicts.create_extended_dict(source_dict, dest_dict={}, rename_keys=True)¶
Generates a dictionary where each key is uniquely named. Duplicate keys get _1, _2, _3 etc appended to them. If exact key/value match is found, they’re excluded to avoid redundant information.
- Parameters
- Returns
dict - a new dictionary with uniquely named keys
- Raises
N/A –
- pyats.utils.dicts.enforce_max_key_value_length(dict_to_check, max_key_length=40, max_value_length=512)¶
Enforce key length and value length rules for supplied dictionary.
- Parameters
- Returns
N/A
- Raises
Exception – if any key has more characters than max_key_length or if any value has more characters than max_value_length
- pyats.utils.dicts.generate_unique_key_name(key, value, dictionary, allow_match=False) str ¶
Generates a unique key name by appending an underscore and integer
- Parameters
- Returns
None - if an exact key/value match was found str - if a unique key name has been generated
- Raises
N/A –
- pyats.utils.dicts.load_dict_from_json_string(loadable) dict ¶
Load a dictionary from a JSON string. The JSON string can optionally be urlsafe base64 encoded.
- Parameters
loadable (str) – JSON string, optional with base64 encoding
- Returns
dictionary
- Raises
ValueError if the JSON string could not be loaded –
- pyats.utils.dicts.load_dict_from_kv_string(loadable) dict ¶
load a flat dictionary from k=v value pairs.
- Parameters
loadable (str) – String with k=v pairs, separated by space, optional with base64 encoding
- Returns
value} pairs
- Return type
dictionary of {key
- pyats.utils.dicts.load_dict_from_list(loadable, unique_keys=True) dict ¶
load a flat dictionary from string of List of string values.
- pyats.utils.dicts.recursive_cast(d, type_)¶
Recursively cast a nested dictionary to the provided class type
- pyats.utils.dicts.recursive_setdefault(a, b)¶
Recursively calls setdefault on nested dictionary a with dictionary b.
- pyats.utils.dicts.recursive_update(a, b, *, list_extend=False)¶
Recursively updates on nested dictionary a with dictionary b.
- pyats.utils.dicts.set_dict_by_key_path(d, keys, val, *, append_list=False)¶
Utility function which sets an element in a nested dictionary by indexing the nested dictionary with a list of keys, creating any keys which don’t exist
Example
>>> d = {} >>> set_dict_by_key_path(d, ['a', 'b', 'c'], 1) >>> d {'a': {'b': {'c': 1}}} >>> set_dict_by_key_path(d, ['a', 'b', 'd'], 0) {'a': {'b': {'c': 1, 'd': 0}}} >>>
- Parameters
(dictionary) (d) –
strings) (keys (list of) –
(any) (val) –
(bool (append_list) – append the value to it. If the element specified by the key doesnt exist, insert an empty list and append the value to it. If the existing element is not a list than raise a ValueError
optional) (if element specified by a key is a list,) – append the value to it. If the element specified by the key doesnt exist, insert an empty list and append the value to it. If the existing element is not a list than raise a ValueError
- Returns
- Return type
the value which was set, or None if no value was set
- class pyats.utils.email.EmailMsg(from_email=None, to_email=None, subject='', body='', attachments=None, html_email=False, html_body='', default_domain=None)¶
Bases:
object
EmailMsg Class
A container for email information.
EmailMsg constructor Initialize a single email message (which can be sent to multiple recipients).
- Parameters
(list/str) (from_email) – in the generated email’s “From:” field.
to_email(list/str) (list or string-list of addresses to be used) – in the generated email’s “To:” field.
(str) (subject) –
(string) (html_body) –
(list) (attachments) –
(bool) (html_email) –
(string) –
- static convert_to_address(value, default_domain)¶
convert address values
converts space/comma/semi-colon delimited strings and lists of string ids into email address objects.
- get_content()¶
get message body
Returns report plain text body
- Returns
- Return type
self.body
- property mailbody¶
mailbody property getter
Returns the body attribute of EmailMsg object.
- property mailsubject¶
mailsubject property getter
Returns the subject attribute of EmailMsg object.
- message()¶
creates message
Constructs email.message.EmailMessage object
- Returns
- Return type
msg - email.message.EmailMessage object
- recipients()¶
recipients list
Returns a list of all recipients of the email
- Returns
- Return type
self.to_email
- send(host=None, port=None, ssl=None, timeout=None, username=None, password=None)¶
send message
Sends email using smtp host
Errors related to utils module
- exception pyats.utils.exceptions.SchemaClassError(path, cls, data, detail=None, locations=None)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, cls, data, detail, locations)¶
- exception pyats.utils.exceptions.SchemaError(*args, locations=None, **kwargs)¶
Bases:
Exception
Error during Schema validation.
- joinPath(path)¶
- exception pyats.utils.exceptions.SchemaFallbackCall(path, diff_context_retry)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, diff_context_retry)¶
- exception pyats.utils.exceptions.SchemaFallbackError(path, data)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, data)¶
- exception pyats.utils.exceptions.SchemaFallbackLoopError(a, b)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(a, b)¶
- exception pyats.utils.exceptions.SchemaMissingKeyError(path, keys, locations=None)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, keys, locations)¶
- exception pyats.utils.exceptions.SchemaTypeError(path, schema, data, detail=None, locations=None)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, schema, data, detail, locations)¶
- exception pyats.utils.exceptions.SchemaUnsupportedKeyError(path, keys, locations=None)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, keys, locations)¶
- exception pyats.utils.exceptions.SchemaValueError(path, schema, data, detail=None, locations=None)¶
Bases:
pyats.utils.exceptions.SchemaError
- format(path, schema, data, detail, locations)¶
- pyats.utils.exceptions.safe_chainget(d, path)¶
- class pyats.utils.objects.Contains(value=None)¶
Bases:
pyats.utils.objects.Operator
Contains operator
Examples
>>> class Obj(): def __init__(self): self.data = {'100': {'status': 'active', 'vl_mode': 'CE', 'members': [1,2,3,4], 'vlan_type': 'enet', 'name': 'VLAN0100'}} obj= Obj() found = find(obj, R(['data',Operator('(.*)'), 'members', Contains(1)])) found = find(obj, R(['data',Operator('(.*)'), 'name', Contains('100')]))
Operator class
- class pyats.utils.objects.Find¶
Bases:
object
- find(from_, *requirements, type_=None, filter_=True, index=None, _first=True, all_keys=False, **kwargs)¶
Filters the objects that are matching the requirements in an iterable.
- Params:
from_(list): Iterable object that will be searched. Can’t be None
requirements: List of requirements(R objects) for the search
- type_(list): Class type of the object that the user wants to find,
can be provided as a list as well
- kwargs: Key word arguments to create a set of requirements. Easier
for users to create requirements.
filter_
(bool
): If True: Will return the particular matchingobject. If False: Will return the actual value which is matching. Default: True
- index (
int
): Can only be used with filter_=False. Used for mentioning which of the dictionary value to return. Default: last element (Aka value).
- index (
- all_keys (
bool
) If True: Will return all the particular matching objects with path to objects that matches to first requirement. If False: Will return the particular matching objects with path to objects which is matching. Default: False
- all_keys (
Examples
>>> from pyats.utils.objects import find, R
>>> find(from_ = [1, 2, 1.2, "bla"], type_ = int) [1, 2]
>>> find([1,2,1.2, "bla", {"bla": "blabla"}], R(bla = "blabla"), type_ = [dict]) [{"bla": "blabla"}]
TODO:
R class sets a limitation to find api’s “__” syntax, as it’s explained in the documentation, if the object name or attribute name starts or ends with “_”, find API can’t find the expected results. There are 2 ways to come over the problem, first the syntax can be something like “_r_” then limitation will be rare. Find will fail only if user object name has “_r_” in it. The other way is providing dictionaries instead of R objects as requirement sets and changing the syntax to some character that is not allowed to use as variable name such as “!” or “.”. But this will also has a limitation for dictionary keys as these characters actually allowed to be a key of a dictionary.
- reset_keys()¶
Reset all the keys as find api returns an instance not the object.
- class pyats.utils.objects.GroupKeys¶
Bases:
object
- Compose the dict which contains the headers as keys, and values
from the source corresponding keys
Short version from Genie
- classmethod group_keys(source, reqs, ret_num=None, all_keys=False)¶
Compose the dict which contains the headers as keys, and values from the source corresponding keys
- Parameters
- Returns
dict - Dictionary with the keys from args, format will be like {key1: [value1, value2], key2: [value1, value2]} empty - Empty dict
- Raises
None –
Example
>>> group_keys(source = [('Established', ['instance', 'default', 'vrf', 'default', 'neighbor', '200.1.1.1', 'session_state']), ('Established', ['instance', 'default', 'vrf', 'default', 'neighbor', '200:1::1:1', 'session_state'])], headers = ['neighbor', 'vrf', 'instance'])
>>> {'vrf': ['default', 'default'], 'instance': ['default', 'default'], 'neighbor': ['200.1.1.1', '200:1::1:1']}
- class pyats.utils.objects.Not(value=None)¶
Bases:
pyats.utils.objects.Operator
Not operator
Examples
>>> class Obj(): def __init__(self): self.data = {'100': {'status': 'active', 'vl_mode': 'CE', 'members': [1,2,3,4], 'vlan_type': 'enet', 'name': 'VLAN0100'}} obj= Obj() found = find(obj, R(['data',Not('200')])) found = find(obj, R(['data',Operator('(.*)'), 'status', Not('deactive')]))
Operator class
- class pyats.utils.objects.NotExists(value=None)¶
Bases:
pyats.utils.objects.Operator
Key does not exists in dictionary and object
Examples
>>> class Obj(): def __init__(self): self.data = {'100': {'status': 'active', 'vl_mode': 'CE', 'members': [1,2,3,4], 'vlan_type': 'enet', 'name': 'VLAN0100'}} obj= Obj() found = find(obj, R(['data',Operator('(.*)'), 'members', Contains(1)])) found = find(obj, R(['data',Operator('(.*)'), 'name', Contains('100')]))
Operator class
- class pyats.utils.objects.Operator(value=None)¶
Bases:
object
basic find operator
Takes a requirement value and uses to match laterly.
- Parameters
value (
object
) – regex or str or any object
Examples
>>> class Obj(): def __init__(self): self.data = {'100': {'status': 'active', 'vl_mode': 'CE', 'members': [1,2,3,4], 'vlan_type': 'enet', 'name': 'VLAN0100'}} obj= Obj() found = find(obj, R(['data',Operator('(.*)')])) found = find(obj, R(['data',Operator('(.*)'), 'members', Operator([1,2,3,4])]))
Operator class
- match(other)¶
- pyats.utils.objects.find(from_, *requirements, type_=None, filter_=True, index=None, _first=True, all_keys=False, **kwargs)¶
Filters the objects that are matching the requirements in an iterable.
- Params:
from_(list): Iterable object that will be searched. Can’t be None
requirements: List of requirements(R objects) for the search
- type_(list): Class type of the object that the user wants to find,
can be provided as a list as well
- kwargs: Key word arguments to create a set of requirements. Easier
for users to create requirements.
filter_
(bool
): If True: Will return the particular matchingobject. If False: Will return the actual value which is matching. Default: True
- index (
int
): Can only be used with filter_=False. Used for mentioning which of the dictionary value to return. Default: last element (Aka value).
- index (
- all_keys (
bool
) If True: Will return all the particular matching objects with path to objects that matches to first requirement. If False: Will return the particular matching objects with path to objects which is matching. Default: False
- all_keys (
Examples
>>> from pyats.utils.objects import find, R
>>> find(from_ = [1, 2, 1.2, "bla"], type_ = int) [1, 2]
>>> find([1,2,1.2, "bla", {"bla": "blabla"}], R(bla = "blabla"), type_ = [dict]) [{"bla": "blabla"}]
TODO:
R class sets a limitation to find api’s “__” syntax, as it’s explained in the documentation, if the object name or attribute name starts or ends with “_”, find API can’t find the expected results. There are 2 ways to come over the problem, first the syntax can be something like “_r_” then limitation will be rare. Find will fail only if user object name has “_r_” in it. The other way is providing dictionaries instead of R objects as requirement sets and changing the syntax to some character that is not allowed to use as variable name such as “!” or “.”. But this will also has a limitation for dictionary keys as these characters actually allowed to be a key of a dictionary.
- class pyats.utils.parser.ArgsPropagationParser(prog=None, usage=None, description=None, epilog=None, parents=[], formatter_class=<class 'argparse.HelpFormatter'>, prefix_chars='-', fromfile_prefix_chars=None, argument_default=None, conflict_handler='error', add_help=True, allow_abbrev=True, exit_on_error=True)¶
Bases:
argparse.ArgumentParser
- parse_args(args=None, namespace=None)¶
- class pyats.utils.parser.pyATS_HelpFormatter(*args, **kwargs)¶
- class pyats.utils.schemaengine.And(*args, path=None)¶
Bases:
pyats.utils.schemaengine.Schema
And Class (Schema)
Defines a schema of AND relationship, eg, the input data must pass the validation of all of the requirements of this Schema.
Example
# requires a string of ‘left’ or ‘right’ And(str, lambda: s: s in (‘left’, ‘right’))
- Parameters
*args – arbitrary args of schema to apply AND to.
- validate(data, top=False, locations=None, advanced_datatypes=True)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.schemaengine.Any(path=None)¶
Bases:
pyats.utils.schemaengine.Optional
Any Class (Optional, Schema)
Marks a section of a schema that matches anything. This is effectively a wildcard (*).
Note that Any is also Optional.
- class pyats.utils.schemaengine.Default(schema, default, path=None)¶
Bases:
pyats.utils.schemaengine.Optional
Default Class (Optional, Schema)
Defines a schema with a default. Eg, if the schema was not satisfied, the default value is added to the input data. A Default schema is also Optional.
Note
using the Default schema changes the input data (due to application of default values)
- Usage Criteria:
if a Default() is part of a dictionary schema type, then keys leading to this default value cannot be marked with any other schema objects, such as Optional(). Using Default() means that its key-chain is automatically mandatory, because regardless of input, the keys leading to the default value will always be there.
- Parameters
schema (any) – input schema requirements
default (any) – default value to apply
- validate(data, top=False, locations=None, advanced_datatypes=True)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.schemaengine.Fallback(schema, fallback)¶
Bases:
pyats.utils.schemaengine.Optional
Fallback Class (Optional, Schema)
Defines a schema with a Fallback. Eg, if the schema was not satisfied, the value falls-back to another value in the given data. A Fallback schema is also Optional.
Fallbacks can only be used if the input schema and data to be validated are of type dict.
Note
using the Fallback schema changes the input data (due to application of fallback values)
- Parameters
schema (any) – input schema requirements
fallback (str) – string representing the key to fallback to, using ‘.’ as separator to identify dict nesting levels.
Example
# fall back to data[‘a’][‘b’][‘c’] Fallback(str, ‘a.b.c’)
- class pyats.utils.schemaengine.ListOf(schema, path=None)¶
Bases:
pyats.utils.schemaengine.Schema
- validate(data, top=False, locations=None, advanced_datatypes=True)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.schemaengine.Optional(schema, path=None)¶
Bases:
pyats.utils.schemaengine.Schema
Optional Class (Schema)
Marks an optional part of the schema.
- class pyats.utils.schemaengine.Or(*args, path=None)¶
Bases:
pyats.utils.schemaengine.Schema
Or Class (Schema)
Defines a schema of OR relationship, eg, the input data must pass the validation of one of the requirements of this Schema.
Example
# requires a string or an integer Or(str, int)
- Parameters
*args – arbitrary args of schema to apply OR to.
- validate(data, top=False, locations=None, advanced_datatypes=True)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.schemaengine.Schema(schema, path=None)¶
Bases:
object
Schema class
Provides the ability to define schema (schematics/requirements) for input data, and subsequently validate whether the input data meets requirements.
Example
data = Schema(str).validate(‘a string’) data = Schema({‘a’: str}).validate({‘a’: ‘some string’})
- Parameters
schema – the schema to be validated against. Any valid python datastructures/callable.
See also
PyPI: schema https://pypi.python.org/pypi/schema/0.3.1
- apply_defaults(data)¶
This API takes the current data and apply default fields to it wherever needed (eg, missing fields)
- Parameters
data (any) – input data
- Returns
input data augmented with default values
- apply_fallback(data)¶
This API goes through the schema looking for fallback fields. When found, it takes the fallback key, pull up its data, and apply it to the current field, if it doesn’t exist.
- Parameters
data (any) – input data
- Returns
input data augmented with fallback values
- collect_defaults()¶
Based on the given schema, compute the defaults, if any. This involves using the Default subclass and creating a new datastructure that represents the default state of this schema (eg, with a None input, the resulting data should look like the output of this)
- collect_fallbacks()¶
Based on the given schema, compute the fallbacks, if any. This involves using the Fallback subclass and creating a new datastructure that represents the fallback states of this schema, eg, if a key does not exist, it should fallback to another key’s value.
Note
Fallbacks are only valid if the schema type is Dict.
- classmethod priority(obj)¶
Function to make sure that we always process Any objects last. Eg. process mandatory and optional ones first before trying to match Any
- validate(data, top=True, locations=None, advanced_datatypes=True)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.schemaengine.Use(schema, path=None)¶
Bases:
pyats.utils.schemaengine.Schema
- validate(data, top=False, locations=None, **kwargs)¶
validate input
Validates the given data against the current schema, and returns the correct, validated and optionally updated data. If there are defaults or fallbacks associated with the schema, augment the input data with them so that the final return contains validated data + the defaults/fallbacks.
If advanded datatypes is enabled, returns the data with advanced datatypes, e.g. class objects instead of the original data.
- class pyats.utils.secret_strings.FernetSecretStringRepresenter(obj, prefix='string')¶
Bases:
pyats.utils.secret_strings.BaseSecretStringRepresenter
A representer for a cryptographically secure string.
- decode()¶
Decode a contained encoded string object
- encode()¶
Encode a contained plaintext string object
- property key¶
- classmethod keygen()¶
- class pyats.utils.secret_strings.SecretString(secret_string, representer_cls=None, prefix='string')¶
Bases:
collections.UserString
A string that is meant to be a secret.
These strings are not displayed as plaintext but offer APIs to retrieve plaintext and also create from plaintext.
A representer:
Defines how the string is converted to/from plaintext.
If not passed in explicitly in the constructor, may be specified via the following pyats configuration value under
[secrets]
:<prefix>.representer
May require a key, which may be specified via the following pyats configuration value under
[secrets]
:<prefix>.key
<prefix> defaults to ‘string’ but may be overridden in the constructor with
prefix
, thus allowing multiple representers to be kept in the pyats configuration file.Defaults to a class that implements a string that is stored using a non cryptographically secure cipher.
Initialize a new SecretString object.
If representer_cls is not specified directly, it is taken from pyats configuration if specified there.
Otherwise it defaults to a non cryptographically secure cipher.
- Parameters
secret_string (
str
) – The already encoded string being modelled.representer_cls (class inheriting from
BaseSecretStringRepresenter
) – This class handles encoding/decoding the secret string.prefix (
str
) – The pyATS configuration prefix under the [secrets] section. The representer is specified via <prefix>.representer. The key is specified via <prefix>.key. Optional, defaults to ‘string’.
- classmethod from_plaintext(plaintext, representer_cls=None, prefix='string')¶
Encode plaintext into a SecretString.
If the user has specified no secret string representer directly or via pyats configuration then by default a non cryptographically secure cipher is used to encode the string.
- classmethod keygen(representer_cls=None, prefix='string')¶
Generate a key.
If the user has specified no secret string representer directly or via pyats configuration then by default a non cryptographically secure key is returned.
- property plaintext¶
Return the plaintext equivalent of the secret string.
- pyats.utils.secret_strings.to_plaintext(str_or_secret_str)¶
Get plaintext from a potentially secret string.
Perform any required decoding in order to return a secret string in plaintext.
- pyats.utils.sig_handlers.enable_double_ctrl_c(callback=None)¶
This function enables the current process to quit only after 2 ctrl-c’s has been received: the first ctrl-c does nothing. Upon receiving the 2nd ctrl-c, the system will behave as expected (KeyboardInterrupt exception is raised.)
- Parameters
callback (callable) – a callable function that will be called when the first ctrl-c is received. The current stack frame will be passed in as the only argument
- pyats.utils.sig_handlers.restore_sigint_handler()¶
- class pyats.utils.strings.TypeGuesser¶
Bases:
object
Guesses string value into corresponding object types.
- Supports:
int
float
boolean (true/false/on/off/yes/no)
None (none or None)
- is_bool(value)¶
- is_float(value)¶
- is_int(value)¶
- is_none(value)¶
- is_type(value, type_)¶
- to_bool(value)¶
- pyats.utils.strings.decode_cli_string(value)¶
Try to decode command line string.
- Parameters
value (str) – String with optional url quoted and/or base64 encoding
- Returns
string
- class pyats.utils.strings.force_lower_str(arg)¶
Bases:
str
This class behaves like string, but forces itself to lowercase.
- class pyats.utils.strings.force_upper_str(arg)¶
Bases:
str
This class behaves like string, but forces itself to UPPERCASE.
- pyats.utils.strings.wrap_split(str_to_wrap, sep='.', width=80)¶
- Iterator that wraps a string across multiple lines within a given width.
Whenever possible, lines are split at a separator boundary.
- str_to_wrapstr
String to wrap.
- sepstr
Separator to control where the string is wrapped.
- widthint
Maximum length of wrapped line.
>>> print('
- ‘.join(wrap_split(“one.two.three.4.5.six”,width=8)))
one.two. three.4. 5.six
>>> print('
- ‘.join(wrap_split(“one.two.three.4.5.six”,width=15)))
one.two.three. 4.5.six
>>> print('
- ‘.join(wrap_split(“one.two.three.4.5.six”,width=4)))
one. two. thre e.4. 5.
- pyats.utils.utils.chainattr(obj, attrs)¶
Utility function, converts lists of attributes into nested obj getattr().
Example
>>> chainattr(obj, ['a','b','c']) >>> chainattr(obj, a.b.c) # is equivalent to >>> obj.a.b.c
- Parameters
(object) (obj) –
(list/str) (attrs) – a string, it will be split by ‘.’
- Returns
- Return type
the final object attribute
- pyats.utils.utils.chainattrget(obj, attrkeys)¶
Utility function, converts list of attributes/keys into nested obj using getattr() or get().
Example
>>> chainattrget(obj, ['a','b','c']) >>> chainattrget(obj, a.b.c) # is equivalent to any mix of attribute or dictionary keys: >>> obj.a.b.c >>> obj[a][b][c] >>> obj.a[b].c
- Parameters
(object) (obj) –
(list/str) (attrkeys) – a string, it will be split by ‘.’
- Returns
- Return type
the final object attribute
- pyats.utils.utils.chainget(d, keys)¶
Utility function, converts lists of keys into nested dictionary gets.
Example
>>> chainget(d, ['a','b','c']) >>> chainget(d, 'a.b.c') # is equivalent to >>> d['a']['b']['c']
- Parameters
(dict) (d) –
(list/str) (keys) – a string, it will be split by ‘.’
- Returns
- Return type
the final value
- pyats.utils.utils.get_argv_args(argv)¶
Parse argv for dash arguments.
Arguments without a value are added as a boolean True value.
- Returns
dictionary of arguments with values
- pyats.utils.utils.get_distro_info()¶
- pyats.utils.utils.get_pip_pkgs()¶
Get pip packages
- pyats.utils.utils.get_runtime_env()¶
- pyats.utils.utils.get_time(seconds=None)¶
- pyats.utils.utils.get_user_frame(exclude_patterns=[])¶
Function that returns the desired frame, ignoring all frames related to this file and those who match any provided exclude patterns.
- pyats.utils.utils.repr_data(data)¶
recursively explore dicts/lists and repr any non-primitives to protect pickling from weakrefs etc.
- pyats.utils.utils.str_to_number(value)¶
Try to convert string value to float or int.
If conversion fails, return value as is.