Saravanan666/pypi-org huggingface dataset:
Package: damealgorithms
Table of Contentshttps://python-packaging.readthedocs.io/en/latest/minimal.htmlTo install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damealgorithms-0.0.1.tar.gzTo install from Internet:
$ pip3 install damealgorithmsIf you upload various tar.gz to pypi, you can need remove old files in dist directory and repeat the process:
$ rm dist/*tar.gz
$ python3 setup.py register sdist
$ twine upload dist/damealgorithms-0.0.1.tar.gz
Package: damebasics
What?That's a package to run tests about basics of Python.
For example, lists, strings, for, dictionaries, ...Run tests!$ ./runtests.shGive me the packagehttps://python-packaging.readthedocs.io/en/latest/minimal.htmlTo install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damebasics-0.0.1.tar.gzTo install from Internet:
$ pip3 install damebasicsIf you upload various tar.gz to pypi, you can need remove old files in dist directory and repeat the process:
$ rm dist/*tar.gz
$ python3 setup.py register sdist
$ twine upload dist/damebasics-0.0.1.tar.gz
Package: dame-cli
Desktop Application for Model Execution (DAME)The Desktop Application for Model Execution (DAME) is an application for executing environmental models in any local environment or server through a command line interface.DAME contains a registry of model containers and input data files, as well as metadata about what input data needs to be loaded to run regional configurations and setups of any given model.Given a model identifier (e.g., TopoFlow for the Awash region:topoflow36_2.1.0_Awash), DAME downloads the model container and its execution environment, and fetches the datasets needed (e.g., soil data, elevation data, etc). Then users can run the model with different input scenarios.DAME works in Linux, MacOS and Windows.  It is installed through a simple pip command.RequirementsDocker Configuration [MacOS, Windows, Linux]:DockerPython >= 3.6DockerDAME can use Docker to manage and run containers of software components.Installation on LinuxInstallation on MacOSInstallation on WindowsPython 3DAME uses Python. To install Python, just follow the steps below:Installation on LinuxInstallation on MacOSInstallation on WindowsInstallationTo install the latest version of DAME, open a terminal and run:pipinstalldame-cliDocumentationFull documentation of the CLI, including usage examples, can be found at:https://dame-cli.readthedocs.io/en/latest/
Package: damedb
<div id=”table-of-contents”>
<h2>Table of Contents</h2>
<div id=”text-table-of-contents”>
<ul>
<li><a href=”#sec-1”>1. Installing</a></li>
<li><a href=”#sec-2”>2. Check Test</a></li>
<li><a href=”#sec-3”>3. Pypi</a></li>
</ul>
</div>
</div>Learning about databases and python from tests by David Arroyo
Menéndez.# Installing<a id=”sec-1” name=”sec-1”></a>Installing Mongo:https://docs.mongodb.com/manual/tutorialInstalling MySQL:https://dev.mysql.com/doc/mysql-installation-excerpt/5.7/en/Downloading SQLite:https://www.sqlite.org/download.html# Check Test<a id=”sec-2” name=”sec-2”></a>Execute all tests:$ nosetests3 testsExecute one file:$ nosetests3 tests/test_basics.pyExecute one test:nosetests3 test/test_syn.py:TddInPythonExample.test_syn_returns_correct_result# Pypi<a id=”sec-3” name=”sec-3”></a>To install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damedb-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/dn
$ cd /tmp/dn
$ source bin/activate
$ pip3 install damedb
Package: damefaces
<div id=”table-of-contents”>
<h2>Table of Contents</h2>
<div id=”text-table-of-contents”>
<ul>
<li><a href=”#sec-1”>1. Source</a></li>
<li><a href=”#sec-2”>2. Pypi</a></li>
</ul>
</div>
</div>DamePhoto by David Arroyo Menéndez# Source<a id=”sec-1” name=”sec-1”></a>This source is modified from <https://github.com/smahesh29/Gender-and-Age-Detection>
and redistributed under GPLv3.This source is only for gender detection.# Pypi<a id=”sec-2” name=”sec-2”></a>To install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damephoto-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install damephoto
Package: dame-flame
DAME-FLAMEA Python package for performing matching for observational causal inference on datasets containing discrete covariatesDocumentationhereDAME-FLAME is a Python package for performing matching for observational causal inference on datasets containing discrete covariates. It implements the Dynamic Almost Matching Exactly (DAME) and Fast, Large-Scale Almost Matching Exactly (FLAME) algorithms, which match treatment and control units on subsets of the covariates. The resulting matched groups are interpretable, because the matches are made on covariates, and high-quality, because machine learning is used to determine which covariates are important to match on.InstallationDependenciesdame-flamerequires Python version (>=3.6.5). Install fromhereif needed.pandas>=0.11.0numpy>= 1.16.5scikit-learn>=0.23.2If your python version does not have these packages, install fromhere.To run the examples in the examples folder (these are not part of the package), Jupyter Notebooks or Jupyter Lab (availablehere) and Matplotlib (>=2.0.0) is also required.User InstallationDownload from PyPi via
$ pip install dame-flame
Package: dameformats
To execute tests:$ cd dameformats
$ ./runtests.sh
$ nosetests3 testsPypiTo install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/dameformats-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install dameformats
Package: damefunniest
https://python-packaging.readthedocs.io/en/latest/minimal.htmlTo install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damefunniest-0.1.tar.gz
$ twine upload –repository-urlhttps://test.pypi.org/legacy/dist/*You can install from Internet in a python virtual environment to cheRRRck:
$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install damefunniestIf you upload various tar.gz to pypi, you can need remove old files in dist directory and repeat the process:
$ rm dist/*tar.gz
$ python3 setup.py register sdist
$ twine upload dist/damefunniest-0.1.tar.gz
Package: damei
dameidamei(大妹) library。涉及深度学习和量子力学交叉。提供常用函数、控制台、解算器等。1.安装pypi安装:pip install damei下载源码后：unzip damei-master.zip
cd damei-master
python setup.py install2.使用详细API文档importdameiasdm3.更新日志"""20200808 v1.0.0 初始版本20210303 v1.0.15 general.letterboxgeneral.plot_one_box_trace_pose_statusgeneral.xyxy2xywhgeneral.xywh2xyxydm.torch_utils.select_device20211010 v1.0.153 dm.tools.check_COCO dm.tools.check_YOLO20211201 v1.0.154 数据增强，根据mask的目标的随机位置、随机缩放和随机旋转20211210 v1.0.155 dm.genral.pts2bbox20211223 v1.0.156 dm.video2frames20211223 v1.0.157 dm.misc.list2tabledm.misc.flatten_list20220114 v1.0.158 dm.general.torch_distributed_zero_firs20220117 v1.0.159 dm.getLogger(name=None, name_lenth=12, level=logging.INFO)20220215 v1.0.160 dm.misc.dict2info(info_dict)  # 字典带颜色转为方便查看的字符串dm.current_system()  # 返回linux windows macosdm.system_lib_suffix()  # 返回.so .dll .dylib20220304 v1.0.161 支持无torch库时import damei，有torch库时能调用20220305 v1.0.162 ct = dm.current_time()  # 当前时间et = dm.plus_time(ct=None, seconds=1)  # 未来某个到期时间bool = dm.within_time(et, ct=None)  # 输入到期时间，判断当前时间是否在内dm.rsa.gen_rsa(length=1024)  # 在随机生成公钥-私钥对，存储在当前路径pubk.pen和privk.pem里dm.rsa.encrypt(plaintext, pubk=None, privk=None, length=1024)  # 用公钥或私钥对明文加密dm.rsa.decrypt(ciphertext, pubk=None, privk=None, length=1024)  # 用私钥或公钥对密文解密dm.rsa.sign(message, privk, hash_method='MD5')  # 签密体制下的签名dm.rsa.verify(message, signature, pubk)  # 签密体制下的验签20220309 v1.0.163 cfg = dm.PyConfig(cfg_file)print(cfg.info())  # 查看配置cfg.merge(cfg2)  # 合并配置20220322 v1.0.164 dm.comm.push_stream(  # 把视频推成流source, ip='127.0.0.1', port=1935, stream_type='rtmp', key=None))20220323 v1.0.165 dmpeg = dm.DmFFMPEG()  # 传入一堆参数for img in imgs:  # 循环中推流dmpeg.push_stream(img)  # 推流# 取流：ffplay rtmp://127.0.0.1:1935/live20220408 v1.1.0 # 新增dm.nnuaii = dm.nn.api.UAII()v1.1.1 # 新增dm.argparse，只读取默认值，不解析命令行参数parser = dm.argparse.ArgumentParser()20220610 v1.1.6 # damei_doc上线20220621 v1.1.7 # damei.comm.push_stream()  提供API文档20230209 v1.2.0 # Lightweight, remove some larger dependencies."""
Package: damejson
<div id=”table-of-contents”>
<h2>Table of Contents</h2>
<div id=”text-table-of-contents”>
<ul>
<li><a href=”#sec-1”>1. To execute tests:</a></li>
<li><a href=”#sec-2”>2. Pypi</a></li>
</ul>
</div>
</div># To execute tests:<a id=”sec-1” name=”sec-1”></a>$ cd damejson
$ ./runtests.sh
$ nosetests3 tests# Pypi<a id=”sec-2” name=”sec-2”></a>To install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damejson-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install damejson
Package: damelibraries
Table of Contents1. Logo2. Introduction3. Install and Check tests in a Library4. Music5. LicenseLogoIntroductionMany people needs little snippets of source to make exercises and
learn a library. You can store your exercises in a repository, such
as,https://github.com/davidam/python-examples.git. It's useful, but
if the library is suffering changes or changing dependencies, perhaps
your snippets is not running.In this project, we are experimenting a way, to store the snippets in
files to execute unit test. So, the snippets is easy to maintain.Install and Check tests in a LibraryIf you want python virtual environment$ python3 -m venv /tmp/dl
$ cd /tmp/dl
$ source bin/activateNow, you can install with pip$ pip install --upgrade pip
$ pip3 install damelibrariesChecking my snippets:$ cd /tmp/dl/lib/python3.5/site-packages/damealgorithms
$ nosetests3 tests
$ cd /tmp/dl/lib/python3.5/site-packages/damejson
$ nosetests3 tests
$ cd /tmp/dl/lib/python3.5/site-packages/damepandas
$ nosetests3 tests
$ cd /tmp/dl/lib/python3.5/site-packages/damenltk
$ nosetests3 tests
$ cd /tmp/dl/lib/python3.5/site-packages/damenumpy
$ nosetests3 tests
$ cd /tmp/dl/lib/python3.5/site-packages/damescipy
$ nosetests3 testsMusichttps://www.youtube.com/playlist?list=PLeobXV-Yyn-LvQydcnr46ZkGh1V6tDGEkLicenseThis document is under aCreative Commons Attribution 4.0 International
Package: damenltk
Table of Contents1. Check Test2. PypiLearning about Natural Language Tool Kit (NLTK) from testsA first version can be found in:https://github.com/Lingwars/GAPLENThanks to GAPLEN by the shared time.Learning NLTK from Tests by David Arroyo MenéndezCheck TestExecute all tests:$ nosetests3 testsExecute one file:$ nosetests3 tests/test_basics.pyExecute one test:nosetests3 test/test_syn.py:TddInPythonExample.test_syn_returns_correct_resultPypiTo install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damenltk-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/dn
$ cd /tmp/dn
$ source bin/activate
$ pip3 install damenltk
Package: damenumpy
Table of Contents1. Check Test2. PypiLearning Numpy from Tests by David Arroyo MenéndezCheck TestExecute all tests:$ nosetests3 testsExecute one file:$ nosetests3 tests/test_basics.pyExecute one test:$ nosetests3 tests/test_basics.py:TestBasics.test_indexingPypiTo install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damenumpy-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install damenumpy
Package: damepandas
Table of Contents1. Check Test2. Packaging stuffLearning Pandas from Tests by David Arroyo MenéndezCheck TestExecute all tests:$ nosetests3 testsExecute one file:$ nosetests3 tests/test_create.pyExecute one test:$ nosetests3 tests/test_create.py:TestCreate.test_seriesPackaging stuffTo install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damepandas-0.1.tar.gzTo install from Internet:
$ pip3 install damepandas
Package: damescikit
DavidTable of Contents1 Check Test
2 PypiLearning machine learning with scikit from Tests by David Arroyo
Menéndez1 Check TestIn the path:,----
| $ cd damescikit
`----Execute all tests:
,----
| $ nosetests3 tests
`----Execute one file:
,----
| $ nosetests3 tests/test_models.py
`----Execute one test:
,----
| nosetests3 tests/test_models.py:TddInPythonExample.test_vectorizer_method_returns_correct_result
`----2 PypiTo install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damenltk-0.1.tar.gzYou can install from Internet in a python virtual environment to
check:
$ python3 -m venv /tmp/dn $ cd /tmp/dn $ source bin/activate $ pip3
install damenltk
Package: damescipy
Table of Contents1. Check Test2. PypiLearning Scipy from Tests by David Arroyo MenéndezCheck TestExecute all tests:$ nosetests3 testsExecute one file:$ nosetests3 tests/test_basics.pyExecute one test:$ nosetests3 tests/test_basics.py:TestBasics.test_descriptivesPypiTo install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damescipy-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/ds
$ cd /tmp/ds
$ source bin/activate
$ pip3 install damescipy
Package: damescraping
<https://python-packaging.readthedocs.io/en/latest/minimal.html>To install from local:
$ pip install -e .To install create tar.gz in dist directory:
$ python3 setup.py register sdistTo upload to pypi:
$ twine upload dist/damescraping-0.1.tar.gz
$ twine upload –repository-urlhttps://test.pypi.org/legacy/dist/*You can install from Internet in a python virtual environment to check:
$ python3 -m venv /tmp/funny
$ cd /tmp/funny
$ source bin/activate
$ pip3 install damescrapingIf you upload various tar.gz to pypi, you can need remove old files in dist directory and repeat the process:
$ rm dist/*tar.gz
$ python3 setup.py register sdist
$ twine upload dist/damescraping-0.1.tar.gz
Package: dame-sexo
This package allows to determine the gender of a person depending on the fisrt name. It does so abut using a list of 95000 names already classied.
If the name given appears in the list, it will provid the gender weather it is male or female. If not it will use the Bayesian NLKT model which provides 80.06% accuracy.Version 0.0.1 works very well with names in Europe and America. It could be wrong with names such as Andrea which are male in Italy but male in the rest of the countries.
Package: damewebutils
Table of Contents1. Logo2. Check Test3. Pypi4. Dame Music5. LicenseWebutils from Tests by David Arroyo MenéndezLogo[]Check TestExecute all tests:$ ./testsbycommands.shPypiRun it!$ dameurls.py http://www.davidam.com
    $ dameimgs.py http://damegender.davidam.com
    $ damerss.py http://damegender.davidam.com/rss-feed.xml
    $ damejson.py https://damegender.davidam.com/names/inter/DAVID_all.jsonPypiTo install from local:$ pip install -e .To install create tar.gz in dist directory:$ python3 setup.py register sdistTo upload to pypi:$ twine upload dist/damenumpy-0.1.tar.gzYou can install from Internet in a python virtual environment to check:$ python3 -m venv /tmp/dw
$ cd /tmp/dw
$ source bin/activate
$ pip3 install damewebutilsDame MusicListen music …LicenseThis document is under aCreative Commons Attribution 4.0 International
Package: damg
JUST A SIMPLE PACKAGEA style of damg team object, I modified a bit base on PyQt5.DAMG: just an object.DAMGERROR: An exception type object.DAMGLIST: An list type object.DAMGDICT: An dict type object.DAMGWORKER: Using QRunable for multi threading.DAMGTHREAD: Using QThread for multi threading.DAMGTHREADPOOL: A thread pool to manage multi threadingEnjoy.
Package: daml
Data-Analysis Metrics Library (DAML)About DAMLThe Data-Analysis Metrics Library, or DAML, focuses on characterizing image data and its impact on model performance across classification and object-detection tasks.Model-agnostic metrics that bound real-world performancerelevance/completeness/coveragemetafeatures (data complexity)Model-specific metrics that guide model selection and trainingdataset sufficiencydata/model complexity mismatchMetrics for post-deployment monitoring of data with bounds on model performance to guide retrainingdataset-shift metricsmodel performance bounds under covariate shiftguidance on sampling to assess model error and model retrainingGetting StartedRequirementsPython 3.8-3.11Installing DAMLYou can install DAML directly from pypi.org using the following command.  The optional dependencies of DAML aretorch,tensorflowandall.  Usingtorchenables Sufficiency metrics, andtensorflowenables Outlier Detection.pip install daml[all]Installing DAML from GitHubTo install DAML from source locally on Ubuntu, you will needgit-lfsto download larger, binary source files andpoetryfor project dependency management.sudo apt-get install git-lfs
pip install poetryPull the source down and change to the DAML project directory.git clone https://github.com/aria-ml/daml.git
cd damlInstall DAML with optional dependencies for development.poetry install --all-extras --with devAlternatively, you can install with optional dependencies used to generate documentation as well.poetry install --all-extras --with dev --with docsNow that DAML is installed, you can run commands in the poetry virtual environment by prefixing shell commands withpoetry run, or activate the virtual environment directly in the shell.poetry shellDocumentation and TutorialsFor more ideas on getting started using DAML in your workflow, additional information and tutorials are in our Sphinx documentation hosted onRead the Docs.ContributingFor steps on how to get started on contributing to the project, including setting up a development environment and running unit tests and building documentation locally, you can follow the steps inCONTRIBUTING.md.AttributionThis project uses code from theAlibi-Detectpython library developed by SeldonIO.  Additional documentation from the developers are also availablehere.POCsPOC: Scott Swan @scott.swanDPOC: Andrew Weng @aweng
Package: dam-lev
Author:Daniel WalkerVersion:0.1.2Date:2023-01-05OverviewThedam_levpackage implements theDamerau–Levenshtein diff algorithm.  That is,
it will take two sequences and determine the minimum number of transpositions, substitutions, insertions, and
deletions needed to transform the first sequence into the second.UsageThe package exposes a single function,dam_lev.get_changes.  It takes two sequences (i.e., they must
implement the__len__and__getitem__methods) and returns a list ofdam_lev.Mutationobjects.  There are four subclasses ofdam_lev.Mutationcorresponding to the four types of
transformations.  For example,diffs=dam_lev.get_changes('abcdef','bcedxy')print(diffs)# [Deletion(at=0), Transposition(at=3), Substitution(at=5, at2=4), Insertion(at=6, at2=5)]We see that the sequence of transformations is:Delete the item at index 0 ('a')Transpose the item at index 3 ('d') with its successorSubstitute the item at index 5 ('f') with the item from the second sequence at index 4 ('x')Insert at index 6 the item from the second sequence at index 5 ('y')Note the index for the transposition.  Even though, after the deletion, the'd'is at index 2, it’s at
index 3 in the original version of the sequence.  Likewise for the successive mutations.Key functionYou can also pass a callable as thekeykeyword argument todam_lev.get_changes.  Similar tolist.sort, this callable will be used to compare the elements of the sequences.  For example,diffs=dam_lev.get_changes('aBc','AbC',key=str.upper)print(diffs)# []
Package: damm
Damm algorithm decimal check digitNote that check digits are NOT used for verification of data transfers between
computers – use a CRC or a hash for that purpose! Check digits are used to
checkmanualentry of a digit into a computer system.A Damm check digit is a single check digit that can detect any
single-digit error as well as any adjacent-digit transpositions. The digit
computed in this module also detects some important phonetic errors (13<->30,
14<->40, … 19<–>90).This makes the Damm check digit better than other, more well-known check digits
like the Luhn code (used in credit cards) and the ISBN base-11 check digit. It
is equal in detection strength to a Verhoeff check digit, but much simpler to
compute.Furthermore, a hexadecimal Damm check digit was added. This single hexadecimal
check digit that detects every single-digit error as well as any adjacent-digit
transpositions. The digit computed in this module also detects some important
phonetic errors (13<->30, 14<->40, … 19<–>90). It also detects all
jump-transposition errors (abc -> cba), 93.5 % of all twin digit errors (aa ->
bb) and 93.5 % of all jump twin digit errors (aca -> bcb).There are four functions in this module:encode,encode16,checkandcheck16. The first two,encodeandencode16are used to calculate the
check digit for a number that you have. Pass in a string with the number you
want encoded and get a string with the check digit back. The other two,checkandcheck16are used to check that a number that was entered was entered
correctly. Pass in a string with a number including check digit and get backTrue/False.Damm algorithmThe Damm check digit is computed by starting with a check digit of zero and then
continually multiplying this check digit with the digits of a given number,
using the multiplication of a totally anti-symmetric quasigroup. The properties
and the selection of the group ensure the qualities of the check digit stated
above.For further reference on how the algorithm works seehttp://en.wikipedia.org/wiki/Damm_algorithmLicense informationCopyright (C) 2013 Johannes SpielmannThis module,damm, is licensed under the terms of the GNU General Public Licenses as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.For a full description of the license, please see the fileLICENSE