Saravanan666/pypi-org huggingface dataset:
Package: colinote
ColinoteColinote is a command-line tool for managing notes.InstallationYou can install Colinote using pip:pip install colinoteUsageTo use Colinote, simply run the colinote command followed by the action you want to perform and any relevant options.Actionsadd:Add a new note to a context.edit:Edit an existing note.delete:Delete an existing note.show: List all notes or all notes for a specific id,context or date.Options-c, --context:The context for the note.-t, --text:The text of the note.-d, --date:The date of the note (in the format "YYYY-MM-DD").-i, --id:The ID of the note.ExamplesAdd a note in default context (todo)colinote add "I did something amazing"Add a note in context "standup"colinote add "I did something amazing" -c "standup"Edit a note with id 1 and change the textcolinote edit 1 -t "I did something even more amazing"Edit a note with id 1 and change the contextcolinote edit 1 -c "standup"Delete note with id 1colinote delete 1List all notescolinote showList all notes for a specific contextcolinote show -c "work"List all notes for a specific datecolinote show -d "2023-01-01"Show a specific notecolinote show -i 1ContributingContributions are always welcome! Here are some ways to contribute:Fork the repository and make changes on your local branch.Create a pull request with your changes.Work on open issues.DevelopmentTo develop Colinote, first clone the repository:git clone https://github.com/tiakas/colinote.git`
cd colinoteThen, install the development dependencies:pip install -r requirements.txtTo run the tests, use:pytestTo build the package, use:python setup.py sdist bdist_wheelThis will create a dist directory containing the source distribution (.tar.gz) and wheel distribution (.whl) of the package.LicenseThis project is licensed under the MIT License - see the LICENSE file for details.
Package: colinws-todo
=====Django Todo List=====Todo is a simple Django app to conduct Web-based todo list.You can add your new list to do and check for some which had beed finished,or recover the finished to un-finished status.or you can delete itemsDetailed documentation is in the "docs" directory.Quick start-----------1. Add "todo" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'todo',]2. Include the todo URLconf in your project urls.py like this::url(r'^todo/', include('todo.urls')),3. Run `python manage.py makemigrations todo` to create todo models migrations.4. Run `python manage.py migrate todo` to create todo real models.5. Start the development server and visit http://127.0.0.1:8000/admin/to create a todo  (you'll need the Admin app enabled).6. Visit http://127.0.0.1:8000/todo/ to participate in the todo list.
Package: colititato
ColititatoThis is a simple command-line interface (CLI) implementation of the popular Tic Tac Toe game in Python. It allows a player to play the game with a computer player by taking turns to mark the spaces on a 3x3 grid.InstallationTo install the game, you can use pip to download and install it from PyPI:pip install colititatoUsageAfter installation, you can start the game by running the following command in your terminal:colititatoThis will start a new game and prompt the first player to make a move. The game board will be displayed in the console as follows:123456789To make a move, enter the number corresponding to the cell you want to mark (1-9) and press Enter. The cell will be marked with either "X" or "O", depending on whose turn it is. The game will continue until one of the players wins, or the game ends in a tie.DevelopmentTo develop Colinote, first clone the repository:git clone https://github.com/tiakas/colititato.git`
cd colinoteThen, install the development dependencies:pip install -r requirements.txtTo run the tests, use:pytestTo build the package, use:python setup.py sdist bdist_wheelThis will create a dist directory containing the source distribution (.tar.gz) and wheel distribution (.whl) of the package.Check the package contents:twine check dist/*Upload the package to PyPI:twine upload dist/*LicenseThis project is licensed under the MIT License - see the LICENSE file for details.ContributingContributions are always welcome! Here are some ways to contribute:Fork the repository and make changes on your local branch.Create a pull request with your changes.Work on open issues.
Package: coll
CoLL -ContinualLanguageLearningCoLL is a playground for research at the intersection of continual learning, active learning, natural language processing. CoLL provides the following two main features to natural language processing community:The implementation of typical baseline methods and the respective continual learning settings.
The interface for customized evaluation. Seedocumentationfor more details.Note:This is still very much a Work-In-Progress! Please feel free to share your wisdom.Installpipinstallcoll
Package: collaborative-filtering
Collaborative FilteringA package for collaborative filtering recommendation.RequirementsLinux-based OSPython 3.6+Get startedInstall the packageInstall fromhttps://pypi.org/:pipinstallcollaborative-filteringOr install it manually:gitclonehttps://github.com/yusanshi/collaborative-filtering.gitcdcollaborative-filtering
pipinstall.Prepare the datasetTODORunTODOTODOTODO
Package: collabutils
collabutilsUtilities for collaborative curation of data - in particular for curating cross-linguistic data viacldfbench.InstallationInstall viapipinstallcollabutilsNote that some modules have "extra" requirements, thus can only be used when these extras are
installed as well. Refer to the docs linked below for details.Curating tabular dataIn acldfbench-enabled curation workflow, it is often required to curate the
"configuration data", i.e. data in a dataset'setc/directory collaboratively -
or even share it (e.g. language lists) across multiple datasets.Thus, curating this data in collaborative spreadsheet apps, and only pulling it into
the dataset repository whencldfbench downloadis run, can be a solution.collabutilsprovides functionality to do this easilyfrom Google Sheetsfrom OwnCloud installationsCurating lexical dataWhile simple wordlists are somewhat easy to maintain as single table, this gets
considerably trickier when cognate codings are added. Thus, curating lexical
data with cognate codings can profit from specialized apps.collabutilsprovides functionality to pull down lexical data curatedin EDICTORCurating bibliographiesSources referenced in datasets are another type of data, that may be better curated
with tools tailored to bibliographical data.collabutilsprovides functionality to sync bibliographies between a dataset's
sources file andZoteroOverleaf: coming soon!
Package: collage
This package builds collages using images downloaded from
the internet. It makes a set of tiles from the images, which
are matched against the images and used to cover images which match well.The images which happen to be fitted most closely by the tiles
are rendered with the matching tiles. The resulting images resemble the
original images, but are made up entirely from minature versions of the
same images.Images are fetched according to a query, optionally provided by the user.The downloaded images are categoried by primary colour on disk.InstructionsInstall system requirements.:$ sudo apt-get install python build-essential python-dev python-virtualenv libjpeg-dev libfreetype6 libfreetype6-dev zlib1g-devOn 64-bit Ubuntu, symlink the image libraries otherwise PIL won’t work very well.:$ sudo ln -s /usr/lib/`uname -i`-linux-gnu/libfreetype.so /usr/lib/
$ sudo ln -s /usr/lib/`uname -i`-linux-gnu/libjpeg.so /usr/lib/
$ sudo ln -s /usr/lib/`uname -i`-linux-gnu/libz.so /usr/lib/Create and activate a new virtual Python environment.:$ virtualenv --no-site-packages ve
...
$ source ve/bin/activate
(ve)$Install package.:(ve)$ pip install ~/Downloads/collage-0.1.0.tar.gz
...Start creating collages.:(ve)$ collage-create "jack nicholson"
...Bugs and PatchesPlease email any bugs or patches tojohn.bywater@appropriatesoftware.net.
Package: collage-library
collageThis library helps you to enter students or employees information of a collage through specific items that library or its classes asked you.How it works?
Use the following command to install this librarypip install collageThis library has a base class and two different child classes:
1.Student: that needs (name,family,idnumber,age,phone,idclass) to display a string output of the student information.
2.Employee: that needs (name,family,idnumber,age,phone,salary(in your own currency)) to display a string output of the staff information,in addition to normal information this class will display tax price,insurance price and finally income.Use:
1:display student informationfrom collage import Student
get_date=Student(name,family,idnumber,age,phone,idclass)
print(get_date)
#you have to enter all wanted or required dataes as string format("")when you make an object from the classexample:
from collage  import Student
get_date=Student("ali","akbari","006","35","0912","A3")
print(get_date)output:
A STUDENT :information of the person is :
full name is :ali    akbari
id number is :006
age :35     phone:0912
the student class number is :A32:display employee informationfrom collage import Employee
get_date=Student(name,family,idnumber,age,phone,salary)
print(get_date)
#you have to enter all wanted or required dataes as string format("")when you make an object from the classexample:
from collage import Employee
get_date=Employee("hasan","jamali","25874","45","0912",4500000)
print(get_date)output:
AN EMPLOYEE :information of the person is :
full name is :hasan    jamali
id number is :25874
age :45     phone:0912
unpure salary :4500000
tax is :200000      insurance is :315000
total income is :3985000.0
Package: collage-maker
image collage makerInstallationpip install collage-makerDescriptionsCollage is a image combiner to combine lists of arrays.This is Collage Maker, it makes the collage with borders.You may want to set theborder_px,border_bg,directionto let it work.By default,border_px=3, border_color=[255, 255, 255, 255]Usage:fromcollage_makerimportmake_collagecollage=make_collage(images=[[image_a,image_b],[image_c,image_d,[image_f,image_g]]],direction=0,border_px=1,border_color=[0,0,0,255]).. note:: The border_color is of length 4 because images are length 4.
Package: collagen
CollagenNote: This documentation is a work in progress.Collagen is a virtual stack machine that lets you write procedures in configuration files, like JSON or YAML, that generate outputs like data,
images, or documents.
A procedure defines a sequence of operations that run in the Python environment, and the operations in a procedure pass data to each other by pushing, popping, and swapping data on the stack.
The standard toolkit (built-in) defines a turning complete set of operations that provide the backbone for scripting logic in your procedures.
You can add methods with new functionality by adding toolkits, which add methods by implementing Python functions with the new functionality and using the@cvm.methoddecorator.InstallationYou can install collagen viapip. Note that the basic installation only supports JSON procedures.pip install collagenProcedures written in JSON5, HSON, or YAML can have comments and multi-line strings. You can install support for additional configuration file formats via extra requirements.pip install collagen[json5,hson]If you're developing a collagen toolkit, include thedevanddocsextra
requirements.pip install "collagen[dev,docs]"
Package: collagraph
Collagraph 📓Reactive user interfaces.The wordCollagraphyis derived from the Greek wordkollorkolla, meaning glue, and graph, meaning the activity of drawing.Inspired by Vue and React.FeaturesWrite your Python interfaces in a declarative manner with plain render functions, component classes or even single-file components using Vue-like syntax, but with Python!Reactivity (made possible by leveragingobserv)Function componentsClass components with local state and life-cycle methods/hooksSingle-file components with Vue-like syntax (.cgxfiles)Custom renderersHere is an example that shows a simple counter, made with a function component:fromPySide6importQtWidgetsfromobservimportreactiveimportcollagraphascg# Declare some reactive statestate=reactive({"count":0})# Define function that adjusts the statedefbump():state["count"]+=1# Declare how the state should be rendereddefCounter(props):returncg.h("widget",{},cg.h("label",{"text":f"Count:{props['count']}"}),cg.h("button",{"text":"Bump","on_clicked":bump}),)# Create a Collagraph instance with a PySide renderer# and register with the Qt event loopgui=cg.Collagraph(renderer=cg.PySideRenderer(),event_loop_type=cg.EventLoopType.QT,)# Render the function component into a container# (in this case the app but can be another widget)app=QtWidgets.QApplication()gui.render(cg.h(Counter,state),app)app.exec()For more examples, please take a look at theexamples folder.Currently there are two renderers:PysideRenderer: for rendering PySide6 applicationsPygfxRenderer: for rendering 3D graphic scenes withPygfxIt is possible to create a custom Renderer using theRendererinterface, to render to other UI frameworks, for instance wxPython, or even the browser DOM.
Package: collapsar
CollapsarIntroductionCollapsar is a package that will let you save time creating a dashboard for your app. You won't need to worry anymore about creating CRUD's.FeaturesAdd multiple resources to your dashboard using Masonite ModelsUse fields: TextField, IdField, PasswordField, SelectField and moreAdd basic validations: max, min, required, email, etc.DocumentationSee theofficial documentationto learn how to use Collapsar.InstallationpipinstallcollapsarConfigurationAdd CollapsarProvider to your project inconfig/providers.py:# config/providers.py# ...fromcollapsarimportCollapsarProvider# ...PROVIDERS=[# ...# Third Party ProvidersCollapsarProvider,# ...]Create a new resource usingpythoncraftresourceMyModelAnd see your panel onhttps://localhost/collapsarContributingPlease read theContributing Documentationhere.MaintainersEduardo AguadLicenseCollapsar is open-sourced software licensed under theMIT license.
Package: collapse
Collapsing Cosmology Research UtilitiesThecollapsepackage contains utilities for computing symbolic and numerical expressions related to the time evolution
of collapsing cosmologies.Symbolic ToolsThecollapsepackage makes use ofsympyto compute symbolic curvature equations (EFE).Specific DetailsExample Computation: FLRW Cosmology# Load the predefined FLRW metricfromcollapse.symbolicimportmetric,gravity,utilitiesflrw=metric.flrw().subs({'c':1})flrwefe_00=utilities.clean_expr(gravity.einstein_equation(0,0,flrw))efe_00# Can simplify notation using "dots"metric.simplify_deriv_notation(efe_00,flrw,use_dots=True)
Package: collapsing-thread-pool-executor
CollapsingThreadPoolExecutorThe CollapsingThreadPoolExecutor is inspired by and compatible with the ThreadPoolExecutor from the
"futures" module, it operates differently in that worker threads are handled with a stack which results in the same worker or workers doing all the work (and idle workers being destroyed).How to install$ pip install collapsing-thread-pool-executorHow to developPrerequisitespython3 w/ pippython2 w/ pipvirtualenvwrapperentrSet up the environments$ mkvirtualenv -p `which python2.7` collapsing-thread-pool-executor-py2
$ pip install .
$ pip install -r requirements.txt

$ mkvirtualenv -p `which python3` collapsing-thread-pool-executor-py3
$ pip install .
$ pip install -r requirements.txtWatch the tests# watch python2 tests in one window
$ workon collapsing-thread-pool-executor-py2
$ find ./ -name '*.py' | entr -c py.test -v --log-level=DEBUG collapsing_thread_pool_executor

# watch python3 tests in one window
$ workon collapsing-thread-pool-executor-py3
$ find ./ -name '*.py' | entr -c py.test -v --log-level=DEBUG collapsing_thread_pool_executorExamplesThe example below will executesome_task()100 times; assome_task()should take a second to execute and as we've allocated 10 workers, the whole thing should take about 10 seconds.import time

from collapsing_thread_pool_executor import CollapsingThreadPoolExecutor

def some_task():
    time.sleep(1)

# all arguments are optional
pool = CollapsingThreadPoolExecutor(
    workers=10,
    thread_name_prefix='SomePool',
    permitted_thread_age_in_seconds=60,
)

for i in range(0, 100):
    pool.submit(some_task)
Package: collate-cs
## descriptionThe thin format for source code is designed to minimise visual distraction when coding. Methods and variable declarations are separated into different files. Whitespace is syntactically significant.This repository contains the python code used to translate thin format csharp code into normal csharp code.## usagecollate_cs from_path to_path depth## getting startedTo work on developing this repository, add a file called local.zsh with the following format:#!/bin/zsh
nunit_path=’nunit.framework.dll Windows path’
csc=’csc.exe path’
nunit_runner=’nunitlite-runner.exe path’
Package: collect-bin-deps
collect-bin-deps.pyA tool to collect binary dependencies - typically shared libraries required by
an executable.Requirementspefile,pyelftoolspackageUsageSimplest case:collect-bin-deps.py -t <my exe file> <directory with dependency>...NotesThe "debug info" doesn't try to locate the debug info file using the information
contained in the binaries or so, it just looks for files with the same basename
as a dependency but with extensions used for debug info files.LimitationsCurrently supports Windows (PE) and Linux (ELF) binaries.Inspirationvcpkg can provide this functionality out of the box, realized with a
PowerShell script. collect-bin-deps.py qs written from scratch to provide the
same functionality.
Package: collect-columns
collect-columnsThis tool retrieves a column from each in a set of tables and compiles into a single table.
Optionally, additional attributes from the associated GTF/GFF file may be added to the output
tables.InstallationInstall from PyPI:pip install collect-columnsInstall from github:Clone the repository:git clone https://github.com/biowdl/collect-columns.gitEnter the repository:cd collect-columnsInstall using pip:pip install .Usagecollect-columns output_path input_files...It assumes that all input count tables are in the same format.
By default the format is assumed to be headerless and tab separated, with the
first column being the feature identifiers and the second the values of interest.
The output table will use the same separator as the input tables and contain
a header. Thefeaturecolumn will contain the feature identifiers, the value
columns will be named after the input files or according to the names given
through the-noption, which takes a list of names as argument.Please note that if multiple rows with the same feature identifier exist in
an input table, then these values will overwrite each other in the output table
by default. See also the-Sflag.In order to use a different input format the following options can be given:optionargumentsdefinition-fa numberThe index of the column containing the feature identifiers.-ca numberThe index of the column containing the values/counts.-sa characterThe separator.-HIndicates that the table has a header.-SIndicates that values should be added up if multiple rows exist with the same feature id. The values will become floats if this flag is set. By default only the last value will be taken and a warning will be give.To add additional attributes from a GTF/GFF, the following options can be given:optionargumentsdefinition-aa list of wordsThe attributes to be added to the output table.-ga pathThe gtf file from which the attributes will be retrieved.-Fa wordThe attribute used to map rows in the input tables to gtf record. Defaults togene_id.ExamplesHTSeq-countUsing the output from HTSeq-count as input the following command:collect-columns all.tsv s1.tsv s2.tsvwill result in a table like:features1.tsvs2.tsvMSTRG.11011MSTRG.26012.........StringtieUsing stringtie abundance output as input, the following command:collect-columns all.FPKM s1.abundance s2.abundance \
    -c 7 \
    -H \
    -a ref_gene_id gene_name \
    -g merged.gtf \
    -n sample1 sample2 \
    -S # Stringtie may at times return multiple rows for one gene, these values can simply be summed up.will result in a table like:featureref_gene_idgene_namesample1sample2MSTRG.1g_1gene_1185151.953125151.964231MSTRG.2g_2gene_2100160.0703121160.030213...............
Package: collect-db-models
collect db modelscollect sqlalchemy models to one file安装pipinstallcollect-db-models使用flaskcollect-db-models>{package_name}/models/__init__.py2如果没有报错，就可以把文件更名为__init__.py用下面的语句更简单，也会有一样的效果flaskcollect-db-models-wFlask项目需要符合下面的结构your_project/
│
├──core/
│   └── __init__.py
├──models/
│   └── __init__.pyyour_project/core/__init__.pyfromflask_sqlalchemyimportSQLAlchemydb=SQLAlchemy()
Package: collectd-ceilometer-plugin
OpenStack Ceilometer plugin for collectd.This plugin for collectd publishes telemetry data gathered by collectd to Ceilometer.
This enables a more comprehensive telemetry set to be made available to Ceilometer
which will enable smarter scheduling and environmental service assurance monitoring.Free software: Apache licenseDocumentation:http://docs.openstack.org/developer/collectd-ceilometer-pluginSource:http://git.openstack.org/cgit/openstack/collectd-ceilometer-pluginBugs:http://bugs.launchpad.net/collectd-ceilometer-pluginFeaturesConverts from collectd data sources to Ceilometer formatAdds units for CeilometerDevstack pluginConfigure and deploy plugin
Package: collectd-ceph-storage
Yet another Ceph Collectd Plugin in PythonOverviewThis plugin issues commands against Ceph in order to obtain valuable metrics
regarding the performance and health of your Ceph cluster.Sample GraphsMetricscollectd-ceph-storage-cluster/gauge-total_availcollectd-ceph-storage-cluster/gauge-total_spacecollectd-ceph-storage-cluster/gauge-total_usedcollectd-ceph-storage-mon/gauge-numbercollectd-ceph-storage-mon/gauge-quorumcollectd-ceph-storage-osd-(*)/gauge-apply_latency_mscollectd-ceph-storage-osd-(*)/gauge-commit_latency_mscollectd-ceph-storage-osd-(*)/gauge-kb_totalcollectd-ceph-storage-osd-(*)/gauge-kb_usedcollectd-ceph-storage-osd-(*)/gauge-num_snap_trimmingcollectd-ceph-storage-osd-(*)/gauge-snap_trim_queue_lencollectd-ceph-storage-osd/gauge-downcollectd-ceph-storage-osd/gauge-incollectd-ceph-storage-osd/gauge-outcollectd-ceph-storage-osd/gauge-upcollectd-ceph-storage-pg/gauge-activecollectd-ceph-storage-pg/gauge-cleancollectd-ceph-storage-pg/gauge-scrubbingcollectd-ceph-storage-pool-(pool name)/gauge-bytes_usedcollectd-ceph-storage-pool-(pool name)/gauge-kb_usedcollectd-ceph-storage-pool-(pool name)/gauge-objectscollectd-ceph-storage-pool-(pool name)/gauge-pg_numcollectd-ceph-storage-pool-(pool name)/gauge-pgp_numcollectd-ceph-storage-pool-(pool name)/gauge-read_bytes_seccollectd-ceph-storage-pool-(pool name)/gauge-read_op_per_seccollectd-ceph-storage-pool-(pool name)/gauge-sizecollectd-ceph-storage-pool-(pool name)/gauge-write_bytes_seccollectd-ceph-storage-pool-(pool name)/gauge-write_op_per_seccollectd-ceph-storage-pool/gauge-number
Package: collectd-connect-time
# TCP Connect Time PluginReturns the time required to connect to hostname[:port]# CLI$ collectd-connect-time google.de{"64.233.167.94:80": 5.728006362915039}# Collectd ConfigurationLoadPlugin python<Plugin python>ModulePath "/usr/lib/python2.7/dist-packages/"Import "collectd_connect_time"<Module collectd_connect_time>target "google.de" "web.de" "aol.com"</Module></Plugin>- this results in values stored at `<hostname>.connect-time-<target[1]>.response_time-max`# LicenseSee `LICENSE`