Search results

python3-arrow-1.2.3-12.lbn36.noarch

Arrow is a Python library that offers a sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps. It implements and updates the datetime type, plugging gaps in functionality, and provides an intelligent module API that supports many common creation scenarios. Simply put, it helps you work with dates and times with fewer imports and a lot less code.

python3-asana-5.0.0-1.lbn36.noarch

Python client library for Asana.Authentication -- Personal Access TokenCreate a client using your Asana Personal Access Token: client asana.Client.access_token('PERSONAL_ACCESS_TOKEN') OAuth 2Asana supports OAuth 2. asana handles some of the details of the OAuth flow for you.

python3-asgiref-3.8.1-1.lbn36.noarch

ASGI is a standard for Python asynchronous web apps and servers to communicate with each other, and positioned as an asynchronous successor to WSGI. You can read more at package includes ASGI base libraries, such as:* Sync-to-async and async-to-sync function wrappers, asgiref.sync * Server base classes, asgiref.server * A WSGI-to-ASGI adapter, in asgiref.wsgi

python3-asgiref-3.8.1-1.lbn36.noarch

ASGI is a standard for Python asynchronous web apps and servers to communicate with each other, and positioned as an asynchronous successor to WSGI. You can read more at package includes ASGI base libraries, such as:* Sync-to-async and async-to-sync function wrappers, asgiref.sync * Server base classes, asgiref.server * A WSGI-to-ASGI adapter, in asgiref.wsgi

python3-asgiref-3.8.1-1.lbn36.noarch

ASGI is a standard for Python asynchronous web apps and servers to communicate with each other, and positioned as an asynchronous successor to WSGI. You can read more at package includes ASGI base libraries, such as:* Sync-to-async and async-to-sync function wrappers, asgiref.sync * Server base classes, asgiref.server * A WSGI-to-ASGI adapter, in asgiref.wsgi

python3-asn1crypto-1.3.0-1.lbn25.noarch

Fast ASN.1 parser and serializer with definitions for private keys, public keys, certificates, CRL, OCSP, CMS, PKCS#3, PKCS#7, PKCS#8, PKCS#12, PKCS#5, X.509 and TSP.

python3-asn1crypto-1.5.1-1.lbn36.noarch

Python has long had the pyasn1 and pyasn1_modules available for parsing and serializing ASN.1 structures. While the project does include a comprehensive set of tools for parsing and serializing, the performance of the library can be very poor, especially when dealing with bit fields and parsing large structures such as CRLs. After spending extensive time using pyasn1, the following issues were identified: Poor performance Verbose, non-pythonic API Out-dated and incomplete definitions in pyasn1-modules No simple way to map data to native Python data structures No mechanism for overridden universal ASN.1 types The pyasn1 API is largely method driven, and uses extensive configuration objects and lowerCamelCase names. There were no consistent options for converting types of native Python data structures. Since the project supports out-dated versions of Python, many newer language features are unavailable for use. Time was spent trying to profile issues with the performance, however the architecture made it hard to pin down the primary source of the poor performance. Attempts were made to improve performance by utilizing unreleased patches and delaying parsing using the Any type. Even with such changes, the performance was still unacceptably slow. Finally, a number of structures in the cryptographic space use universal data types such as BitString and OctetString, but interpret the data as other types. For instance, signatures are really byte strings, but are encoded as BitString. Elliptic curve keys use both BitString and OctetString to represent integers. Parsing these structures as the base universal types and then re-interpreting them wastes computation. asn1crypto uses the following techniques to improve performance, especially when extracting one or two fields from large, complex structures: Delayed parsing of byte string values Persistence of original ASN.1 encoded data until a value is changed Lazy loading of child fields Utilization of high-level Python stdlib modules While there is no extensive performance test suite, the CRLTests.test_parse_crl test case was used to parse a 21MB CRL file on a late 2013 rMBP. asn1crypto parsed the certificate serial numbers in just under 8 seconds. With pyasn1, using definitions from pyasn1-modules, the same parsing took over 4,100 seconds. For smaller structures the performance difference can range from a few times faster to an order of magnitude or more.

python3-asn1crypto-1.5.1-1.lbn36.noarch

Python has long had the pyasn1 and pyasn1_modules available for parsing and serializing ASN.1 structures. While the project does include a comprehensive set of tools for parsing and serializing, the performance of the library can be very poor, especially when dealing with bit fields and parsing large structures such as CRLs. After spending extensive time using pyasn1, the following issues were identified: Poor performance Verbose, non-pythonic API Out-dated and incomplete definitions in pyasn1-modules No simple way to map data to native Python data structures No mechanism for overridden universal ASN.1 types The pyasn1 API is largely method driven, and uses extensive configuration objects and lowerCamelCase names. There were no consistent options for converting types of native Python data structures. Since the project supports out-dated versions of Python, many newer language features are unavailable for use. Time was spent trying to profile issues with the performance, however the architecture made it hard to pin down the primary source of the poor performance. Attempts were made to improve performance by utilizing unreleased patches and delaying parsing using the Any type. Even with such changes, the performance was still unacceptably slow. Finally, a number of structures in the cryptographic space use universal data types such as BitString and OctetString, but interpret the data as other types. For instance, signatures are really byte strings, but are encoded as BitString. Elliptic curve keys use both BitString and OctetString to represent integers. Parsing these structures as the base universal types and then re-interpreting them wastes computation. asn1crypto uses the following techniques to improve performance, especially when extracting one or two fields from large, complex structures: Delayed parsing of byte string values Persistence of original ASN.1 encoded data until a value is changed Lazy loading of child fields Utilization of high-level Python stdlib modules While there is no extensive performance test suite, the CRLTests.test_parse_crl test case was used to parse a 21MB CRL file on a late 2013 rMBP. asn1crypto parsed the certificate serial numbers in just under 8 seconds. With pyasn1, using definitions from pyasn1-modules, the same parsing took over 4,100 seconds. For smaller structures the performance difference can range from a few times faster to an order of magnitude or more.

python3-asn1crypto-1.5.1-1.lbn36.noarch

Python has long had the pyasn1 and pyasn1_modules available for parsing and serializing ASN.1 structures. While the project does include a comprehensive set of tools for parsing and serializing, the performance of the library can be very poor, especially when dealing with bit fields and parsing large structures such as CRLs. After spending extensive time using pyasn1, the following issues were identified: Poor performance Verbose, non-pythonic API Out-dated and incomplete definitions in pyasn1-modules No simple way to map data to native Python data structures No mechanism for overridden universal ASN.1 types The pyasn1 API is largely method driven, and uses extensive configuration objects and lowerCamelCase names. There were no consistent options for converting types of native Python data structures. Since the project supports out-dated versions of Python, many newer language features are unavailable for use. Time was spent trying to profile issues with the performance, however the architecture made it hard to pin down the primary source of the poor performance. Attempts were made to improve performance by utilizing unreleased patches and delaying parsing using the Any type. Even with such changes, the performance was still unacceptably slow. Finally, a number of structures in the cryptographic space use universal data types such as BitString and OctetString, but interpret the data as other types. For instance, signatures are really byte strings, but are encoded as BitString. Elliptic curve keys use both BitString and OctetString to represent integers. Parsing these structures as the base universal types and then re-interpreting them wastes computation. asn1crypto uses the following techniques to improve performance, especially when extracting one or two fields from large, complex structures: Delayed parsing of byte string values Persistence of original ASN.1 encoded data until a value is changed Lazy loading of child fields Utilization of high-level Python stdlib modules While there is no extensive performance test suite, the CRLTests.test_parse_crl test case was used to parse a 21MB CRL file on a late 2013 rMBP. asn1crypto parsed the certificate serial numbers in just under 8 seconds. With pyasn1, using definitions from pyasn1-modules, the same parsing took over 4,100 seconds. For smaller structures the performance difference can range from a few times faster to an order of magnitude or more.

python3-asn1crypto-tests-1.5.1-1.lbn36.noarch

asn1crypto_testsRun the test suite via:bash python -m asn1crypto_tests Full documentation a <