Saravanan666/pypi-org huggingface dataset:
Package: commot
COMMOTScreening cell-cell communication in spatial transcriptomics via collective optimal transportInstallationInstall from PyPI bypip install commotor install from source by cd to this directory andpip install .[Optional] InstalltradeSeqin R to analyze the CCC differentially expressed genes.Currently, tradeSeq version 1.0.1 with R version 3.6.3 has been tested to work.In order for the R-python interface to work properly, rpy2==3.4.2 and anndata2ri==1.0.6 should be installed.
To use this feature, install from PyPI bypip install commot[tradeSeq]or from source bypip install .[tradeSeq].UsageBasic usageImport packagesimport commot as ct
import scanpy as sc
import pandas as pd
import numpy as npLoad a spatial dataset(e.g., a Visium dataset)adata = sc.datasets.visium_sge(sample_id='V1_Mouse_Brain_Sagittal_Posterior')
adata.var_names_make_unique()Basic processingsc.pp.normalize_total(adata, inplace=True)
sc.pp.log1p(adata)Specify ligand-receptor pairsLR=np.array([['Tgfb1', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway'],['Tgfb2', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway'],['Tgfb3', 'Tgfbr1_Tgfbr2', 'Tgfb_pathway']],dtype=str)
df_ligrec = pd.DataFrame(data=LR)(or use pairs from a ligand-receptor databasedf_ligrec=ct.pp.ligand_receptor_database(database='CellChat', species='mouse').)Construct CCC networksUse collective optimal transport to construct CCC networks for the ligand-receptor pairs with a spatial distance constraint of 200 (coupling between cells with distance greater than 200 is prohibited). For example, the spot-by-spot matrix for the pair Tgfb1 (ligand) and Tgfbr1_Tgfbr2 (receptor)is stored inadata.obsp['commot-user_database-Tgfb1-Tgfbr1_Tgfbr2']. The total sent or received signal for each pair is stored inadata.obsm['commot-user_database-sum-sender']andadata.obsm['commot-user_database-sum-receiver'].ct.tl.spatial_communication(adata,
    database_name='user_database', df_ligrec=df_ligrec, dis_thr=200, heteromeric=True)DocumentationSee the documentation athttps://commot.readthedocs.io/en/latest/index.htmlfor all the APIs to perform visualization and analyses such as visualizing spatial signaling direction and identifying CCC differentially expressed genes.ReferenceCang, Zixuan, Yanxiang Zhao, Axel A. Almet, Adam Stabell, Raul Ramos, Maksim Plikus, Scott X. Atwood, and Qing Nie. "Screening cell-cell communication in spatial transcriptomics via collective optimal transport." bioRxiv (2022): 505185
Package: commscores
Microbial communities predicate most biological systems on Earth, yet the interaction dynamics between community members remains opaque. Quantitative metrics offer a means of isolating these complex, multi-dimensional, interactions into single biological dimensions; although, several ostensibly important biological dimensions evade existing metrics and extant metrics have moreover not be consolidated into a single operable package. We therefore developed CommScores as a comprehensive package for quantifying microbial interaction dimensions within a microbial community, and thereby elucidating the dynamics that govern the given community. CommScores leveragesModelSEEDpyandCOBRApypackages for metabolic modeling, and theCOBRA-KBasepackage for acquiring genomic information from KBase. CommScores should accelerate fundamental discoveries in microbial ecology and the rational design of microbial communities for diverse applications in medicine, ecology, and industry.NoteThis project is under active development, and may be subject to losing back-compatibility.InstallationCommScores and all of its dependencies should automatically install when it is installed from PyPI:pip install commscores
Package: commtrack
# CommtrackTracking commits was never easier.<div align="center"><img src="./docs/commtrack_example.png" alt="commtrack example" width="400"></div><hr />## Installation```git clone https://github.com/bregman-arie/commtrack.gitcd commtrackpipenv install -e .```## Usage```# Search for comit 2142commtrack -c 2142# Search for change ID in OpenStack Gerrit:commtrack --changeid t3gq2 --links openstack_gerrit```## User GuideWould like to learn more about Commtrack? Click [here](docs/user_guide.md)## Developer GuideWould like to assist with Commtrack development? Click [here](docs/developer_guide.md)
Package: communardo-metadata
Communardo Metadata Python LibraryThis is a simple wrapper around the REST API which the Communardo
Metadata plugin for Confluence provides.InstallationInstall from pypi use: ~~pip install communardo-metadata
~~Usagefromcommunardo.metadata.clientimportMetadataClientwithMetadataClient("https://server:port/contextpath",("user","pass"))asclient:metadata_results=client.search(cql="ID=1")Development and DeploymentSee theContribution guidelines for this projectfor details on how to make changes to this library.
Package: communebot-fr
Commune BotA friendly Twitter bot built withMunibotthat tweets aerial pictures of France'scommunes.Install and setupInstall it with pip:pip install communebot-frAnd follow the instructions onMunibot's documentationregarding configuration and setup.This particular bot requires:AnIGN geoserviceskey to access the WMS service, which you can obtainhereThe backend SQLite database with communes data, which you can download from this repo (datafolder)Both these should be referenced in the[profile:fr]section of yourmunibot.inifile:[profile:fr]
ign_key=CHANGE_ME
twitter_key=CHANGE_ME
twitter_secret=CHANGE_ME
db_path=/path/to/data/communes_fr.sqlitePatchesAs of April 2021 this bot requires apatch in OWSLibto be able to send headers as part of the WMSGetMaprequests. The patch is included in thedatafolder.LicenseMIT
Package: communesplone.layout
IntroductionThis product is dedicated to override default plone layout.Adapted for plone 4.2.x and 4.3.15, 4.3.16, 4.3.17, 4.3.18For older versions, seehttp://svn.communesplone.org/svn/communesplone/communesplone.layout/tags/default profileOverrides login_form to display a warning message when authentication plugins are deactivated
and sendto_form to integrate a captcha.simplify profileSet site permissions only for managers (sharing, rules, views, …)
Add a cleaning css applied for user not in ‘full-layout’ groupChangelog4.3.15.1 (2020-02-25)Validated for Plone 4.3.15.
[gbastien]4.3.8.1 (2017-05-17)Adapted translation for ‘label_by_author’ from ‘By {author}’
to ‘Created by ${author}’.
[gbastien]4.3.8 (2017-02-02)moved to Plone 4.3.8
[gbastien]override the ‘label_click_here_to_retrieve’ translation to display a clear
message on the link to retrieve password when lost
[gbastien]433 (unreleased)moved to Plone 4.3.3
[gbastien]432 (2014-02-12)moved to Plone 4.3.2
[gbastien]4 (2013-08-28)login_form overrides to display message when authentication plugins are deactivated
[sgeulette]sendto_form overrides to integrate a captcha (collective.captcha)
[gbastien]
Package: communex
CommuneXWhy CommuneXInstallation withpipInstallation with NixFeaturesPlannedCLI UsageExamplesCompletionsContributingCommune compatibilityWhy CommuneXCommuneX serves as an alternative library/SDK to the originalCommune
Aicodebase, offering a streamlined and
user-friendly experience. It is designed for simplicity and scalable
development. To learn morevisit docsInstallation withpipRequirements: Python 3.10+Install thecommunexPython package directly withpip:pipinstallcommunexOr add it to your Poetry project with:poetryaddcommunexInstallation with NixTo installcommunexthe communex cli with Nixnixprofileinstall.FeaturesCommandsKey managementTransfering and staking tokensModule managementPlannedClient to interact with served modulesModule class and serverModule API extraction and documentation generatorCLI UsageThe CLI commands are structured as follows:comx[OPTIONS]COMMAND[ARGS]There are six top-level subcommands:balance: transfer, stake, unstake and showing balance operationskey: creating, saving (AKA regenerating), listing and showing balance
operationsmodule: info, list, register, serve, updatenetwork: block, parameters, proposals / proposing, voting operationssubnet: info, list, updatemisc: apr, circulating supplycomxsubcommand[OPTIONS]COMMAND[ARGS]...ExamplesRetrieving Balance# Show staked, free and total balance.comxbalanceshow5FgfC2DY4yreEWEughz46RZYQ8oBhHVqD9fVq6gV89E6z4EaCreating a Keycomxkeycreatekey_nameRetrieving Key Infocomxkeyshowkey_name# Add the `--show-private` flag to show sentitive fields like private key.comxkeyshowkey_name--show-privateListing Keys# Lists the names and addresses of keys stored on disk.comxkeylistList Keys With Balances# Lists keys stored on disk with their balance (free, staked and total).comxkeybalancesRetrieving Module Information# Note that the module has to be registered on the network.comxmoduleinfovali::calc[--balance]Retrieving Global ParameterscomxnetworkparamsRetrieving Subnet ParameterscomxsubnetlistRetrieving Circulating Supply# Gets all tokens then were ever emitted minus burned tokens.comxmisccirculating-supplyCompletionsYou can enable completions for your shell by running:# On bashcomx--install-completionbash# On zshcomx--install-completionzshContributingBug reports and pull requests and other forms of contribution are welcomed and
encouraged!  :)To report a bug or request a feature, pleaseopen an issue on GitHub.If you have any questions, feel free to ask on theCommuneX Discord channelor
post on ourGitHub discussions page.Commune compatibilityYes,communexis compatible with thecommunelibrary/CLI. However, there are
important considerations to note.communexverifies the integrity of your
keys, which means that mixing certain types of keys is not permissible.
Specifically, if you possess node keys or other similar types that are not
designed to receive tokens, you to relocate them outside of the key
directory.
Package: communica
Easy to use IPC libraryThis library is still in development process.
There will be added Pub/Sub entities and data validation in
serializers with pydantic and dataclass-factory libraries.

Stream connectors has no acknowledgements at the moment,
so messages on service restart will be lost
(they will be lost anyway on restarting side, but with acks loss can be less)Plug-n-play IPCIdeaContains two mainentities:ClientandServer, which usesConnectorsto createConnections.In most cases, there are one server and few clients. After successful connect there is
no difference between them, any side can make requests to other.Currently available connectors:ConnectorDescriptionLocalConnectorUses Named Pipes on Windows and Unix domain sockets on other systems, if availableTcpConnectorUses TCP/IP protocol, has ability to specify SSLContextRmqConnectorUses RabbitMQ server, has caveats (documented in connector)The most stable connector right now is RmqConnector. Other works too,
but lose messages on every disconnect.ExtrasYou can install additional dependencies for various featurespip install communica[extraname1, extraname2]Extra nameFeatureorjsonFaster JSON library, recommended with CPythonrabbitmqRmqConnector, which use AMQP server for communication
Package: communicationAppModule
communication app botwhat is thisThis project is amied to create a python package can easily send message to any communication appSupport telegram right now, fell free to let me know which app you want to have this functionInstallingpip3 install communicationAppModuleprerequisiteTelegramcreate a bot via botfather to get a bot tokenCreate Client# bot token only for telegram# db_name optional# log_file_name optionalfromcommunicationAppimport*client=createClient('Telegram',bot_token='',db_name='',log_file_name='')Send Message# send single sentenceclient.send_message("hi")# send multi lineclient.send_message(['hi','John','this is wayne'])Send Photo# send photo from urlclient.send_photo({'photo_url':photo_url})# send photo from telegram file idclient.send_photo({'file_id':file_id})#send photo from filefile=open('path','rb')client.send_photo({'file':file})Get message# send last responseclient.get_response()# get multi responsesclient.get_response(10)Response Format{"status_code":200,"data":[{"user_info":{},"date":"timestamp","text":"string"}],"error":"string"}Change Log0.1 (06/03/2022)First Release0.2.0 (10/04/2022)add send photo feature
Package: communico
Communico is a simple Django app for contact forms.Quick startInstall “communico” from PyPI:pip install communicoAdd “communico” to your INSTALLED_APPS setting like this:INSTALLED_APPS = [
    ...
    'communico',
]Add the following email settings to your settings file:EMAIL_HOST = ''
EMAIL_HOST_USER = ''
EMAIL_HOST_PASSWORD = ''
EMAIL_USE_TLS = True
EMAIL_PORT = 587Include the communico URLconf in your project urls.py like this:url(r'^contact/', include('communico.urls', namespace='communico')),Start the development server and visithttp://127.0.0.1:8000/contact/to view the contacts form.Communico comes with a basic html and no styling, please tweak as needed.
Package: community
merge together [wellness](https://github.com/warmwaffles/wellness) compatible
checks to build a unified view of your conglomerated servicesRoutes/health/statusreturns as wellness does, but does not handleDEGRADEDstatus/health/detailsreturns a wellness likestatus,services,detailshash with combinedservicesanddetailsdictionaries bynameConfiguraitoncommunityaccepts one and only one environment variable!COMMUNITY_MEMBERS: a|separated list of,separated (name, health url) pairs
* example:core-api,https://core.example.com/health|user-api,https://user.example.com/healthwill produce approximately this output$ curl conglomo.example.com/health/status
{"status":"HEALTHY"}
$ curl conglomo.example.com/health/details
{
  "status": "HEALTHY",
  "services": {
    "core-api": {
      "mysql": {
        "status": "HEALTHY",
        "details": {}
      }
    },
    "user-api": {
      "database": {
        "status": "HEALTHY",
        "details": {}
      },
      "sidekiq": {
        "status": "HEALTHY",
        "details": {
          "busy": 0,
          "default_latency": 104502.181265831,
          "enqueued": 290,
          "failed": 6045,
          "processed": 10982,
          "redis": {
            "connected_clients": "158",
            "uptime_in_days": "224",
            "used_memory_human": "4.19M",
            "used_memory_peak_human": "8.14M"
          },
          "retries": 3,
          "scheduled": 0
        }
      }
    }
  },
  "details": {
    "core-api": {
      "git": {
        "revision": "deadbeef"
      }
    },
    "user-api": {
      "git": {
        "revision": "deadbeef"
      }
    }
  }
}
Package: community-circuitpython-tca9555
IntroductionCircuitPython library for Texas Instruments TCA9555 Low-Voltage 16-Bit I2C
and SMBus I/O Expander with Input / Output and Polarity Inversion.DataSheetDependenciesThis driver depends on:Adafruit CircuitPythonBus DeviceRegisterPlease ensure all dependencies are available on the CircuitPython filesystem.
This is easily achieved by downloadingthe Adafruit library and driver bundleor individual libraries can be installed usingcircup.Installing from PyPIOn supported GNU/Linux systems like the Raspberry Pi, you can install the driver locallyfrom
PyPI.
To install for current user:pip3installcommunity-circuitpython-tca9555To install system-wide (this may be required in some cases):sudopip3installcommunity-circuitpython-tca9555To install in a virtual environment in your current project:mkdirproject-name&&cdproject-namepython3-mvenv.envsource.env/bin/activatepip3installcommunity-circuitpython-tca9555Usage ExampleCreate an instance of TCA9555 expander. This defaults to all 16 pins set as
inputs with no polarity conversion.fromcommunity_tca9555importTCA9555# If the board has I2C definedexpander=TCA9555(board.I2C())# Use default address of 0x20# Else specify the specific pinsexpander=TCA9555(busio.I2C(scl=board.GP5,sda=board.GP4))# for the RP PicoSet the low 8 bits as inputs and the high 8 bits as outputs.# set all 16 pins at onceexpander.configuration_ports=0x00FF# or# set port 0 (8bits) and port 1 (8 bits)expander.configuration_port_0=0xFF# Inputsexpander.configuration_port_1=0x00# Outputs# or# set each pin individuallyexpander.configuration_port_0_pin_0=True# Input# ...expander.configuration_port_1_pin_7=False# OutputSet pins 6 and 7 of both port 0 and port 1 as polarity inverted.# Set polarity inversion state for individual pins.expander.polarity_inversion_port_0_pin_6=True# Invertedexpander.polarity_inversion_port_0_pin_7=Trueexpander.polarity_inversion_port_1_pin_6=Trueexpander.polarity_inversion_port_1_pin_7=True# or# Set an 8bit port at onceexpander.polarity_inversion_port_0=0xC0# Just bits 6 and 7# or# Set all 16bits at onceexpander.polarity_inversions=0xC0C0Read the input pins.input_state=expander.input_port_0print("Inputs:{:08b}".format(input_state))Set the state of the output pins.expander.output_port_1=0x42ContributingContributions are welcome! Please read ourCode of Conductbefore contributing to help this project stay welcoming.DocumentationFor information on building library documentation, please check outthis guide.
Package: community_detect
community-detectCommunity detection using attribute and structural similarities.Installation:pip install community_detectDependencies:NetworkXMatplotlibUsage:Import:from community_detect import CommunityInitialize:com = Community(alpha_weight = 0.5) #You can add your own value for AlphaFunctions:Main method: get_communities(Graph, #Your GraphVertices, #List of VerticesSimilarity Matrix, #Similarity matrix for attribute similarities (It should be a N X N matrix where N is the number of verticesSimilarity Matrix Type #Types : cosine, euclidean etc)Returns a dictionary with each key containing all the nodes in that communityTo View Communities : view_communities(Communities, #Output of above functionGraph, #Your GraphVertices, #List of VerticesSimilarity Matrix, #Similarity matrix for attribute similarities (It should be a N X N matrix where N is the number of verticesSimilarity Matrix Type #Types : cosine, euclidean etc)
Package: community-detection
IntroductionThe community-detection module contains basic functions for find communities in a graph. Internally, community-detection usessimple-graphto hold the structure of a graph.Installpipinstallcommunity-detectionor updatepipinstall--upgradecommunity-detectionUsagefromsimple_graphimportGraphfromcommunity_detectionimportFastUnfoldingG=Graph({0:[1,2],1:[2]})fu=FastUnfolding()communities=fu.process(G)Q=fu.modularity(G,communities)print(communities)print('Q:',Q)ouput:[[0,1,2]]Q:0.0Licensecommunity-detection is a free software. See the file LICENSE for the full text.Authors
Package: communityid
pycommunityidThis package provides a Python implementation of the openCommunity IDflow hashing standard.It supports Python versions 2.7+ (for not much longer) and 3+.InstallationThis package is availableon PyPI, therefore:pip install communityidTo install locally from a git clone, you can use also use pip, e.g. by sayingpip install -U .UsageThe API breaks the computation into two steps: (1) creation of a flow
tuple object, (2) computation of the Community ID string on this
object. It supports various input types in order to accommodate
network byte order representations of flow endpoints, high-level ASCII,
and ipaddress objects.Here's what it looks like:import communityid

cid = communityid.CommunityID()
tpl = communityid.FlowTuple.make_tcp('127.0.0.1', '10.0.0.1', 1234, 80)

print(cid.calc(tpl))This will print "1:mgRgpIZSu0KHDp/QrtcWZpkJpMU=".The package includes three sample applications:community-id,
which calculates the ID directly for given flow tuples. It supports
a small but growing list of parsers. Example:$ community-id tcp 10.0.0.1 10.0.0.2 10 20
1:9j2Dzwrw7T9E+IZi4b4IVT66HBI=community-id-pcap,
which iterates over a pcap via dpkt and renders
Community ID values for each suitable packet in the trace. This
exercices the package's "low-level" API, using flow tuple values as
you'd encounter them in a typical network monitor.community-id-pcapfilter,
which iterates over a pcap via dpkt and produces a pcap of
only those packets whose Community IDs have a specific value,
filtering out all others.community-id-tcpdump,
which takes tcpdump output on stdin and
augments it with Community ID values on stdout. This exercices the
package's "high-level" API, using ASCII representations of tuple
values.TestingThe package includes a unittest testsuite in thetestsdirectory
that runs without installation of the module. After changing into that
folder you can invoke it e.g. viapython -m unittest communityid_testornose2 -C --coverage ../communityid --coverage-report term-missing communityid_testor by running./communityid_test.pydirectly.
Package: community-layout
Community LayoutLayout of large networkx graphs with community segmentationA small package used to visualise community-structured networkx graphs.Layout of communities individually, with communities themselves arranged according to their inter-links, allows far faster visualisation of large graphs.Note: This is an early version, and usage will likely be changed as new functionality is added.UsageThe layout class is accessed via:from community_layout.layout_class import CommunityLayoutPosition calculation is during__init__.
After__init__,CommunityLayout(G).full_positionsis an dictionary of keys corresponding to node positions, as in networkx layout algorithms.Basic usage is as follows:import networkx as nx
from community_layout.layout_class import CommunityLayout

G = nx.gnm_random_graph(2000, 40000)
layout = CommunityLayout(G)
pos = layout.full_positionsThere are several parameters that can be changed by the user:CommunityLayout(self,
                G,
                community_compression = 0.25,
                layout_algorithm = nx.spring_layout,
                layout_kwargs = {"k":75, "iterations":1000},
                community_algorithm = community.louvain_communities,
                community_kwargs = {"resolution":2})These are designed to work with networkx functions, but custom functions will work assuming similar syntax and that they return the same objects.community_algorithmcan also be a list of pre-determined communities, ie["community_1":{"node_id1", "node_id2",...}, "community_2":{"node_id3", "node_id4",...}].community_compressioncontrols the scale compression of individual community sub-layouts.
Lower values will result in each community occupying smaller portions of the overall layout.Optionally we also include figure plotting:layout.display(colors = None,
               bundle = False,
               complex_alphas = True,
               ax = None)Which, if passedax = matplotlib.Axes, returns the same. If noAxesis passed, it saves a.pngin the working directory and callsplt.show().Note: Edge bundling is currently a much heavier process than the community layout process.RequirementsRequires the packagesnumpy,pandas,tqdm,scipyandnetworkxto be installed.matplotlibis required for figure plotting. Edge bundling requiresdatashaderandscikit-image.