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python2-meld3-1.0.2-3.lbn25.noarch
meld3 is an HTML/XML templating system for Python 2.5+ which keeps template markup and dynamic rendering logic separate from one another.
Located in LBN / … / Plone and Zope / BastionLinux 25
python2-nose-1.3.7-19.lbn25.py37.noarch
nose extends the test loading and running features of unit test, making it easier to write, find and run tests. By default, nose will run tests in files or directories under the current working directory whose names include "test" or "Test" at a word boundary (like "test_this" or "functional_test" or "TestClass" but not "libtest"). Test output is similar to that of unit test, but also includes captured stdout output from failing tests, for easy print-style debugging. These features, and many more, are customizable through the use of plugins. Plugins included with nose provide support for doctest, code coverage and profiling, flexible attribute-based test selection, output capture and more.
Located in LBN / … / Plone and Zope / BastionLinux 25
librdkafka-2.4.0-1.lbn36.x86_64
Librdkafka is a C/C++ library implementation of the Apache Kafka protocol, containing both Producer and Consumer support. It was designed with message delivery reliability and high performance in mind, current figures exceed 800000 messages/second for the producer and 3 million messages/second for the consumer.
Located in LBN / … / Data Science / BastionLinux 36
python3-fastavro-1.9.4-2.lbn36.x86_64
Because the Apache Python avro package is written in pure Python, it is relatively slow. In one test case, it takes about 14 seconds to iterate through a file of 10,000 records. By comparison, the JAVA avro SDK reads the same file in 1.9 seconds. The fastavro library was written to offer performance comparable to the Java library. With regular CPython, fastavro uses C extensions which allow it to iterate the same 10,000 record file in 1.7 seconds. With PyPy, this drops to 1.5 seconds (to be fair, the JAVA benchmark is doing some extra JSON encoding/decoding). Supported Features • File Writer • File Reader (iterating via records or blocks) • Schemaless Writer • Schemaless Reader • JSON Writer • JSON Reader • Codecs (Snappy, Deflate, Zstandard, Bzip2, LZ4, XZ) • Schema resolution • Aliases • Logical Types • Parsing schemas into the canonical form • Schema fingerprinting Missing Features • Anything involving Avro’s RPC features
Located in LBN / … / Data Science / BastionLinux 36
python3-fastavro+lz4-1.9.4-2.lbn36.x86_64
This is a metapackage bringing in lz4 extras requires for python3-fastavro. It makes sure the dependencies are installed.
Located in LBN / … / Data Science / BastionLinux 36
python3-fastavro+zstandard-1.9.4-2.lbn36.x86_64
This is a metapackage bringing in zstandard extras requires for python3-fastavro. It makes sure the dependencies are installed.
Located in LBN / … / Data Science / BastionLinux 36
python3-google-analytics-admin-0.22.7-1.lbn36.noarch
Python Client for Analytics Admin |preview| |pypi| |versions|Analytics Admin_: allows you to manage Google Analytics accounts and properties.- Client Library Documentation_ - Product Documentation_.. |previe .. |pyp .. |versions| image::
Located in LBN / … / Data Science / BastionLinux 36
python3-hdfs+kerberos-2.7.3-1.lbn36.noarch
This is a metapackage bringing in kerberos extras requires for python3-hdfs. It makes sure the dependencies are installed.
Located in LBN / … / Data Science / BastionLinux 36
python3-immutabledict-4.2.1-2.lbn36.noarch
Implements the complete mapping interface and can be used as a drop-in replacement for dictionaries where immutability is desired. The immutabledict constructor mimics dict, and all of the expected interfaces (iter, len, repr, hash, getitem) are provided.
Located in LBN / … / Data Science / BastionLinux 36
python3-pinecone-client-4.1.2-1.lbn36.noarch
Pinecone Python Client The official Pinecone Python client. For more information, see the docs at https:/www.pinecone.io/docs/ Documentation If you are upgrading from a 2.2.x version of the client, check out the v3 Migration Guide. Reference Documentation Example code Many of the brief examples shown in this README are using very small vectors to keep the documentation concise, but most real world usage will involve much larger embedding vectors. To see some more realistic examples of how this client can be used, explore some of our many Jupyter notebooks in the examples repository. Prerequisites The Pinecone Python client is compatible with Python 3.8 and greater. Installation There are two flavors of the Pinecone python client. The default client installed from PyPI as pinecone-client has a minimal set of dependencies and interacts with Pinecone via HTTP requests. If you are aiming to maximimize performance, you can install additional gRPC dependencies to access an alternate clie
Located in LBN / … / Data Science / BastionLinux 36

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