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python3-beautifulsoup4-4.4.1-1.lbn19.noarch: Beautiful Soup is a Python HTML/XML parser designed for quick turnaround projects like screen-scraping. Three features make it powerful: Beautiful Soup won't choke if you give it bad markup. Beautiful Soup provides a few simple methods and Pythonic idioms for navigating, searching, and modifying a parse tree. Beautiful Soup automatically converts incoming documents to Unicode and outgoing documents to UTF-8. Beautiful Soup parses anything you give it. Valuable data that was once locked up in poorly-designed websites is now within your reach. Projects that would have taken hours take only minutes with Beautiful Soup. This is the Python 3 build of Beautiful Soup.

python3-PyHDFS-0.1.1-1.lbn19.noarch: Python WebHDFS client Because the world needs yet <https://github.com/spotify/snakebite>_ another <https://github.com/ProjectMeniscus/pywebhdfs>_ way <https://pypi.python.org/pypi/hdfs>_ to talk to HDFS from Python.Usage This library provides a Python client for WebHDFS <https://hadoop.apac he.org/docs/current/hadoopprojectdist/hadoophdfs/WebHDFS.html>_. NameNode HA is supported if you pass ...

python3-Cython-0.24.1-31.lbn19.x86_64: This is a development version of Pyrex, a language for writing Python extension modules. For more info, see: Doc/About.html for a description of the language INSTALL.txt for installation instructions USAGE.txt for usage instructions Demos for usage examples

python3-Bottleneck-0.6.0-9.lbn19.x86_64: python3-Bottleneck is a collection of fast NumPy array functions written in Cython.

python3-3.4.2-6.lbn19.x86_64: Python 3 is a new version of the language that is incompatible with the 2.x line of releases. The language is mostly the same, but many details, especially how built-in objects like dictionaries and strings work, have changed considerably, and a lot of deprecated features have finally been removed.

python2-snakebite-2.11.0-1.lbn19.noarch: Snakebite is a python library that provides a pure python HDFS client and a wrapper around Hadoops minicluster. The client uses protobuf for communicating with the NameNode and comes in the form of a library and a command line interface. Currently, the snakebite client supports most actions that involve the Namenode and reading data from DataNodes.

python2-grafyaml-0.0.5-1.lbn19.noarch: grafyaml Grafyaml takes simple descriptions of Grafana dashboards in YAML format, and uses them to configure Grafana.* Free software: Apache license * Documentation: http://docs.openstack.org/infra/grafyaml/ * Source: http://git.openstack.org/cgit/openstackinfra/grafyaml * Bugs: https://storyboard.openstack.org/!/project/818Features

python2-PyHDFS-0.1.1-1.lbn19.noarch: Python WebHDFS client Because the world needs yet <https://github.com/spotify/snakebite>_ another <https://github.com/ProjectMeniscus/pywebhdfs>_ way <https://pypi.python.org/pypi/hdfs>_ to talk to HDFS from Python.Usage This library provides a Python client for WebHDFS <https://hadoop.apac he.org/docs/current/hadoopprojectdist/hadoophdfs/WebHDFS.html>_. NameNode HA is supported if you pass ...

python-rpy2-2.8.3-1.lbn19.x86_64: Python interface to the R language (embedded R)

prometheus-snmp-exporter-0.0.5-1.lbn19.noarch: See https://github.com/prometheus/snmp_exporter/blob/master/README.md for documentation.

prometheus-pushgateway-0.3.0-1.gitc3b9ef4.lbn19.x86_64: The Prometheus Pushgateway exists to allow ephemeral and batch jobs to expose their metrics to Prometheus. Since these kinds of jobs may not exist long enough to be scraped, they can instead push their metrics to a Pushgateway. The Pushgateway then exposes these metrics to Prometheus. The Pushgateway is explicitly not an aggregator, but rather a metrics cache. It does not have a statsd-like semantics. The metrics pushed are exactly the same as you would present for scraping in a permanently running program. For machine-level metrics, the textfile collector of the Node exporter is usually more appropriate. The Pushgateway is best used for service-level metrics.

prometheus-promu-0.0.0-1.gitd007363.lbn19.x86_64: promu is the utility tool for Prometheus projects Usage: promu [flags] promu [command] Available Commands: build Build a Go project crossbuild Crossbuild a Go project using Golang builder Docker images info Print info about current project and exit release Upload tarballs to the Github release tarball Create a tarball from the builded Go project version Print the version and exit Flags: --config string Config file (default is ./.promu.yml) -v, --verbose Verbose output --viper Use Viper for configuration (default true) Use "promu [command] --help" for more information about a command.

prometheus-cli-0.3.0-1.gita5c0897.lbn19.x86_64: Usage: prometheus-cli [flags] query <expression> prometheus-cli [flags] query_range <expression> <end_timestamp> <range_seconds> [<step_seconds>] prometheus-cli [flags] metrics Flags: -csv=true: Whether to format output as CSV -csvDelimiter=";": Single-character delimiter to use in CSV output -server="": URL of the Prometheus server to query -timeout=1m0s: Timeout to use when querying the Prometheus server

prometheus-alertmanager-0.3.0-1.git97eca6d.lbn19.x86_64: The Alertmanager handles alerts sent by client applications such as the Prometheus server. It takes care of deduplicating, grouping, and routing them to the correct receiver integration such as email, PagerDuty, or OpsGenie. It also takes care of silencing and inhibition of alerts.

prometheus-1.2.1-1.lbn19.x86_64: Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

packetbeat-5.0.0-3.rc1.b85820f.lbn19.x86_64: Packetbeat is an open source network packet analyzer that ships the data to Elasticsearch. Think of it like a distributed real-time Wireshark with a lot more analytics features. The Packetbeat shippers sniff the traffic between your application processes, parse on the fly protocols like HTTP, MySQL, PostgreSQL, Redis or Thrift and correlate the messages into transactions. For each transaction, the shipper inserts a JSON document into Elasticsearch, where it is stored and indexed. You can then use Kibana to view key metrics and do ad-hoc queries against the data. To learn more about Packetbeat, check out https://www.elastic.co/products/beats/packetbeat.

opentsdb-2.2.0-1.lbn19.noarch: OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase. OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable. Thanks to HBase's scalability, OpenTSDB allows you to collect many thousands of metrics from thousands of hosts and applications, at a high rate (every few seconds). OpenTSDB will never delete or downsample data and can easily store billions of data points.

nodejs-elasticsearch-browser-12.0.0-1.lbn19.noarch: The official low-level Elasticsearch client, for use in the browser.

nodejs-elasticsearch-12.0.0-1.lbn19.noarch: The official low-level Elasticsearch client for Node.js and the browser.


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