Saravanan666/pypi-org huggingface dataset:
Package: ahfhalotools
AHFHaloToolsAHFHaloTools is a Python 3 library for the analysis of data produced by AMIGA's Halo Finder (AHF).FeaturesFile parsing for.AHF_halos,.AHF_profiles,.AHF_mtree(_idx)File truncationAnalysis of radial profile dataAnalysis of integral properties (halo data)Proper tracking of halos through timeMerger detectionAnalysis of enclosed halos as indicator of host halo kinematicsDependenciesNumPymatplotlibAstroPyInstallationpip install ahfhalotoolsDocumentationView HTML documentationhereDocumentation is also available in docstrings within the
code, which can be viewed using the built-inhelpfunction:>>>fromahfhalotools.objectsimportCluster>>>help(Cluster)HelponclassClusterinmoduleahfhalotools.objects:...The majority of analysis is enabled by theahfhalotools.objects.Clusterobject.ExamplesExample scripts are available in/examples. These scripts are provided without data, as the data files are large and can't go on GitHub. To run them on a local machine, data must be downloaded and truncated, and the paths to the data in the scripts should be updated to reflect the location of the files.
Alternatively the scripts could be deployed to popia/castor and run there, after updating the directory paths in the code. Data should still be truncated before running, otherwise the scripts will execute very slowly.AHF documentationFor information on AMIGA's Halo Finder, including documentation and output file formats, you can visit their websitehere.Gallery
Package: ahi
Application Hacking InterfaceUsing the simple HTTPClientfromloggingimport*c=ahi.HTTPClient(cache_ttl=60,force_wait_interval=1,auto_adjust_for_rate_limiting=True,logging_level=DEBUG,proxy='http://127.0.0.1:8080',verify=True,allow_redirects=False,timeout=None)resp=c.get('http://example.com/')print(resp)Using the Selenium driver for Firefoxfromloggingimport*fromselenium.webdriver.common.keysimportKeysff=ahi.SeleniumFirefox(headless=True,force_wait_interval=timedelta(seconds=0),logging_level=DEBUG)ff.get('https://example.com/')ff.html.css('#LoginForm_Password').send_keys('P4$$w0rd')ff.html.css('#LoginForm_Password').send_keys(Keys.RETURN)ff.execute_script('''SetLocation('\x2Fdocs\x2FProMyPlanning.aspx?_Division_=549942',event, 0)''')ff.html.css('#Reports_Reports_Reports_MyPlanning').click()print(ff.html)Converting from a curl command linegirl--curlhttps://example.com/
Package: ahio
ahioahio is a communication library whose goal
is to abstract the interfacing with various I/O hardwares, so that changing
hardware becomes possible with minimum code modification. It's desired that
an application that already works with an I/O hardware will only need pin
remapping and possibly initial setup change to work with another hardware, not
entire code rewrite.It works with drivers, which are installed in theahio.driverspackage. Every
driver must implement the API described in theahio.abstract_driverpackage.
If you plan to use this library or develop a driver, read the documentation
there.InstallationSimplest way is to use pip:pip3 install ahioAlternatively you can checkout this repository and runpython3 setup.py installBasic usage# Import the package:importahio# You can see what drivers are available in this platform by callingprint(ahio.list_available_drivers())# Instantiate the desired driverwithahio.new_driver('Arduino')asarduino:# The driver can have a driver-specific setup function. Call it as/if needed.arduino.setup('/dev/tty.usbmodem1421')# Map the pins. From now on, when you use 1 in the API, it will have effects# on pin D3 in the Arduino. If you change hardware in the future, just change# the mapping.arduino.map_pin(1,arduino.Pins.D3)arduino.map_pin(2,arduino.Pins.D13)arduino.map_pin(3,arduino.Pins.A1)# Change a pin direction (Input or Output)arduino.set_pin_direction([1,2],ahio.Direction.Output)arduino.set_pin_direction(3,ahio.Direction.Input)# Set the output of a pinarduino.write([1,2],ahio.LogicValue.High)arduino.write(1,0.4,pwm=True)# Read the input of a pinprint(arduino.read(3))DocumentationDocumentation is hosted atGitHub
Package: ahk-bin
ahk-binA python package that bundled with workable AutoHotkey binary which could works for ‘ahk’ packageUsageimport ahkbin
from ahk import AHK

# If your Scripts directory of python be placed in PATH, it should works
# like a charm
ahk = AHK()

# Otherwise, you must specific the path which bundled in our package
ahk = AHK(executable_path=ahkbin.get_executable())LicenseThis package is licensed under GPLv2.The license of AutoHotkey binary are described in LICENSE_AHK.txtHistory0.0.5 (2021-02-08)Upgrade binary to AutoHotkeyU32 1.1.33.020.0.4 (2020-07-03)Upgrade binary to AutoHotkeyU32 1.1.330.0.3 (2020-05-30)Placed the AutoHotkey.exe into Scripts directory of python, so it’s easier to
create the AHK object when Scripts directory in PATH.Thanks @spyoungtechSpencer Phillip Young0.0.2 (2020-04-26)First release on PyPI.
Package: ahk-binary
Packages the AutoHotkey binary as an installable Python package. Intended for use with the [ahkpackage](https://pypi.org/project/ahk/).The license of AutoHotkey is included in theAutoHotkey_LICENSEfile.Installation:Since this is used as an accessory to theahkpackage, the recommended way to do this is to use the “extras” from ahk:$ pip install ahk[binary]Alternatively, it can be installed directly:$ pip install ahk-binary
Package: ahk-json
ahk-jsonThis is an extension package intended to be used with the Pythonahkpackage.It provides interfaces fromcocobelgica/AutoHotkey-JSONfor
working with JSON in AutoHotkey. The extensions in this package do not provide any additional methods,
but simply provide a convenient way to includeJxon.ahkand/orJSON.ahkinto other extensions.This package provides two extensions:JXONandJSON. It also registers a JSON message type (ahk_json.message.JsonResponseMessage)InstallationInstall this extension usingpippipinstallahk-jsonUsageTypically, you use this as a dependency when building your own extensions.In the following example, a simple extension (my_extension) is created. It implements an AHK functionMyTestFunction-- the registered to the extension using the Python functionmy_test_function.fromahk.extensionsimportExtensionfromahkimportAHKfromahk_jsonimportJXON# importing is necessary for ``extensions='auto'`` to work, even if this is not usedext_script='''\MyTestFunction(ByRef command) {arg := command[2]obj := Object("test", arg)res := Jxon_Dump(obj) ; this is available thanks to the extensionreturn FormatResponse("ahk_json.message.JsonResponseMessage", res)}'''my_extension=Extension(script_text=ext_script)@my_extension.registerdefmy_test_function(ahk:AHK,arg:str):returnahk.function_call('MyTestFunction',[arg])defmain():ahk=AHK(extensions='auto')# automatically use all imported/created extensions# or use the extensions explicitly:# ahk = AHK(extensions=[JXON, my_extension])# now ``.my_test_function`` is a method on the `ahk` instance:assertahk.my_test_function('foo')=={'test':'foo'}LicenseThis work is licensed under the MIT license.This package includes substantial portions of theoriginal AutoHotkey-JSON.
The code included from AutoHotkey-JSON is owned and copyrighted by its original author(s) and is used/redistributed
under the terms of theWTFPL.
Package: ahlfors
A sample project that exists as an aid to thePython Packaging User Guide’sTutorial on Packaging and Distributing
Projects.This projects does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.This is the README file for the project.The file should use UTF-8 encoding and be written using ReStructured Text. It
will be used to generate the project webpage on PyPI and will be displayed as
the project homepage on common code-hosting services, and should be written for
that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not
a good idea, although a simple “What’s New” section for the most recent version
may be appropriate.
Package: ahlive
ahlive - animate your data to life!Install the package:pip install ahliveFull Documentation:http://ahlive.readthedocs.io/ahlive is an open-source Python package that makes animating data simple, clean, and enjoyable.It can be as easy as:importahliveasahdf=ah.open_dataset("owid_co2_concentrations_over_the_long_term_scripps",names=["entity","year","co2"])ah.DataFrame(df,xs="year",ys="co2").render()Here are some features that make ahlive stand out!inline labels that follow the datadynamic axes limits that expand as necessaryremarks that pause the animation when a threshold is metmoving average reference linestraightforward usage; just set keywords!The code to generate this example can be foundhere.Need support? Join the community and ask a question at thediscussionspage. Don't be shy--it would make my day to see others use my package, seriously! (And I personally would love to )And if you like the project, don't forget to star the project!
Package: ahocode-test
This repo is a pure python implementation forpyahocorasick, inspired byabusix/ahocorapy.InstallationRequirementsPython 3.8 or laterpipinstallahocode-testDocumentationahocode is a fallback library for pyahocorasick, so theAutomatonclass and its methods
have same names and parameters.Below listed are the implemented classes and methods.ClassesAutomatonMethods for Automaton classadd_wordgetclearexistsfind_allitemsmake_automatoniterkeysvalues__getstate____setstate____len____contains__For documentation please refer to:https://pyahocorasick.readthedocs.io/en/latest
Package: ahocorasick
The Aho-Corasick automaton is a data structure that can quickly do a multiple-keyword search across text. It’s described in the classic paper ‘Efficient string matching: an aid to bibliographic search’:http://portal.acm.org/citation.cfm?id=360855&dl=ACM&coll=GUIDE. The majority of the code here is adapted from source code from the Fairly Fast Packet Filter (FFPF) project:http://ffpf.sourceforge.net/general/overview.php.
Package: ahocorasick-python
ahocorasick-pythonac自动机python的实现，可用于python2 python3等主流python发行版，对标准的ac自动机算法进行了完善 优化(主要是改进了结果的准确性)。注意：为了保证结果的准确性，请安装使用最新版(0.0.9)。1.如何安装pip 安装（推荐）pip install  ahocorasick-python源码安装git clone  https://github.com/xizhicode/ahocorasick-python.git
cd ahocorasick-python && python setup.py install2.如何使用注： 此处python3为例，python2也是类似的结果简单检索importahocorasick# 导入包tree=ahocorasick.AhoCorasick("test","book","oo","ok","k")# 构建ac自动机print(tree.search("test book"))# 检索输出结果：{'test','k','oo','book','ok'}检索并返回结果字符所在的位置（可以用于字符替换等场景）importahocorasick# 导入包tree=ahocorasick.AhoCorasick("test","book","oo","ok","k")# 构建ac自动机print(tree.search("test book",True))# 检索输出结果：{('k',(8,9)),('book',(5,9)),('oo',(6,8)),('ok',(7,9)),('test',(0,4))}3.参考资料ac自动机算法详解ac自动机4.联系我QQ:   943489924邮箱：zhoukunpeng504@163.com5. 注意如果在windows平台上遇到了编码问题，删除所有的中文即可。
Package: ahogeotagger
ahogeotaggerIf you have thousands of passages of text and you want to search them for hundreds or thousands of search strings, the process can become very cumbersome very soon. This is where ahocorasick search becomes very relevant and blazingly fast. You can read more about the algorithmhere.This code combines thevery efficient implementation of ahocorasickin python with a pre-bundled list of cities, states and countries to tag locations in text.RequirementsPython 3.6 or higherpyahocorasick 1.4.0 or higherInstallationUsing PIP via PyPipip install ahogeotaggerUsageRight now the usage is pretty simple. You import and init the tagger with the number of cities you want to search your text for. The cities are in order of population (Tokyo, New york, Mexico City etc.).The data for these cities has been prepopulated from the free version of simplemaps database which you can findhere.from ahogeotagger import tagger
tagger.init(num_cities = 10000)Optionally, if you dont want to use the built-in database of cities, you can provide your own list of cities. The list needs to be a list of tuples with each tuple's values in the following order:(id,city,state,country,iso2,iso3,population,lat,lng)The types foridandpopulationareint,latandlngare floats and all the rest are strings.tagger.init(num_cities = 500, cities = [a,b,c])where a,b,c are tuples described above.To search whether text contains locations, supply any plain text to the search function like this:results = tagger.search('New york and London are are competing for tech talent')
print(results)This produces the following list of tuples as a result[(0, 7, 'New York', 'New York', 'United States', 'US', 'USA', 19354922, 40.6943, -73.9249), 
 (13, 18, 'London', 'London, City of', 'United Kingdom', 'GB', 'GBR', 8567000, 51.5, -0.1167)]Each tuple always contains values in this orderstart_index(for the match in the source string),end_index,city,state,country,iso2,iso3,population,latitude,longitude
Package: ahoi
ahoi (A Horrible Optimisation Instrument)This module contains a few python functions to run Brute-force scans for rectangular cut optimization.InstallationTo install ahoi runpython3-mpipinstall[--user]ahoiUse--userif not in a virtual environment or conda environment.It's recommended to use python3, but currently python2 is also supported.ExampleThe basic functionality uses amasks_listwhich is a list of lists or a list
of 2D numpy arrays that represent pass flags for selection criteria.For example, the following represents pass flags for the criteria>0,>0.1,>0.2, ...,>0.9for 5 random uniform variables in 10000 events:importnumpyasnpnp.random.seed(42)x=np.random.rand(10000,5)masks_list=[[x[:,i]>vforvinnp.linspace(0,0.9,10)]foriinrange(x.shape[1])]To count all matching combinations for all criteria on each variable runimport ahoi
counts = ahoi.scan(masks_list)The entry[0, 1, 2, 3, 4]ofcountswill contain the number of matching
events where the first column ofxis>0, the second one>0.1, the third
one>0.2etc.>>>counts[0,1,2,3,4]3032>>>np.count_nonzero((x[:,0]>0)&(x[:,1]>0.1)&(x[:,2]>0.2)&(x[:,3]>0.3)&(x[:,4]>0.4))3032You can also pass weightsweights=np.random.normal(loc=1,size=len(x))counts,sumw,sumw2=ahoi.scan(masks_list,weights=weights)The arrayssumwandsumw2will contain the sum of weights and sum of squares
of weights for matching combinations. The sum of squares of weights can be used
to estimate the statistical uncertainty on the sum of weights ($\sigma = \sqrt{\sum w_i^2}$).>>>sumw[0,1,2,3,4]3094.2191136427627>>>np.dot(...(x[:,0]>0)&(x[:,1]>0.1)&(x[:,2]>0.2)&(x[:,3]>0.3)&(x[:,4]>0.4),...weights...)3094.219113642755>>>np.sqrt(sumw2[0,1,2,3,4])78.5528532026876>>>np.sqrt(...np.dot(...(x[:,0]>0)&(x[:,1]>0.1)&(x[:,2]>0.2)&(x[:,3]>0.3)&(x[:,4]>0.4),...weights**2...)...)78.55285320268761Tutorial/NotebookHave a look at theexamplesfor a tutorial that explains how to use
this for solving a classification problem.Tests/CoverageRun the tests and coverage report inside the project directory withpython3-mpytest--cov=ahoi--doctest-modules
coveragehtml
Package: ahoy-dtu-webthing
ahoy_dtu_webthingA webthing adapter to provide theAhyoDTUinterface via thewebthing API.Example# webthing has been started on host 192.168.0.23

curl http://192.168.0.23:7122/0/properties 

{
   "name": "Terrasse",
   "serial": "114180123418",
   "p_dc": 23
   ....
}To install this software you can usePIPpackage manager as shown belowsudo pip install ahoy_dtu_webthingAfter this installation you can use the Webthing http endpoint in your Python code or from the command line withsudo dtu --command listen --port 7122 --base_uri http://10.1.11.35/Here the webthing API is bound to the local port 7122. Additionally, the base uri of the AhyoDTU REST api must be set.As an alternative to thelistcommand, you can also use theregistercommand to register and start the webthing service as a systemd entity.
This way, the webthing service is started automatically at boot time. Starting the server manually with thelistencommand is no longer necessary.sudo dtu --command register --port 7122 --base_uri http://10.1.11.35/
Package: ahoyhoy
OverviewA friendly greeting for your services!ahoyhoyis intended as a universal service client for python/django applications.GoalsProvide a standard service discovery and resolution interface for python.Include all required information in each request before sending it to downstream servicesDocumentationFor full documentation, including installation, please seehttp://ahoyhoy.readthedocs.io/en/latest/About the nameFromWikipedia:Ahoyis a signal word used to call to a ship or boat, stemming from the Middle English cry, ‘Hoy!’.Alexander Graham Bell originally suggestedahoybe adopted as the standard greeting when answering a telephone, before ‘hello’ (suggested by Thomas Edison) became common.(Formerly a Ukrainian Unicorn.)
Package: ahp-calculator
Installationpip install ahp_calculatorUsagefrom ahp_calculator import ahp_calculator 

AC=ahp_calculator()
AC.open_calculator()INTRODUCTIONThe Analytic Hierarchy Process (AHP) is a method for organizing and evaluating complicated decisions, using Maths and Psychology. In 1970s, Thomas L. Saaty developed AHP which is a theory of measurement. AHP has been widely used, particularly in large-scale situations with several criteria and when the evaluation of alternatives is mostly subjective. It has quantifying capability which distinguishes the AHP from other decision making techniques.AHP is one of the extensively used Multi Criteria Decision Making (MCDM) tool for processing multiple important objectives and weighting the criteria. The AHP allows to assign a priority among various alternatives and integrating multidimensional measures into a single scale of priorities.METHODThe pair-wise comparison is used to compare the importance of criteria. It can be carried out with nine-point scale value which includes values 9, 8, 7, 6...., 1/7, 1/8, 1/9, which indicates 9 as extreme preference, 7 as very strong preference, 5 as strong preference and so on down to 1 which represents no preference. Thus, the pair-wise comparison aids to simplify the criteria by evaluating the independent contribution of each criterion with each other. The square matrix is organized for pairwise comparisons of various criteria. The principal eigenvalue and their corresponding eigenvector was developed among the relative importance within the criteria from the comparison matrix. The weights for each element can be generated from the normalized eigenvector. The subjective judgment from AHP were checked via consistency index. The consistency index (CI) is calculated as:CI = ( λmax - n ) / ( n - 1 )Where CI = Consitency Indexλmax = maximum eigenvector of the matrixn = order of the matrixAfter comparing CI with random index, Consistency Ratio (CR) can be derived from their ratio. The consistency ratio should be ≤ 0.1 (Saaty, 1990). The pairwise comparison is assumed to be inconsistent if the CR exceeds the threshold, the process has to be reviewed in such case.
Package: ahp-graph
ahp_graph - Python Attributed Hierarchical Port GraphAHP Graphs -https://arxiv.org/pdf/1802.06492.pdfRequires Python3.9 at a minimum. There is a "noTyping" branch which works with older versions of Python (like 3.6)Ubuntu apt packages:aptinstallgraphvizlibgraphviz-devRHEL/CentOS yum packages:yuminstallgraphvizgraphviz-develPython3 packages:python3-mpipinstallpygraphvizorjsonUseful TipsAssembly names are automatically prefixed to the expanded devices names when the graph is flattenedBesides graph construction, the main features that ahp_graph provides are several outputsSSTGraph.build()will immediately turn your graph into SST components and begin a simulationSSTGraph.write_json()will output the graph along with parameters in JSON formatDeviceGraph.write_dot()will output the graph in DOT format and optionally draw SVGs with themAll output generated by ahp_graph goes into a folder called 'output'This is for theSSTGraph.write_json()andDeviceGraph.write_dot()functionsSST global parameters are set by adding things to the DeviceGraph attr fieldSST component parameters are set by adding things to the Device attr fieldYou can still do normal SST Python things (examples below):sst.setProgramOption()sst.setStatisticLoadLevel()sst.setStatisticOutput()SSTGraph.build()returns a dictionary of devices with their name as the keyYou can use this to enable statistics for devices after they are createdIf you plan to build the graph with ahp_graph partitioning and run with MPI, remember to include the--parallel-load=SINGLEflag to sst--parallel-loadby default will work with multiple unique filesahp_graph can generate the graph for each rank using a single file, so it needs the value 'SINGLE'By default sst grabs all command line parametersYou can pass parameters to the python script by putting--before your script parameters
Package: ahps_alerts
ahps_alertsRetrieve NWS AHPS alertsFree software: MIT licenseDocumentation:https://ahps-alerts.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2017-09-18)First release on PyPI.
Package: ahqapiclient
# DEPRECATED! Please use the information at https://[yourname].abusehq.net/api/v1/docs/ and use an http client of your liking for accessing the API directly# AbuseHQ API Client## About**ahqapiclient** is a library which reflects the AbuseHQ API on client side.## Usageimport Client from ahqapiclient### Setupendpoint = {"auth_method": "JWT","auth_options": {"token": "<YOUR_API_KEY>"},"url": "https://<yourcompany>.abusehq.net/api/v1"}api_client = Client(endpoint)### Usage#### Get a casecase = api_client.case.get_case('case_id')#### Perform a transitionapi_client.case.trigger_transition('case_id', 'transition_id')
Package: ahri-mime
Ahri - ahri_mimeGithubContact meahriknow@gmail.comHow to useinstallpipinstallahri_mimeimportfromahri_mimeimportget_ext,get_exts,get_type,get_typesThe ahri_mime hasattr:attributetypeexplainMIMEfileincludeEXT_TO_TYPEandTYPE_TO_EXTEXT_TO_TYPEdictkey isExtension, value isTypeTYPE_TO_EXTdictkey isType, value isExtensionget_extfunctiongetExtensionby typeget_extsfunctionget allExtensions by typeget_typefunctiongetTypeby extget_typesfunctiongetTypes by extExamplefromahri_mimeimportget_ext,get_exts,get_type,get_typesdefhandle():print(get_ext('x-world/x-3dmf'))print(get_exts('x-world/x-3dmf',dot=False))print(get_type('docx',dot=False))print(get_types('.docx'))if__name__=="__main__":handle().3dm['3dm','3dmf','qd3','qd3d']application/vnd.openxmlformats-officedocument.wordprocessingml.document['application/vnd.openxmlformats-officedocument.wordprocessingml.document']
Package: ahstu-sign-up
安科填报自动化脚本填报过程自动化，适用于安徽科技学院某填报系统，摆脱被班委催填报的尴尬，以造福劳苦大众允许自定义填报信息支持多人填报（需要相应配置文件）支持Windows, Linux与人工填写几经无差别使用方法Windows用户提供一键脚本, 具体使用方法参见help.txt文件Linux用户需自建python虚拟环境（提供requirements.txt）使用须知以下情况均不负责因使用本脚本而被查处并记过因使用本脚本而造成填写内容不为实际信息（有bug在issue提出）因使用本脚本而造成本人实质性的损失本脚本制作本意仅为方便日常生活，减少重复工作的目的。个人应在保证自身身体健康的情况下使用，积极配合学校防疫工作，时刻检查自身身体情况，若察觉到异常情况，请关停该脚本，认真填写填报信息并上报。请低调使用