common-workflow-language | CWL standards . | BPM library
kandi X-RAY | common-workflow-language Summary
kandi X-RAY | common-workflow-language Summary
GitHub repository for www.commonwl.org: CWL v1.0.x: (this repository). [Support] #Support) [GitHub stars] The Common Workflow Language (CWL) is a specification for describing analysis workflows and tools in a way that makes them portable and scalable across a\ variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. CWL is designed to meet the needs of data-intensive science, such as Bioinformatics, Medical Imaging, Astronomy, Physics, and Chemistry. CWL is developed by a multi-vendor working group consisting of organizations and individuals aiming to enable scientists to share data analysis workflows. [The CWL project is maintained on Github] and we follow the [Open-Stand.org principles for collaborative open standards development] Legally, CWL is a member project of [Software Freedom Conservancy] and is formally managed by the elected [CWL leadership team] #Leadership_Team), however every-day project decisions are made by the [CWL community] #Support) which is open for participation by anyone. CWL builds on technologies such as [JSON-LD] for data modeling and [Docker] for portable runtime environments.
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Top functions reviewed by kandi - BETA
- Load and validate a document
- Add resource properties
- Add schemas
- Resolve references
- Merge two properties
- Convert l to list
- Merge context with new context
- Expand a URL
- Generate avrold documentation
- Return HTML table of contents
common-workflow-language Key Features
common-workflow-language Examples and Code Snippets
ADD_SUBDIRECTORY(CmdParser) # that's all you would need to do to build the CmdParser library
TARGET_LINK_LIBRARIES(
${EXECUTABLE_YOU_WANT_TO_INFUSE_WITH_FUNCTIONALITY}
CmdParser
)
#include "CmdParser/include/cbicaCmdParser.h" // to shorten pat
from ipython2cwl.iotypes import CWLFilePathInput, CWLFilePathOutput
import csv
input_filename: 'CWLFilePathInput' = 'data.csv'
with open(input_filename) as f:
csv_reader = csv.reader(f)
data = [line for line in csv_reader]
number_of_lines = l
from ipython2cwl.iotypes import CWLFilePathInput, CWLFilePathOutput
import csv
input_filename: 'CWLFilePathInput' = 'data.csv'
with open(input_filename) as f:
csv_reader = csv.reader(f)
data = [line for line in csv_reader]
number_of_lines = l
Community Discussions
Trending Discussions on common-workflow-language
QUESTION
I'm using SPARQLWrapper to query a local SPARQL endpoint (using apache-jena-fuseki), and some of my queries are CONSTRUCT queries.
The query will give me valid results on web-based SPARQL interface, e.g. yasgui. When using SPARQLWrapper, the default query method will give me this error:
...ANSWER
Answered 2020-Nov-05 at 17:35SPARQLWrapper defaults to adding
&format=turtle&output=turtle&results=turtle
to the request.
SPARQLWrapper has a method setOnlyConneg
that turns off the adding of the additional query string parts.
The
WARN SPARQL Query: Unrecognize request parameter (ignored): results
happens because Fuseki does understandresults
and logs a warning about it. It is just a warning.format
is a mechanism to override the proper HTTP content negotiation mechanism because in some situations it is hard to set the HTTP headers. This does not apply to SPARQLWrapper which does correctly setAccept:
.format=turtle
isn't in the list of names for a CONSTRUCT query.ttl
is. (`turtle can be added to future version of Fuseki for completeness).
The best way is not to have the non-standard query string parameters with setOnlyConneg
. SPARQLWrapper correctly sets the "Accept:" header in the request and Fuseki has content negotiation and will work with that header.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install common-workflow-language
You can use common-workflow-language like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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