%global _empty_manifest_terminate_build 0 Name: python-pysisl Version: 0.0.11 Release: 1 Summary: A python library for serialising and deserialising SISL (Simple Information Serialization Language) License: MIT License URL: https://github.com/oakdoor Source0: https://mirrors.aliyun.com/pypi/web/packages/de/c4/8c9ff6b24c60b7d4b689ea1164a74bb7eae45ecd0a1c22631e6aeb32d055/pysisl-0.0.11.tar.gz BuildArch: noarch Requires: python3-ply Requires: python3-jsonschema Requires: python3-deepmerge Requires: python3-mergedeep Requires: python3-construct %description # pySISL A Python library for serialising and deserialising SISL (Simple Information Serialization Language). SISL is a simple structured text format designed for use in the [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data). This library provides the ability to serialise and deserialise SISL as well as perform semantic verification of the SISL. Hardware enforced syntatic verification may be carried out by the [OakdoorTM family of data diodes](https://www.oakdoor.io/products/oakdoor-data-diodes/). Also provides the functionality to wrap and unwrap files with an XOR scrambling technique used on the OakdoorTM data diodes which is designed to render files inert if they fail the syntatic verification allowing the file to be safely transported or stored for later unwrapping and inspection. ## Examples Encoding basic Python object to SISL: >>> import pysisl >>> pysisl.dumps({"hello": "world"}) '{hello: !str "world"}' >>> pysisl.dumps({"name": "helpful_name", "flag": False, "count": 3}) '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' Decoding SISL to Python: >>> import pysisl >>> pysisl.loads('{name: !str "helpful_name", flag: !bool "false", count: !int "3"}') {'name': 'helpful_name', 'flag': False, 'count': 3} ## Basic Usage pysisl.dumps(obj) Serialise a basic Python object into a SISL formatted str. pysisl.loads(sisl, schema=None) Deserialise SISL str to a basic Python object. Optionally, verify the SISL schema using a json schema. pysisl.SislWrapper().wraps(data) Applies an XOR data scrambling technique to wrap and render data inert, equivalent to the OakdoorTM data diode hardware. The data must be bytes() or bytearray(). The XOR key is internally generated and prepended as part of a header. pysisl.SislWrapper().unwraps(data) Unwraps data scrambled with the above XOR data scrambling technique. The data must be bytes() or bytearray(). See the [conversion](#conversion-table) table on this page for more details. ### Splitting large objects into multiple SISL files pySISL supports a maximum length in bytes for SISL files. If the input Python object exceeds this max length it is split into multiple SISL files. A Python list is returned where each item is a SISL string. #### Split an object into SISL with max bytes as 20 >>> import pysisl >>> pysisl.dumps({"abc": 2, "def": 3}, max_length=20) ['{abc: !int "2"}', '{def: !int "3"}'] ### Joining multiple SISL files to form a single Python object If a SISL file has been split in the way described above, pySISL supports joining the split files into a single Python object. When a list of SISL strings is passed to pySISL.loads(), this joining is done by default. A single Python dictionary is returned. Joining is done by merging nesting structures of arbitrary depth, while maintaining order. >>> import pysisl >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_1: !list {_1: !str "a"}, _2: !str "list"}}']) {"abc": ['I', ['am', 'a'], 'list']} >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_2: !list {_0: !str "a"}, _3: !str "list"}}']) {"abc": ['I', ['am'], ['a'], 'list']} ### Semantic Verification with a Schema The [jsonschema](https://pypi.org/project/jsonschema/) library is used to optionally verify the parsed SISL data structure. See [JSON Schema](https://json-schema.org/) for details on the json schema syntax. For example #### Successful Parsing >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "number" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) {'name': 'helpful_name', 'flag': False, 'count': 3} #### Schema Verification Fails >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "string" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) Traceback (most recent call last): File "/home/vagrant/pysisl/pysisl/sisl_decoder.py", line 31, in _verify_schema_if_required json_validator(flattened_sisl, schema=schema, format_checker=FormatChecker()) File "/home/vagrant/pysisl/venv/lib64/python3.6/site-packages/jsonschema/validators.py", line 934, in validate raise error jsonschema.exceptions.ValidationError: 3 is not of type 'string' Failed validating 'type' in schema['properties']['count']: {'type': 'string'} #### Conversion table | Python | SISL | | ------ | ---- | | dict | obj | | list | list | | str | str | | int | int | | float | float| | bool | bool | | None | null | ## Background The [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data), an architecture pattern describes a safe mechanism for handling structured data from an external untrusted source. We use a Transform - Verify approach taking our source data, transforming to an intermediate format, inspecting the intermediate format and then transforming back to the original format. SISL was designed to be a simple and easily inspectable intermediate format for just such an approach. OakdoorTM products enable one- or two-way data transfers between segregated networks, letting organisations safely run services, such as file transfer, protocol exchanges, secure internet browsing and systems management. This is done using a combination of hardware enforced verification and software. pySISL can form part of the transformation engine sub-system that enables cross-network communication that is compatible with the NCSC Safely importing data pattern. The pySISL encoder can be used to convert complex Python dictionaries into valid SISL that is compatible with the diodes and the decoder will convert the SISL back into the same dictionaries without loss of data. ## License MIT licence ## SISL Specification For reference, this is ABNF for SISL. sislfile = grouping *255wsp grouping = "{" ( (*255wsp collection *255wsp ) / *255wsp ) "}" collection = element *("," *255wsp element) element = name ":" 1*255wsp "!" type 1*255wsp value name = ( "_" / ALPHA ) *( "_" / "-" / "." / ALPHA / DIGIT ) type = ( "_" / ALPHA ) *254( "_" / "-" / "." / ALPHA / DIGIT ) value = ( DQUOTE *( printable / escape) DQUOTE ) / grouping escape = "\" ( lcr / lct / lcn / DQUOTE / "\" / (lcx 2HEXDIG) / (lcu 4HEXDIG) / (ucu 8HEXDIG) ) wsp = SP / HTAB / CR / LF printable = %x20-21 / %x23-5B / %x5D-7E ; Printable chars apart from '"' or '\' lcr = %x72 ; lower case r lct = %x74 ; lower case t lcn = %x6E ; lower case n lcx = %x78 ; lower case x lcu = %x75 ; lower case u ucu = %x55 ; upper case u ; Core rules ALPHA = %x41-5A / %x61-7A ; A-Z / a-z DIGIT = %x30-39 ; 0-9 DQUOTE = %x22 ; " (double-quote) SP = %x20 ; space HTAB = %x09 ; horizontal tab CR = %x0D ; carriage return LF = %x0A ; line feed ## Getting Help If you need help using the pySISL module, please contact OakdoorTM support at oakdoor.support@paconsulting.com. ## Examples |Type | Python |SISL | |--------------------|-------------------------------------------|--------------------------------------------------------------------| | Dictionary | `{"field_one": {"key_one": "teststring"}}`| `'{"field_one": !obj {"key_one": !str "teststring"}}'` | | List | `{"field_one": [1, 2, 3]}` | `'{"field_one": !list {_0: !int "1", _1: !int "2", _2: !int "3"}}'`| | Anonymous list | `[1, 2, 3]` | `'{"_": !_list {_0: !int "1", _1: !int "2", _2: !int "3"}}'` | | String | `{"field_one": "teststring"}` | `'{"field_one": !str "teststring"}'` | | Anonymous string | `"teststring"` | `'{"_": !_str "teststring"}'` | | Int | `{"field_one": 1}` | `'{"field_one": !int "1"}'` | | Anonymous int | `1` | `'{"_": !_int "1"}'` | | Float | `{"field_one": 5.3}` | `'{"field_one": !float "5.3"}'` | | Anonymous float | `5.3` | `'{"_": !_float "5.3"}'` | | Bool | `{"field_one": True}` | `'{"field_one": !bool "true"}'` | | Anonymous bool | `True` | `'{"_": !_bool "true"}'` | | None | `{"field_one": None}` | `'{"field_one": !null ""}'` | | Anonymous none | `None` | `'{"_": !_null ""}'` | ## Contributing to pySISL All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. If you notice a bug or would like to make an update to pySISL, please open an issue or raise a pull request. %package -n python3-pysisl Summary: A python library for serialising and deserialising SISL (Simple Information Serialization Language) Provides: python-pysisl BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pysisl # pySISL A Python library for serialising and deserialising SISL (Simple Information Serialization Language). SISL is a simple structured text format designed for use in the [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data). This library provides the ability to serialise and deserialise SISL as well as perform semantic verification of the SISL. Hardware enforced syntatic verification may be carried out by the [OakdoorTM family of data diodes](https://www.oakdoor.io/products/oakdoor-data-diodes/). Also provides the functionality to wrap and unwrap files with an XOR scrambling technique used on the OakdoorTM data diodes which is designed to render files inert if they fail the syntatic verification allowing the file to be safely transported or stored for later unwrapping and inspection. ## Examples Encoding basic Python object to SISL: >>> import pysisl >>> pysisl.dumps({"hello": "world"}) '{hello: !str "world"}' >>> pysisl.dumps({"name": "helpful_name", "flag": False, "count": 3}) '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' Decoding SISL to Python: >>> import pysisl >>> pysisl.loads('{name: !str "helpful_name", flag: !bool "false", count: !int "3"}') {'name': 'helpful_name', 'flag': False, 'count': 3} ## Basic Usage pysisl.dumps(obj) Serialise a basic Python object into a SISL formatted str. pysisl.loads(sisl, schema=None) Deserialise SISL str to a basic Python object. Optionally, verify the SISL schema using a json schema. pysisl.SislWrapper().wraps(data) Applies an XOR data scrambling technique to wrap and render data inert, equivalent to the OakdoorTM data diode hardware. The data must be bytes() or bytearray(). The XOR key is internally generated and prepended as part of a header. pysisl.SislWrapper().unwraps(data) Unwraps data scrambled with the above XOR data scrambling technique. The data must be bytes() or bytearray(). See the [conversion](#conversion-table) table on this page for more details. ### Splitting large objects into multiple SISL files pySISL supports a maximum length in bytes for SISL files. If the input Python object exceeds this max length it is split into multiple SISL files. A Python list is returned where each item is a SISL string. #### Split an object into SISL with max bytes as 20 >>> import pysisl >>> pysisl.dumps({"abc": 2, "def": 3}, max_length=20) ['{abc: !int "2"}', '{def: !int "3"}'] ### Joining multiple SISL files to form a single Python object If a SISL file has been split in the way described above, pySISL supports joining the split files into a single Python object. When a list of SISL strings is passed to pySISL.loads(), this joining is done by default. A single Python dictionary is returned. Joining is done by merging nesting structures of arbitrary depth, while maintaining order. >>> import pysisl >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_1: !list {_1: !str "a"}, _2: !str "list"}}']) {"abc": ['I', ['am', 'a'], 'list']} >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_2: !list {_0: !str "a"}, _3: !str "list"}}']) {"abc": ['I', ['am'], ['a'], 'list']} ### Semantic Verification with a Schema The [jsonschema](https://pypi.org/project/jsonschema/) library is used to optionally verify the parsed SISL data structure. See [JSON Schema](https://json-schema.org/) for details on the json schema syntax. For example #### Successful Parsing >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "number" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) {'name': 'helpful_name', 'flag': False, 'count': 3} #### Schema Verification Fails >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "string" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) Traceback (most recent call last): File "/home/vagrant/pysisl/pysisl/sisl_decoder.py", line 31, in _verify_schema_if_required json_validator(flattened_sisl, schema=schema, format_checker=FormatChecker()) File "/home/vagrant/pysisl/venv/lib64/python3.6/site-packages/jsonschema/validators.py", line 934, in validate raise error jsonschema.exceptions.ValidationError: 3 is not of type 'string' Failed validating 'type' in schema['properties']['count']: {'type': 'string'} #### Conversion table | Python | SISL | | ------ | ---- | | dict | obj | | list | list | | str | str | | int | int | | float | float| | bool | bool | | None | null | ## Background The [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data), an architecture pattern describes a safe mechanism for handling structured data from an external untrusted source. We use a Transform - Verify approach taking our source data, transforming to an intermediate format, inspecting the intermediate format and then transforming back to the original format. SISL was designed to be a simple and easily inspectable intermediate format for just such an approach. OakdoorTM products enable one- or two-way data transfers between segregated networks, letting organisations safely run services, such as file transfer, protocol exchanges, secure internet browsing and systems management. This is done using a combination of hardware enforced verification and software. pySISL can form part of the transformation engine sub-system that enables cross-network communication that is compatible with the NCSC Safely importing data pattern. The pySISL encoder can be used to convert complex Python dictionaries into valid SISL that is compatible with the diodes and the decoder will convert the SISL back into the same dictionaries without loss of data. ## License MIT licence ## SISL Specification For reference, this is ABNF for SISL. sislfile = grouping *255wsp grouping = "{" ( (*255wsp collection *255wsp ) / *255wsp ) "}" collection = element *("," *255wsp element) element = name ":" 1*255wsp "!" type 1*255wsp value name = ( "_" / ALPHA ) *( "_" / "-" / "." / ALPHA / DIGIT ) type = ( "_" / ALPHA ) *254( "_" / "-" / "." / ALPHA / DIGIT ) value = ( DQUOTE *( printable / escape) DQUOTE ) / grouping escape = "\" ( lcr / lct / lcn / DQUOTE / "\" / (lcx 2HEXDIG) / (lcu 4HEXDIG) / (ucu 8HEXDIG) ) wsp = SP / HTAB / CR / LF printable = %x20-21 / %x23-5B / %x5D-7E ; Printable chars apart from '"' or '\' lcr = %x72 ; lower case r lct = %x74 ; lower case t lcn = %x6E ; lower case n lcx = %x78 ; lower case x lcu = %x75 ; lower case u ucu = %x55 ; upper case u ; Core rules ALPHA = %x41-5A / %x61-7A ; A-Z / a-z DIGIT = %x30-39 ; 0-9 DQUOTE = %x22 ; " (double-quote) SP = %x20 ; space HTAB = %x09 ; horizontal tab CR = %x0D ; carriage return LF = %x0A ; line feed ## Getting Help If you need help using the pySISL module, please contact OakdoorTM support at oakdoor.support@paconsulting.com. ## Examples |Type | Python |SISL | |--------------------|-------------------------------------------|--------------------------------------------------------------------| | Dictionary | `{"field_one": {"key_one": "teststring"}}`| `'{"field_one": !obj {"key_one": !str "teststring"}}'` | | List | `{"field_one": [1, 2, 3]}` | `'{"field_one": !list {_0: !int "1", _1: !int "2", _2: !int "3"}}'`| | Anonymous list | `[1, 2, 3]` | `'{"_": !_list {_0: !int "1", _1: !int "2", _2: !int "3"}}'` | | String | `{"field_one": "teststring"}` | `'{"field_one": !str "teststring"}'` | | Anonymous string | `"teststring"` | `'{"_": !_str "teststring"}'` | | Int | `{"field_one": 1}` | `'{"field_one": !int "1"}'` | | Anonymous int | `1` | `'{"_": !_int "1"}'` | | Float | `{"field_one": 5.3}` | `'{"field_one": !float "5.3"}'` | | Anonymous float | `5.3` | `'{"_": !_float "5.3"}'` | | Bool | `{"field_one": True}` | `'{"field_one": !bool "true"}'` | | Anonymous bool | `True` | `'{"_": !_bool "true"}'` | | None | `{"field_one": None}` | `'{"field_one": !null ""}'` | | Anonymous none | `None` | `'{"_": !_null ""}'` | ## Contributing to pySISL All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. If you notice a bug or would like to make an update to pySISL, please open an issue or raise a pull request. %package help Summary: Development documents and examples for pysisl Provides: python3-pysisl-doc %description help # pySISL A Python library for serialising and deserialising SISL (Simple Information Serialization Language). SISL is a simple structured text format designed for use in the [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data). This library provides the ability to serialise and deserialise SISL as well as perform semantic verification of the SISL. Hardware enforced syntatic verification may be carried out by the [OakdoorTM family of data diodes](https://www.oakdoor.io/products/oakdoor-data-diodes/). Also provides the functionality to wrap and unwrap files with an XOR scrambling technique used on the OakdoorTM data diodes which is designed to render files inert if they fail the syntatic verification allowing the file to be safely transported or stored for later unwrapping and inspection. ## Examples Encoding basic Python object to SISL: >>> import pysisl >>> pysisl.dumps({"hello": "world"}) '{hello: !str "world"}' >>> pysisl.dumps({"name": "helpful_name", "flag": False, "count": 3}) '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' Decoding SISL to Python: >>> import pysisl >>> pysisl.loads('{name: !str "helpful_name", flag: !bool "false", count: !int "3"}') {'name': 'helpful_name', 'flag': False, 'count': 3} ## Basic Usage pysisl.dumps(obj) Serialise a basic Python object into a SISL formatted str. pysisl.loads(sisl, schema=None) Deserialise SISL str to a basic Python object. Optionally, verify the SISL schema using a json schema. pysisl.SislWrapper().wraps(data) Applies an XOR data scrambling technique to wrap and render data inert, equivalent to the OakdoorTM data diode hardware. The data must be bytes() or bytearray(). The XOR key is internally generated and prepended as part of a header. pysisl.SislWrapper().unwraps(data) Unwraps data scrambled with the above XOR data scrambling technique. The data must be bytes() or bytearray(). See the [conversion](#conversion-table) table on this page for more details. ### Splitting large objects into multiple SISL files pySISL supports a maximum length in bytes for SISL files. If the input Python object exceeds this max length it is split into multiple SISL files. A Python list is returned where each item is a SISL string. #### Split an object into SISL with max bytes as 20 >>> import pysisl >>> pysisl.dumps({"abc": 2, "def": 3}, max_length=20) ['{abc: !int "2"}', '{def: !int "3"}'] ### Joining multiple SISL files to form a single Python object If a SISL file has been split in the way described above, pySISL supports joining the split files into a single Python object. When a list of SISL strings is passed to pySISL.loads(), this joining is done by default. A single Python dictionary is returned. Joining is done by merging nesting structures of arbitrary depth, while maintaining order. >>> import pysisl >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_1: !list {_1: !str "a"}, _2: !str "list"}}']) {"abc": ['I', ['am', 'a'], 'list']} >>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', '{abc: !list {_2: !list {_0: !str "a"}, _3: !str "list"}}']) {"abc": ['I', ['am'], ['a'], 'list']} ### Semantic Verification with a Schema The [jsonschema](https://pypi.org/project/jsonschema/) library is used to optionally verify the parsed SISL data structure. See [JSON Schema](https://json-schema.org/) for details on the json schema syntax. For example #### Successful Parsing >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "number" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) {'name': 'helpful_name', 'flag': False, 'count': 3} #### Schema Verification Fails >>> import pysisl >>> my_schema = { "properties": { "name": { "type": "string" }, "flag": { "type": "boolean" }, "count": { "type": "string" } } } >>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}' >>> pysisl.loads(decode_example, my_schema) Traceback (most recent call last): File "/home/vagrant/pysisl/pysisl/sisl_decoder.py", line 31, in _verify_schema_if_required json_validator(flattened_sisl, schema=schema, format_checker=FormatChecker()) File "/home/vagrant/pysisl/venv/lib64/python3.6/site-packages/jsonschema/validators.py", line 934, in validate raise error jsonschema.exceptions.ValidationError: 3 is not of type 'string' Failed validating 'type' in schema['properties']['count']: {'type': 'string'} #### Conversion table | Python | SISL | | ------ | ---- | | dict | obj | | list | list | | str | str | | int | int | | float | float| | bool | bool | | None | null | ## Background The [NCSC Safely Importing Data Pattern](https://www.ncsc.gov.uk/guidance/pattern-safely-importing-data), an architecture pattern describes a safe mechanism for handling structured data from an external untrusted source. We use a Transform - Verify approach taking our source data, transforming to an intermediate format, inspecting the intermediate format and then transforming back to the original format. SISL was designed to be a simple and easily inspectable intermediate format for just such an approach. OakdoorTM products enable one- or two-way data transfers between segregated networks, letting organisations safely run services, such as file transfer, protocol exchanges, secure internet browsing and systems management. This is done using a combination of hardware enforced verification and software. pySISL can form part of the transformation engine sub-system that enables cross-network communication that is compatible with the NCSC Safely importing data pattern. The pySISL encoder can be used to convert complex Python dictionaries into valid SISL that is compatible with the diodes and the decoder will convert the SISL back into the same dictionaries without loss of data. ## License MIT licence ## SISL Specification For reference, this is ABNF for SISL. sislfile = grouping *255wsp grouping = "{" ( (*255wsp collection *255wsp ) / *255wsp ) "}" collection = element *("," *255wsp element) element = name ":" 1*255wsp "!" type 1*255wsp value name = ( "_" / ALPHA ) *( "_" / "-" / "." / ALPHA / DIGIT ) type = ( "_" / ALPHA ) *254( "_" / "-" / "." / ALPHA / DIGIT ) value = ( DQUOTE *( printable / escape) DQUOTE ) / grouping escape = "\" ( lcr / lct / lcn / DQUOTE / "\" / (lcx 2HEXDIG) / (lcu 4HEXDIG) / (ucu 8HEXDIG) ) wsp = SP / HTAB / CR / LF printable = %x20-21 / %x23-5B / %x5D-7E ; Printable chars apart from '"' or '\' lcr = %x72 ; lower case r lct = %x74 ; lower case t lcn = %x6E ; lower case n lcx = %x78 ; lower case x lcu = %x75 ; lower case u ucu = %x55 ; upper case u ; Core rules ALPHA = %x41-5A / %x61-7A ; A-Z / a-z DIGIT = %x30-39 ; 0-9 DQUOTE = %x22 ; " (double-quote) SP = %x20 ; space HTAB = %x09 ; horizontal tab CR = %x0D ; carriage return LF = %x0A ; line feed ## Getting Help If you need help using the pySISL module, please contact OakdoorTM support at oakdoor.support@paconsulting.com. ## Examples |Type | Python |SISL | |--------------------|-------------------------------------------|--------------------------------------------------------------------| | Dictionary | `{"field_one": {"key_one": "teststring"}}`| `'{"field_one": !obj {"key_one": !str "teststring"}}'` | | List | `{"field_one": [1, 2, 3]}` | `'{"field_one": !list {_0: !int "1", _1: !int "2", _2: !int "3"}}'`| | Anonymous list | `[1, 2, 3]` | `'{"_": !_list {_0: !int "1", _1: !int "2", _2: !int "3"}}'` | | String | `{"field_one": "teststring"}` | `'{"field_one": !str "teststring"}'` | | Anonymous string | `"teststring"` | `'{"_": !_str "teststring"}'` | | Int | `{"field_one": 1}` | `'{"field_one": !int "1"}'` | | Anonymous int | `1` | `'{"_": !_int "1"}'` | | Float | `{"field_one": 5.3}` | `'{"field_one": !float "5.3"}'` | | Anonymous float | `5.3` | `'{"_": !_float "5.3"}'` | | Bool | `{"field_one": True}` | `'{"field_one": !bool "true"}'` | | Anonymous bool | `True` | `'{"_": !_bool "true"}'` | | None | `{"field_one": None}` | `'{"field_one": !null ""}'` | | Anonymous none | `None` | `'{"_": !_null ""}'` | ## Contributing to pySISL All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. If you notice a bug or would like to make an update to pySISL, please open an issue or raise a pull request. %prep %autosetup -n pysisl-0.0.11 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-pysisl -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 0.0.11-1 - Package Spec generated