Modified items

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python3-sqlalchemy-1.3.3-1.lbn25.x86_64: SQLAlchemy is an Object Relational Mapper (ORM) that provides a flexible, high-level interface to SQL databases. Database and domain concepts are decoupled, allowing both sides maximum flexibility and power. SQLAlchemy provides a powerful mapping layer that can work as automatically or as manually as you choose, determining relationships based on foreign keys or letting you define the join conditions explicitly, to bridge the gap between database and domain. This package includes the python 3 version of the module.

python3-nbsphinx-0.2.17-4.lbn25.py37.noarch: nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Unevaluated notebooks, i.e. notebooks without stored output cells, will be automatically executed during the Sphinx build process.

python3-nb2plots-0.6-4.lbn25.noarch: This package contains tools for converting from Jupyter notebooks to ReST for Sphinx, and vice versa.

python3-matplotlib-wx-3.1.1-1.lbn25.1.x86_64: WX backend for python3-matplotlib

python3-matplotlib-qt5-3.1.1-1.lbn25.1.x86_64: Qt5 backend for python3-matplotlib

python3-matplotlib-qt4-3.1.1-1.lbn25.1.x86_64: Qt4 backend for python3-matplotlib

python3-matplotlib-gtk3-3.1.1-1.lbn25.1.x86_64: GTK3 backend for python3-matplotlib

python3-matplotlib-data-fonts-3.1.1-1.lbn25.1.noarch: Fonts used by python-matplotlib

python3-matplotlib-data-3.1.1-1.lbn25.1.noarch: Data used by python-matplotlib

python3-kafka-1.4.3-1.lbn25.py37.noarch: This module provides low-level protocol support for Apache Kafka as well as high-level consumer and producer classes. Request batching is supported by the protocol as well as broker-aware request routing. Gzip and Snappy compression is also supported for message sets.

python3-jupyter-wysiwyg-0.1.9-1.lbn25.noarch: WYSIWYG editing functionality for markdown/HTML cells in Jupyter

python3-jupyter-1.0.0-2.lbn25.noarch: Install the Jupyter system, including the notebook, qtconsole, and the IPython kernel.

python3-elasticsearch-curator-5.7.6-1.lbn25.noarch: Elasticsearch Curator helps you curate, or manage, your Elasticsearch indices and snapshots by: Obtaining the full list of indices (or snapshots) from the cluster, as the actionable list Iterate through a list of user-defined filters to progressively remove indices (or snapshots) from this actionable list as needed. Perform various actions on the items which remain in the actionable list. Curator allows for many different operations to be performed to both indices and snapshots, including: Add or remove indices (or both!) from an alias Change shard routing allocation Close indices Create index Delete indices Delete snapshots Open closed indices forceMerge indices reindex indices, including from remote clusters Change the number of replicas per shard for indices rollover indices Take a snapshot (backup) of indices Restore snapshots

python3-elasticsearch-7.0.2-1.lbn25.noarch: Low level client for Elasticsearch. It's goal is to provide common ground for all Elasticsearch-related code in Python. The client's features include: - Translating basic Python data types to and from json - Configurable automatic discovery of cluster nodes - Persistent connections - Load balancing (with pluggable selection strategy) across all available nodes - Failed connection penalization (time based - failed connections won't be retried until a timeout is reached) - Thread safety - Pluggable architecture


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