Saravanan666/pypi-org huggingface dataset:
Package: ccm-java8
ccm-java8ccm-java8is aCCMextension that explicitly sets theJAVA_HOMEenvironment variable for all CCM-managed
Cassandra nodes (and related tools) to an available Java 8 installation, which is required to run Cassandra 3.11 and lower.Platforms Currently Supported:macOSLinuxArchDebian-basedRHEL-basedUsageccm-java8is available onPyPI.Install it alongside CCM:pip install ccm ccm-java8Run CCM commands as normal.Cassandra and various tools will launch using the Java 8 VM.If no Java 8 VM can be found, CCM will refuse to start.
Install Java 8 if this occurs.MotivationMany operating systems support the side-by-side installation of multiple Java versions, yet only one version can be selected as the default
(i.e., what version ofjavais on$PATH).Cassandra'sbin/cassandralaunch script prefers thejavabinary under$JAVA_HOME, and will fallback to using thejavabinary on$PATHif$JAVA_HOMEisn't set.
Hence, unless$JAVA_HOMEor the platform default is explicitly set to a Java 8 installation, Cassandra will try, and fail, to start under an incompatible Java version.ccm-java8works by registering a CCM extension that when loaded by CCM explicitly sets theJAVA_HOMEenvironment variable to a directory containing a Java 8 installation, or throws an exception otherwise.Older versions used to register a hook into theappend_to_server_envfunction, but this function doesn't get called for tools (nodetool,sstabledump, etc.).
The current version sets theJAVA_HOMEenvironment variable globally in the CCM Python process, which gets inherited by all sub-processes launched by CCM.
Package: ccnet
ccnetCcnet, cell-cell network, is a single-cell RNA sequencing data analysis package based on non-uniform epsilon-neighborhood network (NEN).FeaturesDifferent from the traditional analysis of scRNA-seq data, which performs visualization, clustering and trajectory inference using methods based on different theories,ccnetaccomplishes the three targets in a consistent manner.NEN network combines the advantages of both k-neighbors (KNN) and epsilon-neighborhood (EN) to represent the intrinsic manifold of data.InstallationInstallccnetfrom pip:pip install ccnetOr, to build and install run from source:python setup.py installUsageFor the usage ofccnet, please refer to theexample, where we introduce the relevant analysis steps, including visualization, clustering, pseudotime ordering, finding trajectory-associated genes, etc.ContributeSource Code:https://github.com/Just-Jia/ccNet.gitContactsMy email:junbo_jia@163.comLicenseThe project is licensed under the GNU GPLv3 license.
Package: ccobra
Cognitive COmputation for Behavioral Reasoning Analysis (CCOBRA) Framework[API Documentation][Online Model Evaluation Platform]InstallationPyPiCCOBRA is available viapip. To install the current version, run the following command:$> pip install ccobrato update your installation, runpip install -U ccobra.Development VersionIt is also possible to install a development version of CCOBRA. The difference to the standard version is that changes to the local copy of the repository are directly reflected in the module loaded from Python viaimport. To install the develop version, download a local copy of the repository and run the following commands:$> cd /path/to/repository/
$> python setup.py develop [--user]To remove the development version, run the following commands:$> cd /path/to/repository
$> python setup.py develop [--user] --uninstall
Package: ccode
# ccode
copyright by author: Mohammed Hamza
The date the library was established : 2023/3/13Description of the library :
A library that encodes and runs any script that has been encrypted through the library in order to preserve the confidentiality of the code and preserve it from theft and preserve the programming rights of the programmer. The Lib99 library is a library that specializes in encryption and uses several offices inside it and uses a special type of encryption that was programmed in 2023 month The third on the 13th
and u need install pycryptodome library using pip install pycryptodome commandFunctions that can be used within the library:
encode:
to encrypt the codelaunch:
In order to run the code and maintain its confidentiality
Package: ccomplex
improved representation of Python complex numbersFree software: BSD 2-Clause LicenseInstallationpip install ccomplexYou can also install the in-development version with:pip install git+ssh://git@https://github.com/urbanij/ccomplex/urbanij/python-ccomplex.git@masterDocumentationhttps://python-ccomplex.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2019-11-21)First release on PyPI.
Package: cconfig
A cascading configuration file object built on top of the ConfigParserLoad a series of configuration files where later files shadow earlierFor example loading 3 configuration files in order:default:[main]
foo: 1
bar: 2
baz: 3user (~/.foo_module):[main]
foo: 4
bar: 5local (./foo_module):[main]
foo: 7Will result in:foo == 7
bar == 5
baz == 3Also, parse command line options such as:./script.py main foo 10
Package: cconvert
# Terminal-currency-converterThis is a rest based service written with python that uses the existinghttps://api.ratesapi.ioservice to get the JSON output for all the currencies with respect to a base currency. Usually the base currency can be altered according to the users needs.A simple get call example can explain the working`https://api.ratesapi.io/api/latest?base=USD`The above example returns a JSON that contains the corresponding values of the present day currency with respect to the base currency provided in the URL.## InstallationUse the package manager [pip](https://pypi.org/project/cconvert/) to install cconvert.` pip install cconvert `## Usage` cconvert 1 usd inr `## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.## License
[MIT](https://choosealicense.com/licenses/mit/)
Package: ccore
ccore  by Python CAPI Extention LibraryOverviewTODOGoalTODOImplementationTODOInstall$ pip install ccoreUnInstall$ pip uninstall ccoreRequirementpython2.7.python3.6 later.LiscenseMIT Liscenserun command EnvironmentWindowsLinuxMac OSXUsageTODOExampleTODOPerfomanceTODOLibraries usedTODOReferences usedTODO
Package: ccore-coral
Coral (c-core)Docker image buildBuilding your own docker image is optional. You can use the pre-built image from docker hub.dockerbuild.-tcoral-fdockerfile/DockerfileRunning from built docker imagedockerrun--rm-v".\data:/data"coral-u"/data/For_Curtain_Raw_PPM1H- PROTAC_TP.txt"-a"/data/annotation.txt"-o"/data/output.txt"-c"/data/comparison.txt"-x"T: Index,T: Gene"Running from docker hub imagedockerrun--rm-v".\data:/data"noatgnu/coral:0.0.1-u"/data/For_Curtain_Raw_PPM1H- PROTAC_TP.txt"-a"/data/annotation.txt"-o"/data/output.txt"-c"/data/comparison.txt"-x"T: Index,T: Gene"Pip installInstall R and setR_HOMEenvironment variable to the R installation directory as well as install the QFeatures package and its dependencies.pipinstallccore-coralRunning from pip installcoral-u"/data/For_Curtain_Raw_PPM1H- PROTAC_TP.txt"-a"/data/annotation.txt"-o"/data/output.txt"-c"/data/comparison.txt"-x"T: Index,T: Gene"CLI Usageusage:coral[-h][-uunprocessed][-aannotation][-ooutput][-ccomparison][-xindex][-fcolumn_na_filter_threshold][-rrow_na_filter_threshold][-iimputation_method][-nnormalization_method][-gaggregation_method][-taggregation_column]-uunprocessed,--unprocessedunprocessedFilepathtotheunprocesseddatafile.-aannotation,--annotationannotationFilepathtotheannotationfile.-ooutput,--outputoutputFilepathtotheoutputfile.-ccomparison,--comparisoncomparisonFilepathtothecomparisonfile.-xindex,--indexindexColumnnamestobeusedasindex.-fcolumn_na_filter_threshold,--column_na_filter_thresholdcolumn_na_filter_thresholdThresholdforcolumn-wiseNAfiltering.-rrow_na_filter_threshold,--row_na_filter_thresholdrow_na_filter_thresholdThresholdforrow-wiseNAfiltering.-iimputation_method,--imputation_methodimputation_methodMethodforimputation.-nnormalization_method,--normalization_methodnormalization_methodMethodfornormalization.-gaggregation_method,--aggregation_methodaggregation_methodMethodforaggregation.-taggregation_column,--aggregation_columnaggregation_columnColumnnametobeusedforaggregation.Usage as a moduleimportpandasaspdfromcoral.dataimportCoralcore=Coral()# Read in the unprocessed datacore.load_unproccessed_file("data/For_Curtain_Raw_PPM1H- PROTAC_TP.txt")# Add sample column namescore.add_sample("...")# Add condition or group namescore.add_condition("...")# Add sample group mappingcore.add_condition_map("condition_name","sample_name")# Add comparisoncore.add_comparison("condition_A","condition_B","comparison_name")# Add index columnscore.index_columns=["index_column_name"]# Filter column by NAcore.filter_missing_columns(0.7)# Create QFeatures objectcore.prepare()# Filter row by NAcore.filter_missing_rows(0.7)# Impute missing valuescore.impute("knn")# log2 transformcore.log_transform()# aggregate featurescore.aggregate_features("new_feature_column")# normalizecore.normalize()# Prepare limma matrixcore.prepare_for_limma()# Run limmaresults=[]fordincore.run_limma():results.append(d)iflen(results)>1:# Merge limma resultsresults=pd.concat(results)else:results=results[0]# Write resultsresults.to_csv("output.txt",sep="\t",index=False)
Package: ccorp-yaml-include
CCorp Ruamel.YAML Include ExtensionThis package extends Ruamel.YAML (a fork of PyYaml) to implement the!includetag in thecomposer, which allows the use of YAML anchors across included files. The prior way of achiving this required modifying the structure of files to invert the inclusion of files, and modifying the loading of the included file to patch in the anchors parsed thusfar. Unfortunately, this isn't possible on an existing collection of YAML files without alotof pushback from other developers, and therefore this package was developed. It processes!includetags as they are encountered by the composer rather than generating a tagged scalar to be processed by the constructor, allowing the processing to happen as a C/C++ programmer would expect, rather than defering until after composition.
Package: ccorp-yaml-include-relative-path
# CCorp Ruamel.YAML Include ExtensionThis package is exactly ccorp-yaml-include package(a fork of ccorp-yaml-include) that contains a bug fix (init of YAML didn’t accept a ‘typ’ kwargs that was a list)
It also allows to use!includetag with a relative path for aliases, e.g.
instead of just writing:
<br>!include bear_common.yaml<br>(which means that bear_common.yaml should be located in the same directory as your yaml file)you can have:
<br>*!include ../common_data/bear_common.yaml* <br>(which means that bear_common.yaml in now located in a separate folder ‘common_data’)
-version 0.0.4: a bug related to ExcludingConstructor.construct_sequence() method to miss a parameter called ‘deep’, fixed.
Package: ccp
Send an event to aChangelogserver.InstallationTo install ccp, simply:$ pip install ccpSupported severitiesINFONOTIFICATIONWARNINGERRORCRITICALExampleIt is pretty easy to use:from ccp.client import Client

client = Client("localhost", 80)
client.send("This is a simple message", "INFO", "category")You can pass a dict to specify additional HTTP headers, for example to do authentication:client.send("Message", "INFO", "category", {"Authorization": "Basic base64encoded"})You can pass a dict to specify additional database fields:client.send(“Message”, “INFO”, “category”, {“Authorization”: “Basic base64encoded”}, extra_fields={“field_1”: “value1”, “field_2”: “value2”})LoggingLogging happens into the logger calledchangelog_clientby default. You can override it by setting theloggerproperty of a client instance to aLoggerobject.Version 1.1Ability to pass extra fields in case if somebody forked the changelog server and added new db fields.Version 1.00.6b becomes stable 1.0 versionVersion 0.6bFixed Basic Authorization example in READMEVersion 0.5bAdded SSL supportVersion 0.4bAdded better logging thanks to abesto (https://github.com/abesto)Added support for passing severity directly as an int thanks to abesto (https://github.com/abesto)Add support for passing extra headers thanks to abesto (https://github.com/abesto)Version 0.3bInitial release
Package: ccp4ED
Electron diffraction toolsSome python wrappers for common electron diffraction simulation codes and utilities for continuous rotation electron diffraction.Some figures producedBloch wave simulations performed for diamond.N denotes the configuration :N=2 for 2 strongly excited beams,N=4+2w for 4 strongly exited beams and 2 weak contributing beams,
r1 for a random orientation.Nabc233+1w44+2wr1a) Setup displaying excitation errors (orange map) and structure factor (diamond) at this beam orientation.
b) Intensity I_z as function of thickness for selected beams.
c) Rocking curve for selected beam at various thicknesses.
Package: cc-pathlib
In shortThis libray propose to extend the capabilities of pathlib.
The Path class provided here is a sub-class of the original pathlib.Path class.It especially enable an easy interaction with widespread file formats like json, pickle or tsv files, plain or compressed.Options are mostly not setable, this package was meant to fit my needs, not all :D.from cc_pathlib import PathIn detailPath.make_dirs(self, umask='shared')is an equivalent ofPath.mkdir(parents=True, exists_ok=True), with the added possibility to set a umask to each directory created in-between. Especially, the default value is 'shared' for a mask value of 0o2770 (which means: available for read and write access to user and group but not others, and gid set such as each new file or directory created subsequently keep this properties).Path.make_parents(self, umask='shared')same asPath.make_dirs(self, umask='shared')but works on files, it create the whole directory structure above it. It does not create the file though.Path.delete(self, content_only=False)delete recursively if thePathis a directory. Ifcontent_only=Trueit keeps the root directory once emptied.Path.or_archivereturn the name of a corresponding archive if it exists. Looking at the following extensions, in this order,.br,.lz,.gz. This function is meant to work on files, not on complex archives like.tarfiles.Path.load(self, encoding='utf-8')is an auto-loader. The type of file is guessed from the extensionThe auto-loaderThe auto-loader works in two steps :if the file is compressed with one of the following extensions, it is first unzipped :.gzfor gzip.brfor brotli.lzfor lzipif the file match one of the following filter, the content is properly parsed, and only the resulting object is returned:.picklefor a pickled file.jsonfor a json data structure.tsvfor a tab separated value type of file, returned as alist()oflist()ofstr(). The complete spec of a.tsvfile is described below
Package: cc-pathplanner
Complete coverage Path Planning (CCPP)What is it useful for?This repository contains a program which generates a guidance trajectory for complete 2D coverage. It can be used for operations where complete coverage of an Area of Interest (AoI) is required, for land or marine applications.How to use the programTo use the program, runcoverage_path_planner.cpp(input_file, params). It returns a list of coordinates that compose a path for complete coverage.
In the input file, describe the boundaries of the AoI using its lat-lon coordinates like this:lat1  lon1
  lat2  lon2
  ...
  lat1  lon1
  NaN  NaNEnsure that the AoI is a closed polygon, by keeping the first coordinate the same as the last coordinate. Separate different polygons by including aNaN NaNat the end. Also ensure that the coordinates of the polygon are described clockwise, and counter-clockwise for any obstacles and forbidden regions.coverage_path_planner.find_min(input_file, params)runs a single objective optimizer to find the driving angle that minimizes the trajectory length for a given AoI and the specified parameters.##Example usagefrom cc_pathplanner import coverage_path_planner

def main():
	n_clusters=4	#number of sections
	r=2	#radius for Dubins curves
	input_file='sample_area.txt' #location of the input file containing coordinates of the field
	width = 10	#distance between tracks
	driving_angle=90	#angle wrt X-axis in degrees
	no_hd=0	#number of margins around boundary (each with distance=0.5*width) if needed, otherwise 0
	
	op=coverage_path_planner.cpp(input_file,num_hd=no_hd,width=width,theta=driving_angle,num_clusters=n_clusters,radius=r,visualize=False) # returns list of waypoint coordinates composing trajectory
	print('The trajectory for full coverage consists of the following waypoints:',op)
	min=coverage_path_planner.find_min(input_file)  # runs optimizer and returns angle corresponding to minimum path length
	print('Angle for trajectory with minimum length:', min)

if __name__ == '__main__':
	main()
Package: ccpayment
ccpaymentReference of functionsSpecific parameters: Refer to the API documentationDocument Address :https://doc.ccpayment.com/ccpayment-for-merchant/homeNameDescriptionget_support_tokenObtain the token list supported by merchantsget_token_chainObtain the list of the available networks for a certain tokencreate_orderManage 100% of your front-end interactions and use our APIs to build your own checkout page.checkout_urlSimplify your integration by utilizing CCPayment's hosted checkout page. CCPayment will generate a checkout URL to merchant, it will direct customers to CCPayment hosted checkout page to make payment.withdrawCall the withdrawal API to initiate withdrawalscheck_userCheck the Validity of Cwallet IDget_token_rateThe amount of USD converted into tokensassetsObtain details of merchant's assetsnetwork_feeObtain the network fee of a certain networkwebhookNotification of order callbacksget_order_infoObtain Order Information
Package: cc-plugin-glider
GliderDAC Compliance Checker PluginThisioos/compliance-checkerplugin supports the following sources and standards:StandardChecker NameGlider DACgliderdacInstallationConda$condainstall-cconda-forgecc-plugin-gliderPip$pipinstallcc-plugin-gliderSee theioos/compliance-checkerfor additional Installation notesUsage$compliance-checker-l
IOOScompliancecheckeravailablecheckersuites(codeversion):...-gliderdac(x.x.x)...
$compliance-checker-tgliderdac[dataset_location]See theioos/compliance-checkerfor additional Usage notesSummary of the ChecksThe checks have been designed to help data providers submit the highest quality data to the GliderDAC. Submitting uncompliant data to the DAC may result in services not working. For example, not providing the correct Sea Name in the GLobal atttributes may put your glider depoyment into the wrong region on the GliderMap. Not providing proper metadata about the platform and instruments, and attribution may prevent NCEI from archiving your data. And not making your files CF compliant could prevent the files from showing up on ERDDAP and THREDDS servers all together.High priority checksFailures in these checks should be addressed before submitting to the GliderDAC!check_required_variablescheck_dimensionscheck_lat_lon_attributescheck_time_attributescheck_pressure_depth_attributescheck_ctd_variable_attributescheck_profile_variable_attributes_and_typescheck_global_attributescheck_standard_namescheck_monotonically_increasing_timecheck_dim_no_datacheck_depth_arrayMedium priority checks:check_qc_variablescheck_primary_variable_attributescheck_trajectory_variablescheck_container_variablescheck_qartodcheck_ancillary_variablescheck_dtypecheck_valid_min_dtypecheck_valid_max_dtypeLow priority checkscheck_ioos_racheck_valid_loncheck_ncei_tablesOptional environment variablesPaths for cached text files for institution, project, instrument, and
platform authority tables can be set with the following environment variablesINSTITUTION_TABLEPROJECT_TABLEINSTRUMENT_TABLEPLATFORM_TABLEAdditionally, a cached version of the NCEIseanames.xmlfile can be provided
with a filesystem path inSEA_NAME_TABLEenvironment variable.The table below indicates the relationship of the environment variables for
cached table locations on disk to their usual remote locations.Environment VariableRemote Table LocationINSTITUTION_TABLEhttps://gliders.ioos.us/ncei_authority_tables/institutions.txtPROJECT_TABLEhttps://gliders.ioos.us/ncei_authority_tables/projects.txtINSTRUMENT_TABLEhttps://gliders.ioos.us/ncei_authority_tables/instruments.txtPLATFORM_TABLEhttps://gliders.ioos.us/ncei_authority_tables/platforms.txtSEA_NAME_TABLEhttps://www.nodc.noaa.gov/General/NODC-Archive/seanames.xml
Package: cc-plugin-ugrid
[![Build Status](https://travis-ci.org/ioos/cc-checker-ugrid.svg?branch=master)](https://travis-ci.org/ioos/cc-checker-ugrid)# UGRID Compliance Checker PluginThis is a checker for [UGRID](http://ugrid-conventions.github.io/ugrid-conventions) complianceIt works with the [IOOS Compliance Checker](https://github.com/ioos/compliance-checker)**Note this code is in a pre-release state. Check back soon for the first release**Licensed under the Apache License, Version 2.0 (the "License");you may not use this file except in compliance with the License.You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.Please see LICENSE for the full license text.For a brief overview of the attributes the UGRID Checker runs through, check [here](/checks.md).## Installation#### Clone this project```bash$ git clone git@github.com:ioos/cc-plugin-ugrid.git$ cd cc-plugin-ugrid$ python setup.py install```#### Tests should now show up when you run compliance checker```bash$ compliance-checker -lIOOS compliance checker available checker suites (code version):- UGRID (0.0.1-dev)- UGRID:1.0 (0.0.1-dev)- UGRID:latest (0.0.1-dev)- acdd (3.1.1)- acdd:1.1 (3.1.1)- acdd:1.3 (3.1.1)- acdd:latest (3.1.1)- cf (3.1.1)- cf:1.6 (3.1.1)- cf:latest (3.1.1)- ioos (3.1.1)- ioos:0.1 (3.1.1)- ioos:1.1 (3.1.1)- ioos:latest (3.1.1)- ioos_sos (3.1.1)- ioos_sos:0.1 (3.1.1)- ioos_sos:latest (3.1.1)```
Package: ccpp
Cookiecutter template for Python packageRequirementsPython 3.6+cookiecutter- template enginepoetry- dependency managementpython-fire- command line toolInstallation$pipinstallccppUsageCreate a new package$ccppnewhello-world&&cdhello-worldTest the package at the first time$pytesttestsBuilding package$poetrybuildBuilding hello-world (0.1.0)- Building sdist- Built hello-world-0.1.0.tar.gz- Building wheel- Built hello-world-0.1.0-py3-none-any.whlPublishing package to PyPI$poetrypublishPublishing hello-world (0.1.0) to PyPIUsername: guaifishPassword:- Uploading hello-world-0.1.0-py3-none-any.whl 0%- Uploading hello-world-0.1.0-py3-none-any.whl 65%- Uploading hello-world-0.1.0-py3-none-any.whl 100%- Uploading hello-world-0.1.0-py3-none-any.whl 100%- Uploading hello-world-0.1.0.tar.gz 0%- Uploading hello-world-0.1.0.tar.gz 83%- Uploading hello-world-0.1.0.tar.gz 100%- Uploading hello-world-0.1.0.tar.gz 100%LicenseCopyright © 2020guaifish.
This project isMITlicense.