Saravanan666/pypi-org huggingface dataset:
Package: pydyimport
PyDyImportDynamically import python file to aviod mess when you are using a different directory structure from python suggested.UsageJust construct aDynamicImportinstance and callDynamicImport.requirefrompydyimportimportDynamicImportrequire=DynamicImport(__file__).requiremod=require("path/to/file.py")If you only need some of fields in the module, useDynamicImport.require_only, whichalwaysreturn a tuple.frompydyimportimportDynamicImportrequire_only=DynamicImport(__file__).require_onlyfoo,=require_only("path/to/file.py",'foo')# still return tuple even if only one field describedSpam1,Spam2=require_only("path/to/file.py",'Spam1','Spam2')You can inject environment variables to the modules you will import by the use ofenv_injectoroption ofDynamicImport.frompydyimportimportDynamicImportdefmeaningless_env_injector(path:str,code:bytes):return{'__meaning__':'no',}importer=DynamicImport(__file__,env_injector=meaningless_env_injector)importer.require("path/to/file.py")You can inject require* functions byRequireEnvInjector,frompydyimportimportDynamicImportfrompydyimport.injectorimportRequireEnvInjectorrequire=DynamicImport(__file__,env_injector=RequireEnvInjector(next_injector=None))require('path/to/module.py')or just setinject_requireTrue.frompydyimportimportDynamicImportrequire=DynamicImport(__file__,inject_require=True)require('path/to/module.py')If your source contains# inject_require, the require* functions will automatically inject require* functions to the module.#!/usr/bin/env python# inject_requirerequire('path/to/module.py')Spam1,foo=require_only('path/to/module2.py','Spam1','foo')LicenseGNU GENERAL PUBLIC LICENSE, version 3 or later.PyDyImport - dynamically importing and avoid mess in python
    Copyright (C) 2020 thisLight

    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program.  If not, see <https://www.gnu.org/licenses/>.
Package: pydymenu
pydymenu: A Pythonic interface forfzfandrofiA single package to serve all your dynamic menu-ing needs with a simple Pythonic
interface.InstallationDependenciessudoaptinstallfzfrofi-yFromPyPipip3install--userpydymenuUsagefrompydymenuimportfzf,rofipeople=["Joe","Sam","Daniel","Bret","Jordan","Eric","Lex"]# fzftalker=fzf(people,prompt="Pick a podcaster: ",preview="figlet{}")iftalker:returntalker[0]# rofigui_select=rofi(people,prompt="Pick a podcaster: ",multi=True)ifgui_select:returngui_select[0]pydymenu.MENU(items: Iterable[str], **options) -> Optional[List[str]]Optionsprompt: str: The prompt text shown at the selection(default:>)multi: bool: Whether or not to allow multiple selections.(default:multi=False)case_sensitive: bool: Whether or not to use case sensitive search(default:case_sensitive=False)preview: str(fzf only): Command that will be run on each entry and displayed as it's preview when
using the fuzzy finder.Project StatusWorking support for the most commonfzfandrofiuse cases. Currently
expanding functionality for those two programs then going to move onto addingdmenusupport.I'm trying to keep this package as a pretty simple drop-in replacement foriterfzf. Biggest design changes are:fzfautomatically sorts results based on match quality.Selections always return lists of strings. Whenmulti=Falsereturns a list
of length 1.Roadmap:Support fordmenusystemsSource of TruthThis project is available onGitHubandGitLab. Each push tomasterautomatically goes to both so choose whichever platform you prefer. All releases
are uploaded toPyPiBig thanks tofzfandRofidevelopers for making the utilities this tool relies upon.
Package: pydynaa
PyDynAAThis package is a place holder for an upcoming public release of PyDynAA.Until the public release the latest version of this package is available from our private PYPI indexpypi.netsquid.org.
To install it using pip you should specify this index using the--extra-index-urloption, for example:pip3install--user--extra-index-urlhttps://<username>:<password>@pypi.netsquid.orgpydynaawhere<username>and<password>need to be substituted with your credentials.
Package: pyDynamicRoutingUpdater
┻━┻ ︵ヽ(`Д´)ﾉ︵ ┻━┻Dynamic Routing-table updater (DRU)Example of reference.json{"tableName":"direct","adapter":["enp1s0f0","enp1s0f1"]}tableNamewill be the table name the program will use to direct routes and rules againstadapterwill be the interfaces you will split out from the main routing tableWhen you or the service starts up DRU,
it will prepare the required data.After the data has been loaded, it will be ready to start. All this occurs within the init call.When DRU gets the start call, it will do the following:Remove old DRU tables (based on the Table name passed)Find all occupied table idsFilter out occupiedDefine table id and name for all network adapters addedWrite the newly filtered and appended routing tableAfter DRU has started, and processed the routing table, it will start up DRUHook.This is a sub component of DRU, which is intended to watch the network interfaces assigned to DRU and perform routing changes on them.If you want to test DRU out, you can do the followingfromDynamicRoutingUpdaterimportDynamicRoutingUpdaterservice=DynamicRoutingUpdater()service.dryrun()NOTE!ThisWILLdo modifications to your routing table!This will also change and modify your current routes, andWILL NOT BE RESTORED!Usually a reboot is enough to get it recreated, as the code does not include persistanceHow to installTo install and start DRUClone the projectModify reference.json./install.shMake sure that you run the script with sudo or as root, as the script needs access.Or you can do the following:curl-sSL-oinstall.shhttps://raw.githubusercontent.com/bskjon/DynamicRoutingUpdater/master/install.sh&&sudobashinstall.shThis will request you to define table name and select interface thrould selection.A copy of your routing table will exist as:/etc/iproute2/rt_tables.bak
Package: pydynamics
PyDynamicsClient and Query Builder for On-Premise Microsoft Dynamics CRM.Getting an Auth TokenThe first task would be to fetch an authentication token. To do this pass your username and password to the token.get() function along with the URL of your CRM instance.frompydynamicsimporttokentok=token.get('https://crm.domain.com/','DOMAIN\\username','password')The returned token can then be used in subsequent client calls.Create a client instancePass the token generated above to the Client constructor along with the API URL.frompydynamics.clientimportClientclient=Client(tok,'https://crm.domain.com/INSTANCE/api/data/v8.1/')Building QueriesThe package includes a query builder.Select a single itemThe below example returns a single contact record, selected on its GUID and selects 3 specific fields to return. the select() part is optional, a default field set will be returned if it is omitted.frompydynamics.querybuilderimportQueryBuilderq=QueryBuilder('contacts').guid('1bf1c4cf-1ed1-e311-941c-0050568a018c').\select(['firstname','lastname','emailaddress1'])result=client.select(q)Select based on filtersThe below example returns the first 2, based on the limit(), contacts that contain the string "flowplex" within the emailaddress1 field and implements ordering and return field selection.frompydynamics.querybuilderimportQueryBuilderq=QueryBuilder('contacts').\filter('emailaddress1','contains','flowplex','str').\select(['firstname','lastname','emailaddress1']).\order(['lastname'],'asc').limit(0,2)result=client.select(q)Create a recordThe below creates a contact entity with the data provided to the query builder. The GUID of the new item will be returned if successful.frompydynamics.querybuilderimportQueryBuilderq=QueryBuilder('contacts').data({'firstname':'Dan','lastname':'Test','emailaddress1':'dan@fdsdsds.com'})guid=client.create(q)Update a recordThe below updates the firstname field on the specific contact record.frompydynamics.querybuilderimportQueryBuilderq=QueryBuilder('contacts').guid('1bf1c4cf-1ed1-e311-941c-0050568a018c').\data({'firstname':'Daniel'})client.update(q)
Package: pydynamo-w
Pydynamo-wPydynamo-w is a module to define, run and analyse system dynamics. I first present how to use the practical session we designed to play with the module, and then brief comments and references in english at the end.Comments in englishIt was originally created to run the World3 model [2], written in DYNAMO language [1]. Included in the module are functions to convert DYNAMO code to pydynamo syntax. All scenarios ofLimits to Growth, updated with 2003 version, are shown inLimitsToGrowth03. For a quick tuto of how to use World3 in pydynamo, seeWorld3. For a quick tuto on how to use pydynamo, seeBTmodel.Documentation about the World models is inhttps://abaucher.gitlabpages.inria.fr/pydynamo/.Installationclone this repository and got to folderpython -m pip install -r requirements.txtyou can import pydynamoNoteThis is a beta version and all documentation and commands may not be complete or updatedUsageDefine the system equations in a function or file with pydynamo syntaxGet a System object from this function or fileRun, change parameters, re-run, plotAuthorAchille BAUCHER for my internship at the LIG-lab. I used some functions from pyworld3 [3], and nice explanations by it's author Charles Vanwynsberghe.References[1] How DYNAMO  works:https://archive.org/details/dynamousersmanua0000pugh/Some additional explanations about DYNAMO language are indynamo_doc[2] Book describing the world3 model:https://archive.org/details/dynamicsofgrowth0000unse/[3] Pyworld3:https://github.com/cvanwynsberghe/pyworld3
Package: pydyno
PyDyNoPython Dynamic analysis of Biochemical Networks (PyDyNo) is an open source python library for the analysis of
signal execution in network-driven biological processes. PyDyNo supports the analysis ofPySBandSBMLmodels.InstallationFrom PyPI>pipinstallpydynoInstalling the latest unreleased version>pipinstallgit+git:https://github.com/LoLab-VU/pydyno.gitInstalling from source folderDownload and extract pydynoNavigate into the pydyno directoryInstall (Python is necessary for this step):>pythonsetup.pyinstallHow to use PyDyNoImport librariesimportpydynoimportnumpyasnpfromos.pathimportdirname,joinfromIPython.displayimportImagefrompydyno.examples.double_enzymatic.mm_two_paths_modelimportmodelfrompydyno.visualize_simulationsimportVisualizeSimulationsfrompydyno.discretizationimportPysbDomPathfrompydyno.visualize_discretizationimportvisualization_pathfrompysb.simulatorimportScipyOdeSimulator%matplotlibinlineLoad the calibrated parameters and simulate the model with 100 different parameter sets# import calibrated parametersmodule_path=dirname(pydyno.__file__)pars_path=join(module_path,"examples","double_enzymatic","calibrated_pars.npy")pars=np.load(pars_path)# define time for the simulation and simulate modeltspan=np.linspace(0,100,101)sim=ScipyOdeSimulator(model,tspan=tspan).run(param_values=pars[:100])Visualize the dynamics of the modelvt=VisualizeSimulations(model,sim,clusters=None)vt.plot_cluster_dynamics(components=[5])# This saves the figure in the local folder with the filename comp0_cluster0.pngObtain the dominant paths for each of the simulations¶dp=PysbDomPath(model,sim)signatures,paths=dp.get_path_signatures('s5','production',depth=2,dom_om=1)signatures.sequences.head()Obtain distance matrix and optimal number of clusters (execution modes)signatures.dissimilarity_matrix()signatures.silhouette_score_agglomerative_range(4)# Select the number of cluster with highest silhouette scoresignatures.agglomerative_clustering(2)# Plot signaturessignatures.plot_sequences()# File is saved to the local directory with the filename modal.pngpaths{2: [OrderedDict([('s5', [['s3'], ['s4']])]),
  OrderedDict([('s3', [['s0', 's1']]), ('s4', [['s0', 's2']])])],
 1: [OrderedDict([('s5', [['s4']])]), OrderedDict([('s4', [['s0', 's2']])])],
 0: [OrderedDict([('s5', [['s3']])]), OrderedDict([('s3', [['s0', 's1']])])]}Visualize execution modesvisualization_path(model,path=paths[0],target_node='s5',type_analysis='production',filename='path_0.png')# Visualization is saved to local directory wit the filename path0.pngvisualization_path(model,path=paths[1],target_node='s5',type_analysis='production',filename='path_1.png')# Visualization is saved to local directory wit the filename path1.pngvisualization_path(model,path=paths[2],target_node='s5',type_analysis='production',filename='path_2.png')# Visualization is saved to local directory wit the filename path2.png
Package: pydy-viz
pydy-vizVisualization of multibody systems generated with PyDy.InstallationThis package relies on dependencies included in the SciPy stack (i.e. NumPy and
matplotlib). These packages are not necessarily easy to install from source, so
it is best to follow the instructions available on theSciPy installation
page.One example of installing the setuptools, NumPy, and matplotlib dependencies
for Debian based Linux systems is to install from the apt package manager:$ apt-get install python-setuptools python-numpy python-matplotlibOnce the dependencies are installed, then download the source and install with:$ python setup.py installThis will automatically install the latest version of the final dependency
SymPy if needed.TestsThe Python tests require nose so get them with your package manager:$ apt-get python-nose python-coverageor pip:$ pip install nose coverageThe tests can be run from the root directory with:$ nosetestsAnd to see more detail with coverage, run:$ nosetests -v --with-coverage --cover-package=pydy_vizThese are alternative ways to run the Python tests:$ bin/test
$ python setup.py nosetestsFor the Javascript tests the Jasmine and blanket.js libraries are used.  Both
of these libraries are included in pydy-viz with the source. To run the
Javascript tests, go to the javascript library directory:$ cd pydy_viz/static/jsThen run a simple HTTP Server with Python (the server is required due to some
cross browser issues with blanket.js):$ python -m SimpleHTTPServerNow visithttp://localhost:8000/SpecRunner.htmlin a webgl compliant browser.DocumentationRequires:Sphinxnumpydocpip install sphinx numpydocTo build the HTML docs:$ sphinx-build -b html docs/src docs/buildView:$ firefox docs/build/index.htmlRelease Notes0.1.0Initial release.
Package: pyE2EE
pyE2EE 1.0.0End To End Encryption in Python.Installpip install pyE2EEFeaturesCross platform (i think)RSA and AES EncryptionExamples providedUsage/ExamplesimportpyE2EEServer Sidedefclient_loop(server,cli):pass# do stuffserver=pyE2EE.Server(port,client_loop)# client_loop will be called giving args server-obj and clientserver.TotalCons# gives number of total connectionsserver.clients# is a list of all [client, AES-key-of-the-cli]server.send(client,msg)# sends msgserver.recv(client)# recvs msgserver.sendall(msg)# send all connected clientsserver.close(client)# close a connectionClient Sideclient=pyE2EE.Client(server_ip,port)client.send(msg)# send msg to serverclient.recv()# recv msg from serverclient.close()# close connection with serverLicenseMITAuthors@Merwin
Package: pye3d
pye3d Detectorpye3dimplements a published mathematical 3D eye model capturing ocular kinematics
and optics (seeSwirski and Dodgson, 2013, as well asDierkes, Kassner, and Bulling, 2019.InstallationWe recommend installing the pre-packaged binary wheels from PyPI:pip install pye3dFor more information see thedocumentation.
Package: pye3sm
PyE3SMPyE3SM is a Python library to assist E3SM model simulation.
Currently, it only supports the land and river components.AcknowledgementThis research was supported as part of the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research at Pacific Northwest National Laboratory. The study was also partly supported by U.S. Department of Energy Office of Science Biological and Environmental Research through the Earth and Environmental System Modeling program as part of the Energy Exascale Earth System Model (E3SM) project.Installpip install pye3smContactPlease contact Chang Liao (chang.liao@pnnl.gov) if you have any questions.
Package: pye57
pye57Python wrapper ofLibE57Formatto read and write .e57 point cloud filesExample usageimportnumpyasnpimportpye57e57=pye57.E57("e57_file.e57")# read scan at index 0data=e57.read_scan(0)# 'data' is a dictionary with the point types as keysassertisinstance(data["cartesianX"],np.ndarray)assertisinstance(data["cartesianY"],np.ndarray)assertisinstance(data["cartesianZ"],np.ndarray)# other attributes can be read using:data=e57.read_scan(0,intensity=True,colors=True,row_column=True)assertisinstance(data["cartesianX"],np.ndarray)assertisinstance(data["cartesianY"],np.ndarray)assertisinstance(data["cartesianZ"],np.ndarray)assertisinstance(data["intensity"],np.ndarray)assertisinstance(data["colorRed"],np.ndarray)assertisinstance(data["colorGreen"],np.ndarray)assertisinstance(data["colorBlue"],np.ndarray)assertisinstance(data["rowIndex"],np.ndarray)assertisinstance(data["columnIndex"],np.ndarray)# the 'read_scan' method filters points using the 'cartesianInvalidState' field# if you want to get everything as raw, untransformed data, use:data_raw=e57.read_scan_raw(0)# writing is also possible, but only using raw data for nowe57_write=pye57.E57("e57_file_write.e57",mode='w')e57_write.write_scan_raw(data_raw)# you can specify a header to copy information frome57_write.write_scan_raw(data_raw,scan_header=e57.get_header(0))# the ScanHeader object wraps most of the scan information:header=e57.get_header(0)print(header.point_count)print(header.rotation_matrix)print(header.translation)# all the header information can be printed using:forlineinheader.pretty_print():print(line)# the scan position can be accessed with:position_scan_0=e57.scan_position(0)# the binding is very close to the E57Foundation API# you can modify the nodes easily from pythonimf=e57.image_fileroot=imf.root()data3d=root["data3D"]scan_0=data3d[0]translation_x=scan_0["pose"]["translation"]["x"]InstallationIf you're on linux or Windows, a wheel should be available.python -m pip install pye57Building from sourceCloning the repository and required submodulesClone a new repository along with the required submodulesgit clone https://github.com/davidcaron/pye57.git --recursiveIf the repository has already been previously cloned, but without the --recursive flagcd pye57 # go to the cloned repository
git submodule init # this will initialise the submodules in the repository
git submodule update # this will update the submodules in the repositoryDependencies on LinuxInstall libxerces-c-dev first.sudo apt install libxerces-c-devDependencies on WindowsTo get xerces-c, you can either build from source or if you're using conda:conda install -y xerces-cRunpip installfrom the repo sourcecd pye57
python -m pip install .UninstallingUse pip againpython -m pip uninstall pye57
Package: pyeach
pyeachThis is a package meant for use within Cone Health's Enterprise Analytics teams. The goal of this package is to provide reusable python functionality for enterprise projects.Developers and MaintainersTyler UrsuyLuke BrantleyInstallation OptionsInstallation can only be done fromTestPyPicurrently, but will soon be available in a full release at PyPi.TestPyPi:pip install -i https://test.pypi.org/simple/ pyeachBuild StepsTestPyPiUpdate pyproject.toml with new version number and execute all commands from the project base directory. Build the .tar and .whl files by executingpython -m build. Test the package before uploading it to TestPyPi by installing the built pyeach-x.x.x.tar.gz file from the dist folder in a virtual environment and performing the appropriate tests. Install the new test version in a virtual environment withpip install PATHwhere PATH is the absolute path to the tar.gz file. After confirming the package works as intended, executepython -m twine upload --repository testpypi dist/pyeach-x.x.x.tar.gz dist/pyeach-x.x.x-py3-none-any.whlto upload the new version to TestPyPi. A prompt for a username and password will appear. Username is__token__and your password is your unique TestPyPi API token. A TestPyPi account with MFA is required to generate a token. Register for an accounthere.
Package: pyEager
# pyEagerA simple package to read in eager results.## Available functionscompile_endogenous_table(): Creates a compiled table of endogenous DNA statistics from endorspy including all the information in the list of JSON file paths provided. Wrapsparse_endorspy_jsonon all provided JSON paths.parse_endorspy_json(): Read in the information in a single endorspy JSON file.compile_damage_table(): Creates a compiled table of select DamageProfiler results from the list of JSON files provided. Ths resulting dataframe includes the number of reads analysed by DamageProfiler as well as the damage in the first 2 bp of either end of DNA molecules for each sample.collect_damageprofiler_results(): Collects the results from multiple damageprofiler JSON output files into a large dictionary containing all the results for each sample. This function wrapsparse_damageprofiler_jsonacross all provided JSON files.parse_damageprofiler_json(): Read in the information in a single damageprofiler JSON output file.compile_snp_coverage_table(): Creates a compiled table of SNP coverage results from the list of JSON files provided. Wrapsparse_snp_coverage_jsonacross all provided JSON filesparse_snp_coverage_json(): Read in the information in a single SNP coverage JSON file.parse_sexdeterrmine_json(): Reads in the Sexdeterrmine output JSON into a dataframe.parse_nuclear_contamination_json(): Reads in the nuclear contamination output JSON into a dataframe.parse_eager_tsv(): Reads in the eager input TSV into a dataframe, with additional columns specifying what merging steps took place.infer_merged_bam_names(): Infer the names of eager output files based on the merging steps that took place.parse_general_stats_table(): Reads in the general stats table output of MultiQC into a dataframe.## Installation<!– TODO Add installation instructions –>## Usage<!– TODO Add usage examples –>## License[MIT](LICENSE.txt)
Package: pyeagle
PyEAGLE - Read / Write Cadsoft EAGLE FilesScott TorborgPyEAGLE is an interchange API to read and write Cadsoft EAGLE XML (v6 and
later) schematic, library, and PCB layout files.Documentation ishosted at Read The Docs.InstallationInstall with pip:$ pip install pyeagleLicensePyEAGLE is licensed under an MIT license. Please see the LICENSE file for more
information.Example Usageschematic=pyeagle.open('hello.sch')lib=pyeagle.open('SparkFun-Sensors.lbr')forpartinlib:printpart
Package: pyeal
pyeal新的 Python 打包编译工具包名称是python seal的意思目录快速开始功能介绍版权说明快速开始注意下方的python是你的Python, 正常情况下可以直接通过python调用, 而Maya的python一般是"C:\ProgramFiles\Autodesk\<Maya版本>\bin\mayapy.exe"安装python -m pip install pyeal如果你使用mayapy进行安装请注意以下几点:请确认pip给你安装的位置是否在python的搜索路径下,如果不存在可以在“pip install”后加“-t 目标路径” 来解决这个问题.请确认pyeal.exe可以被命令行查找到, 它一般在pip给你安装的库的位置的../../Scripts下.如果无法被找到请将其所在的目录添加到环境变量中.如果出现第一次安装pyeal不会出现以上情况, 而第二次出现或者反过来.请按情况处理即可,这只是python2、python3、maya、windows其中一个出现了未知的变化而已导致的更改而已.建议打开管理员进行安装否则会安装到“C:\Users\PC\AppData\Roaming\Python\Python27\site-packages”下,这将导致库文件和普通的python2混合在一起.如果出现了不在上述情况中的错误请提issue初始化mkdir test_pyeal

cd test_pyeal

python -m pyeal init编译python -m pyeal build功能介绍目前大部分操作都通过命令行调用, 依赖于pyeal.json配置功能.配置{"type":"package","name":"your_name","exec_script":""}配置的各项参数type[str]: 你要封装的类型目前仅支持package, maya-plugin.name[str]: 你要封装的名称, 一般作为名称空间或者名称前缀.imp_name[str]: 打包完成后的导入名称, 未填则为name的值.exec_script[str]: 启动脚本, 一般是导入某一个模块, 然后执行启动函数.annotation[str]: 注释字符串, 在构建类型为maya-plugin或其他可以添加注释的的编译类型的时候被使用.outer_lib[list(str)]: 额外的库目录.文件约定icon.ico logo文件, 在构建类型为maya-plugin或其他需要图标的编译类型的时候被使用的文件.pyeal.json 构建配置文件.index.py 在编写复杂的启动脚本时, 替代exec_script配置项的文件.src/ 源代码目录.lib/ 依赖库目录.build/ 输出目录.版权说明该项目签署了Apache-2.0 授权许可, 详情请参阅 LICENSE