Saravanan666/pypi-org huggingface dataset:
Package: breakSeqInNs-then-translate
breakSeqInNs_then_translate1 IntroductionbreakSeqInNs_then_translateis a tool to filter the sequences by translating the protein coding genes (PCGs) with proper genetic code table, if one of the PCGs has interal stop codon, filter out this sequence. By Guanliang MENG, seehttps://github.com/linzhi2013/breakSeqInNs_then_translate.2 Installationpip install breakSeqInNs_then_translateThere will be a commandbreakSeqInNs_then_translatecreated under the same directory as yourpipcommand.3 Usage$ breakSeqInNs_then_translate
usage: breakSeqInNs_then_translate.py [-h] [-seq <seq>] [-seqfile <file>]
                                      [-seqformat {fa,gb}] [-code <int>] [-nb]
                                      [-gb_genes <int>] [-maxStopGenes <int>]

Filter the sequences by translating the protein coding genes (PCGs) with
proper genetic code table, if one of the PCGs has interal stop codon, filter
out this sequence. Beware: if the seq has Ns, then this script will translate
the sub seqs with three frames (0, 1, 2), only when all these three kinds of
frames have interal stopCodon the seq will be treated as have InternalStop!.
By Guanliang MENG, see
https://github.com/linzhi2013/breakSeqInNs_then_translate

optional arguments:
  -h, --help           show this help message and exit
  -seq <seq>           input sequence
  -seqfile <file>      input fasta or genbank file
  -seqformat {fa,gb}   input -seqfile format [fa]
  -code <int>          genetic code table [1]
  -nb                  do not break sequence in Ns when translate [break]
  -gb_genes <int>      if a genbank record has no less than -gb_genes PCGs and
                       no more than -maxStopGenes PCGs has InternalStops, we
                       keep this record. But if a genbank record has less than
                       -gb_genes PCGs, then we will discard this record if any
                       of its PCGs has InternalStops. This is because we may
                       want to tolerate some assembly/sequencing errors. This
                       has no effect on fasta input file. [5]
  -maxStopGenes <int>  the maximum number of PCGs can have InternalStops in a
                       genbank record if do not discard it [0]4 AuthorGuanliang MENG5 CitationCurrently I have no plan to publishbreakSeqInNs_then_translate.However, sincebreakSeqInNs_then_translatemakes use ofBiopython, you should also cite it if you usebreakSeqInNs_then_translatein your work:Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski, Michiel J. L. de Hoon: “Biopython: freely available Python tools for computational molecular biology and bioinformatics”. Bioinformatics 25 (11), 1422–1423 (2009). https://doi.org/10.1093/bioinformatics/btp163Please go tohttp://www.biopython.org/for more details.
Package: breakthecode
breakthecodeBreak The Codeboard game helper scriptThis script lists all the possible solutions to break the code, according to provided constraints.InstallEasy:pip install breakthecodeUsageusage: breakthecode [-h] [--remove DC] [--sum T[,I[,L[,C]]]] [--position N,I] [--odd O] [--even E] [--black B] [--white W] [--diff D] [--digit I<=>V] [--pairs P]

BreakTheCode board game helper

optional arguments:
  -h, --help            show this help message and exit
  --remove DC, -r DC    number that can't be part of the solution (e.g. 0b, 6w, 5)
  --sum T[,I[,L[,C]]], -s T[,I[,L[,C]]]
                        add a sum constraint (T=total, I=start, L=length, C=color)
  --position N,I, -p N,I
                        add a position constraint (N=number, I=position)
  --odd O, -o O         add an odd numbers count constraint
  --even E, -e E        add an even numbers count constraint
  --black B, -b B       add a black numbers count constraint
  --white W, -w W       add a white numbers count constraint
  --diff D, -d D        add a max-min diff constraint
  --digit I<=>V, -D I<=>V
                        add a digit comparison constraint (I=index, V=value)
  --pairs P, -P P       add a pairs count contraint
Package: break-video-to-frames
Video To FramesvideoToFrames breaks a video to it's frames and save them in a folder.InstallationYou can install the videoToFrames fromPyPI:python -m pip install break-video-to-framesHow to usevideo to frames is a command line application, namedvideoToFrames. To check it's command-line options:$ videoToFrames -hTo break all videos in a folder to frames:$ videoToFrames -p your_folder_pathTo break a specified video:$ videoToFrames -p your_video_pathYou can specify a format to save frames (default isjpg):$ videoToFrames -f pngTo see time and number of frames:$ videoToFrames -vTo import to your program:>>> import videoToFrames
    >>> videoToFrames.__version__
    >>> from videoToFrames.breaker import VideoToFrames
    >>> obj = VideoToFrames(path="your_path", verbose=True, image_format="jpg")
    >>> obj.run_breaking()
Package: breakwater
breakwater: a Python package for the conceptual design of breakwatersDateJuly 2020AuthorSander WinkelContactpybreakwater@gmail.comMaster ThesisDeveloping a design automation tool for the conceptual design of breakwatersDocumentationhttps://breakwater.readthedocs.io/LicenseCC-BY-NC-SA 4.0PurposeThe main goal ofbreakwateris to support the designer in exploring different
types of breakwaters, see Figure 1.1 for a cross section of the breakwater
types defined by CIRIA, CUR, CETMEF (2007). The main use case is thus to make a
conceptual design of a breakwater using one of the design classes, seeChapter 7of the documentation. However, because all functions and classes are also available
frombreakwater.coreit is also possible to develop your own design automation
script.NoteDue to the limited time not all breakwater types defined by CIRIA, CUR, CETMEF (2007)
could be implemented. Currently only the following structures have been implemented:
conventional rubble mound breakwaters with rock and armour units as armour layer,
caisson breakwaters and vertically composite breakwaters.Main Featuresbreakwateroffers the following features to support the designer:Design a rubble mound breakwater with rock or concrete armour units as armour
layer, withbw.RockRubbleMoundorbw.ConcreteRubbleMound.Design a vertical or vertically composite breakwater withbw.Caisson.Design with an interactive design application by usingbw.interactive_design.
With this application several parameters can be changed with sliders, to assess
the influence of certain parameters on the design and cost.Design multiple breakwaters at ones by usingbw.Configurations. With this class
multiple breakwater types can be designed at ones, these concepts can than
be assess by using a multi-criteria analysis or with theDesignExplorer.Use the functions and classes frombreakwater.coreto create your own
design automation approach.breakwater.coreconsist of all functions and
classes defined in Chapters8to11.Getting StartedThe latest released version is available at thePython package indexpipinstallbreakwaterAlternatively, the source code can be downloaded, or cloned, from the GitHub repository.pythonsetup.pyinstallA tutorial ofbreakwatercan be found inChapter 3of the documentation. Thisdocumentationalso provides a full overview of the implemented failure mechanisms,
and is thus a full overview of all features ofbreakwater.
Package: brealid
brealid-python-libbrealid python libraryInstallationpipinstallbrealidStructurebrealidctfcryptoAlias (remote, bytes_xor)GF2nUsagectffrombrealid.ctfimport*frombrealid.ctf.cryptoimportGF2nprint(bytes_xor(b'hello, world',b'\x06\nL\x01\x00^EW\t\x1e\r\x03'))# b'no more flag'num=GF2n(0x13)*GF2n(0x13)print(num)print(repr(num))# 261# GF2n<GaloisField(2^512), poly=0x125> (0x105)
Package: brease-sdk
brease-sdkSDK Installationpipinstallbrease-sdkSDK Example Usageimportsdkfromsdk.modelsimportoperations,shareds=sdk.SDK()req=operations.AddRuleRequest(add_rule_input=shared.AddRuleInput(rule=shared.ModelsRule(action='corrupti',description='provident',expression=shared.ModelsRuleExpression3(condition=shared.Condition(base=shared.ConditionBase2(ref=shared.ConditionBaseRef(dst='unde',src='nulla',),),parameter=False,type=shared.ConditionType.RGX,),),id='69a674e0-f467-4cc8-b96e-d151a05dfc2d',target=shared.ModelsTarget(target='at',target_value='maiores',type='molestiae',),),),context_id='quod',)res=s.context_id.add_rule(req,operations.AddRuleSecurity(api_token="YOUR_BEARER_TOKEN_HERE",))ifres.api_add_rule_responseisnotNone:# handle responseAvailable Resources and Operationscontext_idadd_rule- Adds a new rule to the contextevaluate_rules- Evaluate rules within a context on the provided objectget_all_rules- Returns all rules with the contextremove_rule- Removes a rule from the contextreplace_rule- Replaces an existing rule within the contextMaturityThis SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage
to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally
looking for the latest version.ContributionsWhile we value open-source contributions to this SDK, this library is generated programmatically.
Feel free to open a PR or a Github issue as a proof of concept and we'll do our best to include it in a future release !SDK Created bySpeakeasy
Package: breast-cancer-detection
Breast Cancer Detection from Mammography using Deep LearningDocumentation:https://john-james-ai.github.io/breast_cancer_detectionSource Code:https://github.com/john-james-ai/breast_cancer_detectionPyPI:https://pypi.org/project/breast_cancer_detection/Breast Cancer Detection from Mammography using Deep LearningInstallationpipinstallbcdDevelopmentClone this repositoryRequirements:PoetryPython 3.7+Create a virtual environment and install the dependenciespoetryinstallActivate the virtual environmentpoetryshellTestingpytestDocumentationThe documentation is automatically generated from the content of thedocs directoryand from the docstrings
of the public signatures of the source code. The documentation is updated and published as aGithub project pageautomatically as part each release.ReleasingTrigger theDraft release workflow(pressRun workflow). This will update the changelog & version and create a GitHub release which is inDraftstate.Find the draft release from theGitHub releasesand publish it. When
a release is published, it'll triggerreleaseworkflow which creates PyPI
release and deploys updated documentation.Pre-commitPre-commit hooks run all the auto-formatters (e.g.black,isort), linters (e.g.mypy,flake8), and other quality
checks to make sure the changeset is in good shape before a commit/push happens.You can install the hooks with (runs for each commit):pre-commitinstallOr if you want them to run only for each push:pre-commitinstall-tpre-pushOr if you want e.g. want to run all checks manually for all files:pre-commitrun--all-filesThis project was generated using thewolt-python-package-cookiecuttertemplate.
Package: breast-cancer-toolkit
breast-cancer-toolkitMachine learning toolkit designed to support radiologists and oncologists in breast cancer detection and analysis.Installation from pypipipinstallbreast-cancer-toolkitCLIStart web serverbct-sVisualize from local storagebct-lv[file_path].(dcm|tif|tiff|jpg|png|ljpeg)PythonConsult ournotebooksto learn more. We recommend you starting withGetting started.DICOM WebTODONoteThis project has been set up using PyScaffold 4.4. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.
Package: breathe-plus
Breathe PlusThis is an exploratory project for what a new version of Breathe might look like if it is primarily written in Rust.
This is to improve performance and reduce the memory usage.It is also an experiment in licensing as to make the project more sustainable the idea is to make it is source
available (rather than open source) and free for open source projects but to require a paid license for non-open source
work.RunRequires a Rust & Cargo installation.https://www.rust-lang.org/tools/installAnd Poetry for Python package management.https://python-poetry.org/docs/#installationpoetry install
poetry shell
maturin develop
make -C documentation html
firefox documentation/build/html/index.htmlLicenseLicensed under theParity Public License
Package: brec
Towards Better Evaluation of GNN Expressiveness with BREC DatasetAboutThis package is official implementation of the following paper:Towards Better Evaluation of GNN Expressiveness with BREC Dataset. Evalution process can be easily implemented by this package. For more detailed and advanced usage, please refer toBRECBRECis a new dataset for GNN expressiveness comparison.
It addresses the limitations of previous datasets, including difficulty, granularity, and scale, by incorporating
400 pairs of various graphs in four categories (Basic, Regular, Extension, CFI).
The graphs are organized pair-wise, where each pair is tested individually to return whether a GNN can distinguish them. We propose a new evaluation method,RPC(Reliable Paired Comparisons), with a contrastive training framework.UsagesInstallInstallpytorchandpytorch_geometricwith corresponding versions aligning with your device. Thenpip install brec.ExampleHere is a simple example:importtorchimporttorch.nn.functionalasFfromtorch_geometric.nnimportGCNConvfrombrec.datasetimportBRECDatasetfrombrec.evaluatorimportevaluateclassGCN(torch.nn.Module):def__init__(self):super().__init__()self.conv1=GCNConv(1,16)self.conv2=GCNConv(16,16)defforward(self,data):x,edge_index=data.x,data.edge_indexx=self.conv1(x,edge_index)x=F.relu(x)x=F.dropout(x,training=self.training)x=self.conv2(x,edge_index)returnxdefreset_parameters(self):self.conv1.reset_parameters()self.conv2.reset_parameters()model=GCN()dataset=BRECDataset()evaluate(dataset,model,device=torch.device("cpu"),log_path="log.txt",training_config=None)
Package: brec-iclr2024
Towards Better Evaluation of GNN Expressiveness with BREC DatasetAboutThis package is official implementation of the following paper: Towards Better Evaluation of GNN Expressiveness with BREC Dataset. Evalution process can be easily implemented by this package. For more detailed and advanced usage, please refer toBRECBRECis a new dataset for GNN expressiveness comparison.
It addresses the limitations of previous datasets, including difficulty, granularity, and scale, by incorporating
400 pairs of various graphs in four categories (Basic, Regular, Extension, CFI).
The graphs are organized pair-wise, where each pair is tested individually to return whether a GNN can distinguish them. We propose a new evaluation method,RPC(Reliable Paired Comparisons), with a contrastive training framework.UsagesInstallInstallpytorchandpytorch_geometricwith corresponding versions aligning with your device. Thenpip install brec-iclr2024.ExampleHere is a simple example:importtorchimporttorch.nn.functionalasFfromtorch_geometric.nnimportGCNConvfrombrec.datasetimportBRECDatasetfrombrec.evaluatorimportevaluateclassGCN(torch.nn.Module):def__init__(self):super().__init__()self.conv1=GCNConv(1,16)self.conv2=GCNConv(16,16)defforward(self,data):x,edge_index=data.x,data.edge_indexx=self.conv1(x,edge_index)x=F.relu(x)x=F.dropout(x,training=self.training)x=self.conv2(x,edge_index)returnxdefreset_parameters(self):self.conv1.reset_parameters()self.conv2.reset_parameters()model=GCN()dataset=BRECDataset()evaluate(dataset,model,device=torch.device("cpu"),log_path="log.txt",training_config=None)
Package: brec-icml2024
An Empirical Study of Realized GNN ExpressivenessAboutThis package is official implementation of the following paper: An Empirical Study of Realized GNN Expressiveness. Evalution process can be easily implemented by this package. For more detailed and advanced usage, please refer toBRECBRECis a new dataset for GNN expressiveness comparison.
It addresses the limitations of previous datasets, including difficulty, granularity, and scale, by incorporating
400 pairs of various graphs in four categories (Basic, Regular, Extension, CFI).
The graphs are organized pair-wise, where each pair is tested individually to return whether a GNN can distinguish them. We propose a new evaluation method,RPC(Reliable Paired Comparisons), with a contrastive training framework.UsagesInstallInstallpytorchandpytorch_geometricwith corresponding versions aligning with your device. Thenpip install brec-icml2024.ExampleHere is a simple example:importtorchimporttorch.nn.functionalasFfromtorch_geometric.nnimportGCNConvfrombrec.datasetimportBRECDatasetfrombrec.evaluatorimportevaluateclassGCN(torch.nn.Module):def__init__(self):super().__init__()self.conv1=GCNConv(1,16)self.conv2=GCNConv(16,16)defforward(self,data):x,edge_index=data.x,data.edge_indexx=self.conv1(x,edge_index)x=F.relu(x)x=F.dropout(x,training=self.training)x=self.conv2(x,edge_index)returnxdefreset_parameters(self):self.conv1.reset_parameters()self.conv2.reset_parameters()model=GCN()dataset=BRECDataset()evaluate(dataset,model,device=torch.device("cpu"),log_path="log.txt",training_config=None)
Package: bredg
IntroductionTODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project.Getting StartedTODO: Guide users through getting your code up and running on their own system. In this section you can talk about:Installation processSoftware dependenciesLatest releasesAPI referencesBuild and TestTODO: Describe and show how to build your code and run the tests.ContributeTODO: Explain how other users and developers can contribute to make your code better.If you want to learn more about creating good readme files then refer the followingguidelines. You can also seek inspiration from the below readme files:ASP.NET CoreVisual Studio CodeChakra Core
Package: breezeblocks
BreezeBlocks is a lightweigt SQL abstraction layer that seeks to allow users
to interact with their database as a relational store. The user constructs
Python objects which represent the structure of the database, but these are
then used to build SQL statements and do not also represent records.In other words, BreezeBlocks attempts to avoid or delay, depending on how
you see it, establishing an object-relation mapping. Eventually any query
result will need to be instantiated as a Python object in theisinstance(o, object)sense, but not always in the class-based object-
oriented sense. BreezeBlocks does use Python classes, but by not making
a 1:1 correspondence of database tables to classes it can allow for more
natural use of the other paradigms Python provides.BreezeBlocks is designed as a statement builder rather than an ORM.
SQL Syntax is exposed in Python classes which are passed into methods for
query construction. Query results are plain-old-data types similar to a C
struct. They provide access to fields of the row by name, but are still
compact and don’t have as much usage overhead as most Python objects.The contrasting approach is an ORM implementing something similar to
the Active Record pattern. A class is defined for each table,  with class-level
properties representing the columns. Rows in the table become instances of
their class.This package is meant to help you use databases, not manage databases.
Querying, inserting, updating, and deleting (row-level operations) are within
scope of the project. Creating tables, views, and triggers is not.
Package: breezecli
# breeze-cliThis package provides a unified command line interface for breeze related actions.The breeze-cli package works on Python3 versions:3.3.x and greater3.4.x and greater3.5.x and greater3.6.x and greater3.7.x and greater## 使用 pip 安裝 Breeze CLIBreeze CLI 在 Linux、Windows 和 macOS 的主要分发方式是 pip。这是 Python 通用的套件管理工具，其提供一个简单的方法來安裝、升级和移除 Python 套件及其相依性。#### 安裝 AWS CLI 的最新版本如果你已经有pip3和支持的Python3版本，则可以使用以下命令安裝Breeze CLI。如果您已安裝Python版本3+，我們建议您使用pip3命令。` pip3 install breezecli `### 升级到Breeze CLI最新版本我們建议您定期检查，來确认是否有Breeze CLI的新版本，並在合适的时机进行升级。` pip install--upgradebreezecli `
Package: breezedb
Source code is available inhttps://github.com/RMed/breezedb_pythonLicense:GPLv2ChangelogNew JSON structureDatabase now consists of a single fileImproved special character supportImproved exception handlingAdded several database operationsIssues and bug reportsPlease report any issues or bugs you may encounter inhttps://github.com/RMed/breezedb_python/issuesNOTE: version 1.2.0 is not compatible with previous versions of the library.OverviewThe data is contained within a single file usingJSONstructure.All database operations are done to the filesystem.Uses user session permissions for the databaseIt is not needed to distribute a database with your application, as it can be created on the go.InstallationLinux/Unix (run withsuperuserpermissions):# python setup.py installor using pip:# pip install breezedbWindows (run asadministrator):python.exe setup.py installor using pip:python.exe pip install breezedbor use the provided installer.DocumentationDocumentation is available online inhttp://pythonhosted.org/breezedb. This documentation includes all the available functions and extra information about the structure of the database and the query parser.If you want to build the documentation from source, navigate to thedocdirectory and run:make htmlin Linux/Unix systems or:make.bat htmlin Windows systems.TestsThere are several basic tests available in thetestdirectory that can be run after the library is installed.
Package: breeze-email-reports
The Breeze Church Management System (CHMS) is used by many churches to manage
their operations. Breeze has modules to support (not necessarily a complete list):A database of church members, with flexibility on data to keep on membersTracking giving, including pledges, and preparing giving statementsCreating events, with volunteer management and attendance trackingOnline givingEmails and texts to membersOnline formsBreeze also has a network REST Application Programming Interface (API) that provides remote applications access
to a church’s Breeze data. While the interface is pretty obtuse, the API
makes it possible to retrieve and update a church’s data outside of
Breeze’s normal web interface. The command-line
utilities in this package do not update any data, but they can be used to
email periodic reports on Breeze.The current release contains one utility:email_profile_report,
which can be used
to periodically email a report to selected recipients detailing changes
in a church’s member database between runs. Other utilities may be added in future releases.Using these facilities takes a fair amount of configuration to provide
the credentials needed to access the Breeze API and to allow
sending emails. Both of these are implemented in dependent packages,
but to make it easier for users some basic detail is included in the documentation.SeeDOCUMENTATIONfor details on use how to set up and use these reports.