Saravanan666/pypi-org huggingface dataset:
Package: wuppercodegen
The Wupper Code Generator is a tool to generate various files used for the
implementation of configuration mechanism of the FELIX interface card
firmware. Files that can be generated include:A VHDL description of configuration parameters with
required datatypes (e.g., a list of VHDL record types).A VHDL file for a register mapping, which relates parameter
register to PCIe addresses. This can include write- and read-processes
for all configuration registers.A matching C header file, which matches the register mapping described
in the previous point to C datastructures which represent the different
configuration options.A (partial) OKS schema for the firmware parameters. This still needs to
be extended with an OKS schema for the software configuration options. It
is yet to be determined how much of the H/W OKS schema can be autogenerated,
as not all parameters of the firmware should be configurable using an OKS database.Other use cases are thinkable, e.g., automatic documentation of the parameters,
registers, datatypes, etc.The Wupper Code Generator tool uses two kinds of inputs:A configuration file describing all configuration registers of the firmware, as well
their data types, default values, and other relevant information.
The format of the input file is YAML.A (set of) template file(s), describing how the output of the tool should
look like.Jinja2is used as template engine.Additionally, the tool automatically generates a unique address for each
register. This can be used to assign individual registers to addresses
in the PCI memory mapping.
Package: wurfl-cloud
ScientiaMobile WURFL Cloud Client for Python
The WURFL Cloud Service by ScientiaMobile, Inc., is a cloud-based mobile device detection service that can quickly and accurately detect over 500 capabilities of visiting devices. It can differentiate between portable mobile devices, desktop devices, SmartTVs and any other types of devices that have a web browser.This is the Python Client for accessing the WURFL Cloud Service, and it requires a free or paid WURFL Cloud account from ScientiaMobile:http://www.scientiamobile.com/cloud
Package: wurlitzer
WurlitzerCapture C-level stdout/stderr pipes in Python viaos.dup2.For more details on why this is needed, please readthis blog post.Installpip install wurlitzerUsageCapture stdout/stderr in pipes:fromwurlitzerimportpipeswithpipes()as(out,err):call_some_c_function()stdout=out.read()Capture stdout/stderr in StringIO:fromioimportStringIOfromwurlitzerimportpipes,STDOUTout=StringIO()withpipes(stdout=out,stderr=STDOUT):call_some_c_function()stdout=out.getvalue()Forward C-level stdout/stderr to Python sys.stdout/stderr,
which may already be forwarded somewhere by the environment, e.g. IPython:fromwurlitzerimportsys_pipeswithsys_pipes():call_some_c_function()Or even simpler, enable it as an IPython extension:%load_ext wurlitzerTo forward all C-level output to IPython during execution.AcknowledgmentsThis package is based on stuff we learned with @takluyver and @karies while working on capturing output from theCling Kernelfor Jupyter.Wurlitzer?!Wurlitzermakes pipe organs. Get it? Pipes? Naming is hard.
Package: wurm
wurmWurm is a simple sqlite3-based ORM.Table of ContentswurmUsageInstallationChangelog0.1.00.0.2LicenseUsage# create a table:@dataclassclassPoint(wurm.Table):x:inty:int# types currently supported: int, str, bytes, bool, float, datetime.time,#     datetime.date, datetime.datetime, pathlib.Path# sqlite3 connections cannot be shared, so call setup_connection once per threadwurm.setup_connection(sqlite3.connect(":memory:"))# adding new instances to the database:point=Point(1,0)print(point.rowid)# Nonepoint.insert()print(point.rowid)# 1# making changes:point.x=2point.commit()# simple queries:point=Point[1]# get by rowiddelPoint[1]# delete by rowidpoint.delete()# delete from an objectall_points=list(Point)# iterate over a table to get instances for all rowsnumber_of_points=len(Point)# get the total number of rows in the tableInstallationwurm is distributed onPyPIas a universal
wheel and is available on Linux/macOS and Windows and supports
Python 3.7+.$pipinstallwurmChangelog0.1.0Addwurm.Table.query()andwurm.Query.Removewurm.Table[rowid]getter and deleter.Add documentation for the public interface.0.0.2Ensure tables are created, even in edge cases.Add support fordate,time,datetimeandPath.Addwurm.Unique[T].Licensewurm is distributed under the terms of theMIT License.
Package: wurst
WurstShow how the sausage is made!Wurst is a python package for linking and modifying industrial ecology models, with a focus on sparse matrices in life cycle assessment. It provides the following:Helper functions to filter activities and exchangesHelper functions to link exchangesTransformation functions to change markets, change input efficiencies, and change emissionsData IO withBrightway2Logging framework and a log browserSee also the separatewurst examplesrepository.InstallationDownload and installminiconda, create and activate anew environment, and then install::conda install -c conda-forge brightway2 jupyter wurstLicenseBSD 2-clause license. Contributions are welcome!AuthorsChris MutelBrian CoxTODOReview BW2 IO code to make sure all needed fields are present in newly-created and modified databasesParameterized exchanges (e.g. electricity sector)Check logging on all transformation functionsLog browser web app
Package: wusa
WusaIsis (Ancient Egyptian: ꜣst; Coptic: Ⲏⲥⲉ Ēse; Classical Greek: Ἶσις Isis; Meroitic: 𐦥𐦣𐦯‎ Wos[a] orWusa) was a major goddess in ancient Egyptian religion whose worship spread throughout the Greco-Roman world.Source:WikipediaWusa is also a command-line tool to help managecontainerized self-hosted GitHub Action Runner. In some rare cases, you might require special hardware to execute your CI/CD pipeline. For these cases,wusaremoves the burden of setting up a docker container on your local machine, connecting it to your GitHub repositories, and managing it over time.WARNINGwusa is in the early stages, and issues might appear. Please try it out and let me know what you think of wusa.InstallationIf you wish to install wusa, use pippipinstallwusaor usepipxpipxinstallwusaUsageWusa uses, at the moment, a ubuntu image with the GitHub Action runners. Wusa requires permission to be able to create runners for you. For this, run the following command and follow the steps:wusaauthAfterward, you can create a containerized docker runner for a repo by runningwusacreate"ahelm/wusa"With"ahelm/wusa"is the short name of the repository.If you wish to list all the runner for a repository, runwusalist-repo"ahelm/wusa"or if you wish to remove a runnerwusaremove<some_runner_name>
Package: wutils
wutilsA collection of Python utility functions/classes.Currently only provides one class:wutils.mat.MarkedMatrix, which is a wrapper around anumpy.arraywith additional row labels and helper functions.Can be installed withpip install wutils.Exampleimportnumpyasnpimportmatplotlib.pyplotaspltfromwutils.matimportMarkedMatrix# Create a MarkedMatrix from a tuple of label-matrix tuplesmm=MarkedMatrix((('a',np.random.randn(100,100)),('b',np.random.randn(50,100))# num. of columns must match 'a'))# Create a labeled TSNE plot of the componentsplt.figure()mm.tsne()plt.show()# Perform SVD on the full matrixU,_,_=np.linalg.svd(mm.get_mat(),full_matrices=False)# Form another MarkedMatrix consisting of the first 2 columns of U.# We reuse our existing labelsmm_U=MarkedMatrix((U[:,2],mm.get_loc_idx()))# Split up the MarkedMatrix to an OrderedDict of label to submatrixprint(mm_U.get_pieces())# Output:# OrderedDict([#     ('a', array([...])),#     ('b', array([...]))# ])# where 'a' is 100 x 2# and 'b' is 50 x 2
Package: wutongchain-cts
梧桐链CTS的Python封装 SDK官方文档：https://lgb.wutongchain.com/file/ctsdec.pdf背景 (Backgrounds)CTS是梧桐链（同济区块链）的轻量级独立服务，主要应用场景为存证，可以说是为存证领域而特制的，便于使用的API和服务。方便对区块链本身不熟悉、但适合使用区块链做存证的场景进行方便、高效对接现有业务；区块链浏览器官方区块链浏览器：https://cts.wutongchain.com/Python 环境受限于时间，仅在Python 3.6.9 Mac上调试，并通过100%测试覆盖率安装pip install wutongchain-cts使用初始化对象from wutongchain_cts.api import CTSAPI
cts_instance = CTSAPI(app_id="your_app_id", secret_key="your_secret_key")++注：存证平台服务会对每个访问请求进行身份验证，通过 appid 和 secretkey（用户密钥）来验证请求的发送者身份。appid 和 secretkey 由存证平台颁发给访问者。++调用类方法实现不同功能，可以通过详细示例代码.py参考示例：查询目前链的区块高度调用方法：cts_instance.get_height().json()输入参数：无返回：目前链的区块高度预期返回示例：{'code': 200, 'data': {'height': 80}, 'msg': ''}按区块高度获取区块详情说明：通过区块高度来查询获取到区块的详细信息，如区块哈希，前一区块哈希，交易哈希等内容。调用方法：cts_instance.get_block_detail_by_height(<height>).json()输入参数：height: 所需查找的区块高度预期返回：{
  "code": 200,
  "data": {
    "data": {
      "header": {
        "version": 1,
        "height": 2,
        "timestamp": 1601450330,
        "blockHash": "pl+yAjHm9YRo4/rG9+qSOx+IzM2wImNlm8+/rLQ99xw=",
        "previousHash": "Ep7j7pDgg2/Brnvjcv5vQ8+NFuN40GeK1UQK1gqwUJA=",
        "worldStateRoot": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA=",
        "transactionRoot": "fArdOmAKt7jygo4dKrrnrkPuMxW4cwP1Goqfwzg/D30="
      },
      "txs": [
        "veN+LAbEXz6P3GE2ldYtTbFRZE0KtKo4jylc+CuJudg="
      ],
      "extra": "eyJtaW5lciI6IlFtYTlMNU42ZW5Kck5GYmRGQnhXaURhWHBUUnhSRlVRWUxnMWt6NEhMRnRlZW8ifQ==",
      "raw": "AQAAAAIAAAAAAAAA9srg3XQBAAAgAAAAEp7j7pDgg2/Brnvjcv5vQ8+NFuN40GeK1UQK1gqwUJAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgAAAAfArdOmAKt7jygo4dKrrnrkPuMxW4cwP1Goqfwzg/D306AAAAeyJtaW5lciI6IlFtYTlMNU42ZW5Kck5GYmRGQnhXaURhWHBUUnhSRlVRWUxnMWt6NEhMRnRlZW8ifQ=="
    }
  },
  "msg": ""
}按区块哈希获取区块详情说明：通过区块哈希来查询获取到区块的详细信息，如区块哈希，前一区块哈希，交易哈希等内容调用方法：cts_instance.get_block_detail_by_hash(<hash>).json()输入参数：hash: 区块哈希预期返回：(同上返回)创建存证说明：创建存证内容，并返回哈希值和是否成功创建调用方法：data = 'test/ 测试内容 _by_wally'
business_id = '12345678'
print(cts_instance.put_data(data=data, business_id=business_id).json())输入参数：data: 存证内容businessId: 用户应用中的业务 id，长度不超过 64预期返回：{'code': 200, 'data': {'Figure': 'KZXP53J1Pp9N8xbEelGJ99GnVYSy3rynJKtXKer1AaU=', 'OK': True}, 'msg': ''}注：偶尔会发生如下情况：{'code': 500, 'data': '', 'msg': {'requestId': '4158a50d-f0ef-4f13-9e10-00d52376ee6c', 'code': 'ETIMEDOUT', 'message': 'Internal Server Error'}}或：{'code': 500, 'data': '', 'msg': {'requestId': '002792c0-18f4-461e-bb32-d92ef878f7f9', 'code': 'ECONNREFUSED', 'message': '服务器开小差了，请稍后再试'}}以上情况需要开发者做好容错处理获取存证说明：通过创建存证交易返回的哈希值来获取到该存证交易所在区块的高度和存证内容调用方法：cts_instance.get_data('KZXP53J1Pp9N8xbEelGJ99GnVYSy3rynJKtXKer1AaU=').json()输入参数：hash: 通过创建存证交易返回的哈希预期返回：{'code': 200, 'data': {'data': 'test/ 测试内容 _by_wally', 'businessId': '12345678', 'blockHeight': 90, 'timestamp': 1603097791}, 'msg': ''}开源许可本代码永久遵循MIT License许可，允许个人和商业用途
Package: wvalidate
wvalidateIntroductionWValidate is a validation library.InstallationRequirementsPython 3.8+pipinstallwvalidateBasic usageCreating a simple string validatorfromwvalidateimportValidateasv# creating a validator for stringmy_validator=v.string()my_validator.is_valid("Maria")# => (True, None)my_validator.is_valid(42)# => (False, ValidatorError)Creating a dict validatorfromwvalidateimportValidateasvuser_validator=v.dict({"name":v.string()})user_validator.is_valid({"name":"Fernanda"})# => (True, None)user_validator.is_valid({"name":31})# => (False, ValidatorError)PrimitivesfromwvalidateimportValidateasv# primitive valuesv.string()v.integer()v.float()v.numeric()StringsfromwvalidateimportValidateasvv.string(equal="EQUAL")v.string(min=1)v.string(max=5)v.string(min=2,max=7)v.email()NumbersfromwvalidateimportValidateasvv.integer(min=1)v.integer(max=5)v.integer(min=2,max=7)v.float(min=1)v.float(max=5)v.float(min=2,max=7)# valid integers and floatsv.numeric(min=1)v.numeric(max=5)v.numeric(min=2,max=7)EnumsfromwvalidateimportValidateasv# A list of any type must be passedv.enum(["rock","paper","scissors"])v.enum([True,False])v.enum([5,"FIVE"])my_validator_enum=v.enum([5,"FIVE"])my_validator_enum.is_valid(5)# => (True, None)my_validator_enum.is_valid("SIX")# => (Flase, ValidatorError)NullablesfromwvalidateimportValidateasv# Any Validator must be passedv.nullable(v.string())v.nullable(v.enum([True,False]))v.nullable(v.dict({"name":v.string(),"age":v.integer()}))my_validator_nullable=v.nullable(v.string())my_validator_nullable.is_valid("Maria")# => (True, None)my_validator_nullable.is_valid(None)# => (True, None)my_validator_nullable.is_valid(3)# => (Flase, ValidatorError)ListsfromwvalidateimportValidateasv# Any Validator must be passedv.list(v.string())v.list(v.enum([True,False]))v.list(v.dict({"name":v.string(),"age":v.integer()}))my_validator_list=v.list(v.string())my_validator_list.is_valid(["ONE","TWO","THREE"])# => (True, None)my_validator_list.is_valid(["ONE","TWO",3])# => (Flase, ValidatorError)DictionariesfromwvalidateimportValidateasvv.dict({"name":v.string(),"price":v.numeric(min=0),"category":v.enum(["food","drink"])})v.dict({"name":v.string(),"price":v.integer(min=0),"address":{"city":v.string()}})v.dict({"users":v.list(v.dict({"name":v.string(),"price":v.integer(min=0),}))})user_validator=v.dict({"name":v.string()})user_validator.is_valid({"name":"Fernanda"})# => (True, None)user_validator.is_valid({"name":31})# => (False, ValidatorError)
Package: wvfreader
wvfreaderYokogowa Oscilloscope WVF file reader with basic plotting functionExample Usageimport wvfreader

# Get Some Data
datafiles = wvfreader.datafile()

# Get some info on the first file
datafiles[0].info()

# Files and Traces can be accessed by name
files = datafiles[['file1','file2']]
traces = datafiles['file1'].traces['trace1,trace2']

# Plot the first and second trace, between time 0s and 5s
[datafiles[0].traces[num].plot(t_ind=(0,5)) for num in [0,1]]

# If Bokeh is installed, you can save plots to interactive HTML files
# This will down sample your data if it has more than 15,000 points
datafiles[0].traces[0].plot(output='html')
Package: ww-audio-shot-detection
BallTracking AnnotatorRequired SoftwarePython3.6.9virtualenvInstallationexportPYTHON3_PATH=PATH_TO_YOUR_PYTHON3_BIN_HERE
./installTo Run [Command Line]There are several steps within the pipeline each with their own bash script wrapperThe first step is done with a playstation 4 controller.  The user then does their best to keep the bouning box around the wall for the entirety of the video.  There are also commands to rewind, pause, speed up, and slow down.
To start this step:./big_box_trackVIDEO_PATH_HEREAs long as no other future steps have been run this step can be rerun to make fixes, etc..This requires no user interaction.  This step finds the smaller bounding box within the bounding boxes the user made in step 1../auto_trackVIDEO_PATH_HEREThis is used to find any poorly placed tight bounding boxes and fix them.  Also done with a PS4 controller../edit_auto_detVIDEO_PATH_HEREThis goes to any frame where no ball could be detected in the bounding box created in step 1 and allows the user to fill them in../edit_undetVIDEO_PATH_HERECreates the annnotation output and allows for final sanity checks../create_annotationsVIDEO_PATH_HEREUploads the videos to S3 and saves to a DynamoDB database./uploadVIDEO_PATH_HERETo Run [UI (PyQt]
Package: wwchartlib
Provides some colourful Qt chart widgets.  Requires thePySideQt
bindings.At this time, wwchartlib provides a couple of pie chart widgets.  More
widgets may come in time.  Feel free to contribute!wwchartlib.piechart.PieChartA simple pie chart widget.wwchartlib.piechart.AdjustablePieChartA pie chart whose slices are adjustable with click and drag mouse
movement.Defines two additional signals:itemAdjustedEmitted when an item is adjusted, with that item as the argument.
If two slices are adjusted at the same time, two signals are
emitted.finishedAdjustingEmitted when an adjustment is finished (i.e., the user releases the
mouse).  There are no arguments.
Package: wwdata
wwdataData analysis package aimed at data obtained in the context of (waste)waterFree software: GNU General Public License v3Documentation:https://ugentbiomath.github.io/wwdata-docs/Funding: Waterboard De DommelContext: PhD research at BIOMATH, Ghent UniversityStructureThe package contains one class and three subclasses, all in separate .py files. Division in subclasses is based on the type of data:online data from full scale installations (OnlineSensorBased)online data from lab experiments (LabSensorBased)offline data obtained from lab experiments (LabExperimentBased).Jupyter notbeook files (.ipynb) illustrate the use of the available functions. The most developed class is the OnlineSensorBased one. The workflow of this class is shown in below Figure, where OSB represents an OnlineSensorBased object. Main premises are to never delete data but to tag it and to be able to check the reliability when gaps in datasets are filled.ExamplesFor the workflow with code and more specific examples, check out the Showcase Jupyter Notebook(s) included as documentation of the package.CreditsThis package was created with support fromCookiecutterand theaudreyr/cookiecutter-pypackageproject template, as well as thisGitHub page, provided byDalerand explaining how to use sphinx documentation generation in combination with GitHub Pages.History0.1.0 (2017-10-23)First release on PyPI.The wwdata (wastewater data) package is meant to make data analysis, validation and filling of data gaps more streamlined. It contains code to do all this, while also providing simple visualisations of the whole procedure.The package was (and is) developed in the framework of PhD research, involving the modelling of a full scale wastewater treatment plant (WWTP). Online measurements at the plant are available, but as with all data, is not perfect and therefor needs validation. The gap filling originated from the need to have high-frequency influent data available to run the WWTP model with.0.2.0 (2018-06-12)Second release on PyPI.The wwdata (wastewater data) package is meant to make data analysis, validation and filling of data gaps more streamlined. It contains code to do all this, while also providing simple visualisations of the whole procedure.The package was (and is) developed in the framework of PhD research, involving the modelling of a full scale wastewater treatment plant (WWTP). Online measurements at the plant are available, but as with all data, is not perfect and therefor needs validation. The gap filling originated from the need to have high-frequency influent data available to run the WWTP model with.New in version 0.2.0:Bug fixesAddition of anonly_checkedargument to multiple functions to allow application of the function to only the validated data points (‘original’ in self.meta_valid).Extended, improved and customized documentation website (generated with sphinx).Extended and improved Jupyter Notebook for documentation.Improved visualisation forget_correlation: a prediction band based on the obtained correlation is now included in the produced scatter plot.Known bugs:See (open issues on Github)[https://github.com/UGentBiomath/wwdata/issues])
Package: wwdtm
OverviewThis project provides a Python library that provides an interface to
retrieve data from a copy of theWait Wait Stats Database.If you are in need of a pre-built package to use to build applications, the
library is available atPyPI.RequirementsStarting with version 2.5.0, the minimum supported version of Python has been
changed from Python 3.8 to 3.10. All versions prior to 3.10 will no longer
be supported.Testing for this library has been done using Python 3.10 and 3.12.In addition to the Python version requirement, the library depends on a copy
of theWait Wait Stats Databaserunning on a MySQL Server (or a distribution
of MySQL Server like Percona) running version 8.0 or higher.Running TestsIncluded in this repository are tests that are written for use withpytest.
To run the tests, simply run:pytestfrom the root of the repository.A performance testing script is also included in the repository named,perf_test.pythat tests the core class methods. This script can be used
to create a performance baseline and also used to track changes in performance
between code changes or configuration changes.DocumentationThis project usesreStructuredTextlocated in docstrings and individual
files for its documentation and makes use ofSphinxto build an HTML
(and other formats supported by Sphinx) version of documents. To build the
documentation for this project, usevenv,virtualenvor a similar tool
of your choice to create a virtual environment underdocs/and install the
required packages indocs/requirements.txt, including Sphinx and theFlasktheme.The documentation style guide closely follows the one documented in thePython Developer’s Guide.Once the required packages are installed, an HTML version of the documentation
can be generated by running:makehtmlAn online version of the documentation is also available atdocs.wwdt.meBuildingAfter tests have been successfully run, any and all documentation updates have
been made, a release wheel can then be created for distribution. To create a
wheel, run the following command with the virtualenv activated.python-mbuildKnown IssuesFor documentation on known issues with this project, check out theKnown Issuesdocumentation ondocs.wwdt.me.Code of ConductThis projects follows version 2.1 of theContributor Covenant’sCode of
Conduct. A copy of theCode of Conductdocument is included in this
repository.LicenseThis library is licensed under the terms of theApache License 2.0.
Package: wwf
Walk with fastaiWhat is this project?Welcome to Walk with fastai! This project was started by me (Zachary Mueller) as a way to collect interesting techniques dotted throughout thefast.ai forums, my own course materials, and the fantastic work of others into one centralized place.The goal is to have something much more than a "fastai recipe book," where instead authors can explore in-depth into topics involving the usage of thefastailibrary.There is a central framework and theme for each super chapter, as you can see in the Table of Contents menu at the top of this screen. Topics are broken down by their super topic, such as:VisionClassificationSingle LabelThese collection of articles can be as simple as showing a few lines of code for a use-case, to as advanced as introducing and explaining a topic.At the end of the day, I want this site to be a nice resource for folks to look up quickly how to do XYZ technique inside the library, that perhaps isn't 100% integrated or supported in the library's current status.
Package: wwidget
WWIDGETThis package is to fast embed html snippets  to any web applicationWWIDGET Usagefrom wwidget.login.login import LoginWidget

tpl = LoginWidget(
    template='a_login.html',
    username={
        'required': True,
        'id': 'username'
    },
    password={
        'required': True
    },
    button={
        'value': 'Sign in'
    },
    form_attrs={}
)

tpl.outputOptionsform_attrs: supports any attributesaction: if not set empty url is taken as defaultmethod: if not set POST is taken as defaultusername, password: as a dictionary holding required, id, classbutton: as a dictionary holding value, type, class, id, name, style
Package: wwjfunction
WwjFunction在这个模块中一共有四个函数，分别用来计算加法、减法、乘法、除法加法-add计算加法的程序为add，用户只需要输入两个参数即可得出加法的结果。调用格式为wwjfunction.add(a,b)减法-sub计算加法的程序为sub，用户只需要输入两个参数即可得出减法的结果。调用格式为wwjfunction.sub(a,b)注意：这里得出来的是绝对值乘法-mult计算加法的程序为mult，用户只需要输入两个参数即可得出加法的结果。调用格式为wwjfunction.mult(a,b)除法-div计算加法的程序为div，用户只需要输入两个参数即可得出加法的结果。调用格式为wwjfunction.div(a,b)