Saravanan666/pypi-org huggingface dataset:
Package: eote-dice
Analyze or roll Star Wars Edge of the Empire (EotE) role-playing game dice pools.InstallationNote: Linux and Mac OSX users should usepip3rather thanpip.You can install, upgrade, and uninstalleote-dicewith these commands:$pipinstalleote-dice$pipinstall--upgradeeote-dice$pipuninstalleote-diceUsageInput the dice pool using the first letter of the color of the die (except black Setback die which
usek).  Use--rollto perform a roll oranalyzeto statistically analyze.$eote_dice--poolyygbrppkanalyze--success-cutoff=1--advantage-cutoff=2$eote_dice--poolyygbrppk--rollReleases1.2.0 - 2019-12-15Add Python 3.8 support.Include license file.1.1.0 - 2017-07-09Support Python 3.6 and 3.7.1.0.0 - 2016-03-05Added four dimensional distribution to analyze dependant probabilities (e.g.
What is the probability of at least 1 success and 2 advantage?). Contributions by@drhagen.0.3.2 - 2015-12-31Fix bright black ANSI color difficult to read.0.3.1 - 2015-12-31For rolls, use bright ANSI colors.0.3.0 - 2015-12-31Added rolling capability.0.2.0 - 2015-12-31Dice statistics are now calculated using discrete distribution.  Contribution by@drhagen.0.1.3 - 2015-12-25Fix pip install dependency issues.0.1.2 - 2015-12-23Improve feedback when user enters an incorrect dice color.0.1.1 - 2015-12-23Fixed setup.py.0.1.0 - 2015-12-23First release.
Package: eo-tilematcher
Tools to quickly find the Sentinel2, Landsat5, and Landsat8 tiles that a given region
of interest.Basically, the library returns a geodataframe with:geometry: is the requested geometry to be matched against satellite tilesmatch_polygon: is the intersection/contains WKT geometry (string) that matches each satellite tilematch: partial/total (str). total indicates acontainsconditition.TILE(Sentinel2) orPATH#ROW(Landsat): the satellite tile (path,row) matched inmatchcondition (Sentinel/Landsat convention)UsageBasic library usageFor this case, import the library:from eo_tilematcher import intersectsand run:geo_match = intersects(spacecraft,ROI)WhereROI=geopandas geodataframespacecraft ={sentinel2,landsat8,landsat5}Check theeo-tilematcher-101tutorial notebook to see some plots.Command-line usagePrint the tiles intersecting a Region Of Interest (ROI) for a given satellite:python -m eo_tilematcher /path/to/ROI --spacecraft spacecraftor:eo_tilematcher /path/to/ROI --spacecraft spacecraftWhere:
- /path/to/ROI is the path to any kind of file thatfionacould open (shp,gpkg,geojson,…)
- spacecraft ={sentinel2,landsat8,landsat5} (default sentinel2 no input required).2. Find and save to a file the tiles intersecting a Region Of Interest (ROI) for a given satellite
With dump:python -m eo_tilematcher /path/to/ROI --spacecraft spacecraft  --output my_ouput.gpkgor:eo_tilematcher /path/to/ROI --spacecraft spacecraft  --output my_ouput.gpkgInstallationYou can install them from PyPI by simply running:pip install eo_tilematcherInstallation from sourcesTo install the package, from the project root run:pip install .  # Regular installation
pip install -e .  # Install in development mode
Package: eotransform-xarray
eotransform-xarrayWhat can I use eotransform-xarray for?The eotransform-xarray package provides common transformations on raster data represented asxarraydata structures, following the Transformer protocol ofeotransform.
This makes them easy to mix and match, and you can quickly chain processing pipelines, using othereotransformprotocols.
Additionally, processing pipelines constructed from these Transformers, can be automatically applied to thestreamed_processfunction fromeotransform, to benefit from I/O hiding.Getting StartedInstallationpipinstalleotransform-xarrayExample: streamed processing pipelineIn the following example swath data is resampled, masked and written out as a GeoTIFF stack.resample=ResampleWithGauss(swath_geometry,raster_geometry,sigma=2e5,neighbours=4,lookup_radius=1e6)mask=MaskWhere(lambdax:x>2,np.nan)squeeze=Squeeze()withThreadPoolExecutor(max_workers=3)asex:pipeline=Compose([resample,mask,squeeze])streamed_process(input_src,pipeline,SinkToGeoTiff(dst_dir,lambdai,da:f"out_{i}.tif"),ex)snippet source|anchorNote, that this example useseotransform's streamed_processfunction to hide the I/O operations, using the compute resources more effectively.Support & DocumentationDocumentationGitHub:https://github.com/TUW-GEO/eotransform-xarrayDependencies:eotransform-xarray requires Python 3.8 and has these dependencies:eotransform>=1.8xarrayrioxarraynumpyaffinemore_itertoolssnippet source|anchorCitationIf you find this repository useful, please consider giving it a star or a citation:@software{eotransform_xarray_2023_8002854,author={Raml, Bernhard},title={eotransform-xarray},month=jun,year=2023,publisher={Zenodo},version={2.4.1},doi={10.5281/zenodo.8002854},url={https://doi.org/10.5281/zenodo.8002854}}
Package: eow
This program provides just enough glue to use the excellentCodeMirroras an editor for local files.Do the following:pip install eow

eow --keymap=vim --password=mypassword file-to-edit.txtInstead of specifying a file on the command line, you may also go tohttp://localhost:9113/e/file-to-edit.txt.For what it’s worth, the author uses this to edit LaTeX files on a Linux system
from within a Windows virtual machine with the help of Windows-only speech
recognition software… :)
Package: eox-audit-model
InstallationInstall eox-audit-model:pipinstalleox-audit-modelAdd “eox_audit_model” to your INSTALLED_APPS:INSTALLED_APPS=[...'eox_audit_model',]Run Migrate:pythonmanage.pymigrateeox_audit_modelOpen edX compatibility notesOpen edX ReleaseVersionJuniper>=0.2, < 0.4Koa>=0.4, <= 0.7Lilac>=0.4, <= 0.7Maple>=0.7, <1.0Nutmeg>=1.0Olive>=2.0Palm>=3.0Quince>=3.0UsageAudit any execution of a method or function. This will create a database register with the following information:Status. If the process was successful or not.Action. The string given to identify the process.Time stamp. The execute date.Method name. Method or function name.Captured log. logs generated in the execution.Traceback log. If there was an exception, this will contain the traceback.Site. Current site.Performer. The user who started the method, this depend on the request.userInput. The values used to execute the method.Output. The value returned by the method.Ip. Current ip.Example:fromeox_audit_model.modelsimportAuditModeldefany_method(parameter1,parameter2,parameter3):"""Do something"""return'Success'defaudit_process():"""Execute audit process"""action="This is a simple action"parameters={"args":(2,6),"kwargs":{"parameter3":9},}expected_value=AuditModel.execute_action(action,any_method,parameters)...DecoratorThere is a simple decorator, which can perform the same process.Example:fromeox_audit_model.decoratorsimportaudit_method@audit_method(action="This is a simple action")defany_method(parameter1,parameter2,parameter3):"""Do something"""return'Success'defaudit_process():"""Execute audit process"""expected_value=any_method(3,6,9)...ContributingAdd your contribution policy. (If required)
Package: epa
Python wrapper for the multiple APIs available through the EPA’s
website.Documentation for the APIs can be found here:
[http://www.epa.gov/enviro/facts/ef_restful.html](http://www.epa.gov/enviro/facts/ef_restful.html)APIs### RADInfo>>> from epa.radinfo import RADInfo
>>> r = RADInfo()>>> # An empty method returns a dict of available columns.
... r.facility_type()>>> # A method call without a value returns info about that column.
... r.facility_type('cit_ref_code')>>> # Find information on a facility in a certain city.
... r.facility('city_name', 'Berkeley')
{'data': {'about': "Berkeley's Radiation Facility"}}>>> # Find all the radiation facilities in Texas.
... r.facility('state_code', 'TX')
{'all': {'seven': 'Texas facilities'}}>>> # Integer values are converted to strings automatically.
... r.regulation('part_id', 61)>>> r.regulation('title_id', '40')>>> # Search for the CIT_REF_CODE of a RAD NPL facility.
... r.regulation('cit_ref_code', '40CFR300')>>> data = r.regulatory_program('sec_cit_ref_flag', 'N')
>>> data['Count']
100>>> new_data = r.regulatory_program('sec_cit_ref_code', 'N', count=200)
>>> new_data['Count']
190>>> data = r.regulatory_program('cit_ref_code', '40CFR300', start=50)
>>> data['Count']
8>>> # Find geographic information.
... r.geo('geometric_type_code', '001')### GICS>>> from epa.gics import GICS
>>> g = GICS()>>> # List construction projects that are 91% complete.
... g.construction('complete_percent', 91)>>> # Find all the construction projects at a specific facility.
... data = g.construction('facility_number', 190226001)
>>> data['Count']
8>>> # Search for a specific grant's milestones.
... g.milestone('grant_number', 190709130)>>> # Find all ADMIN COMPLETE milestones.
... g.milestone('milestone_type', 'ADMIN COMPLETE')>>> # Search for milestones on a specific DD-MON-YY date.
... g.milestone('milestone_date', '16-MAR-01')>>> # Find descriptions for a status code.
... g.status('status_code', 'AF')>>> # Find grants on a specific date.
... g.grant('award_accept_date', '12-MAR-01')>>> # Find grants for a specific city.
... g.grant('projecty_city_name', 'San Francisco')>>> # Search the GICS API's grants for a specific state.
... g.grant('project_state_code', 'TX', count=500)>>> # Find an applicant in a specific zipcode.
... g.applicant('zip_code', 94105)### PCS>>> from epa.pcs import PCS
>>> p = PCS()>>> # Search for facilities in a city.
... p.facility('location_city', 'San Francisco')>>> # Find a facility in a particular zipcode.
... p.facility('location_zip_code', 76108)>>> # Find a sludge facility in a specific state.
... p.sludge('handler_state', 'NY')>>> p.pipe_schedule('discharge_num', 333)>>> p.pipe_schedule('npdes', 'GMG290024')>>> p.dmr_measurement('discharge_num', '001')>>> # Find the inspections that took place on a specific date.
... p.inspection('insp_date', '16-MAR-01')>>> p.enforcement_action('ea_code', '09')CopyrightCopyright (c) 2011 Code for America Laboratories.See LICENSE for details.
Package: epages-client
ePages ClientPython 3 client for ePages REST API.Free software: MIT licenseDocumentation:https://epages-client.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.0 (2020-02-11)Dropped Python 2 support0.1.0 (2018-01-05)First release on PyPI.
Package: epages-provisioning
ePages provisioningPython library for calling ePages provisioning servicesFree software: MIT licenseDocumentation:https://epages-provisioning.readthedocs.io.FeaturesePages SimpleProvisioningService for easy shop creation, modifying and deletionCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.[ ~ Dependencies scanned by PyUp.io ~ ]History1.0.2 (2021-01-04)remove last remrants of travis from docsfix readme in built packageretest deploy process1.0.1 (2021-01-04)drop travis and switch to github actions for pypi publishfix pypi and docs build1.0.0 (2021-01-04)drop support for python 2.7update zeep to 4.0.00.5.0 (2018-10-02)added two new methods get_shop_attribute and set_shop_attribute to shop classfixed some documentation typosfixed some code commentsupdated dev requirements via pyup0.4.0 (2018-09-10)update zeep to 3.1.0added coveralls to testsuiteShopAddress attributes to shop classupdate to ShopConfigService12, getAllInfo is now fixed0.3.0 (2017-12-22)added “shop” class which is a pythonic wrapper over the shopconfigservice0.2.1 (2017-12-19)fixed AddtionalAttributes and SecondaryDomainsrestructuring0.2.0 (2017-12-08)First “working” release0.1.2 through 0.1.7 (2017-12-08)Travis deployment tests0.1.0 (2017-12-05)First release on PyPI.
Package: epages-rest-python
SeeePages APIfor detailed documentation.InstallationUsingpip:pip install epages-rest-pythonUsageimport epages

api_url = 'https://your.domain.com/rs/shops/yourShopName'
token = 'yOuRaPiKeYhErE'
client = epages.RESTClient(api_url,
                           token) # optional for public resources

# Get the shop information
shop = client.get('')
# or
shop = client.get('/')
# or
shop = client.get(api_url)
print(shop)

# Create a new product
payload = {
    'productNumber': '1337'
}
new_product = client.post('/products', json=payload)
print(new_product)Works withePages Now v2 (beyond) shops, too:import epages
client = epages.BYDClient('https://yourshop.beyondshop.cloud/api',
                          'client-id-of-your-app',
                          'client-secret-of-your-app')

shop = client.get('/shop')

print(shop['name'])For more examples see theepages-rest-python-examplesrepository.TestingExecuting the tests requires adeveloper shop.cp run_tests.sh.template run_tests.sh

# Edit run_tests.sh: enter your ePages API URL and access token

make test
Package: epanetmsx
epanet-msx-pythonThe python wrapper forepanet-msx.InstallationPython version: 3.6+pip install epanetmsxUsageMost of the functions are used in the same fashion as they would be in the C API, however it is not necessary to
check the return values for an error code anymore. If an error occurs, an exception will be thrown stating the error code.
The only major difference in calling functions using the python wrapper for epanet-msx is the way that values are returned.
If a function in the C API took in a pointer as a parameter that was intended to be used as an output, it now will be returned
by the function.
For example:// In C
int MSXgetindex(int type, char *id, int *index);
# In Python
index = msx.getindex(type, id)If there are multiple pointers given that will be used for output. Python handles it like this:// In C
int MSXgetspecies(int index, int *type, char *units, double *aTol, double *rTol);
# In Python
type, units, aTol, rTol = msx.getspecies(index)Currently, there is only one function that uses a pointer variable for both input and output and it is the "t" variable in MSXstep.
Example usage:t, tleft = msx.step(t)Check out thisexamplefor more details.DevelopmentPrerequisitesInstall CmakeInstall Swigpip install scikit-buildEnsure the epanet-msx subproject is initialized by running git submodule update --init.
Then run and running the following commands (only run clean if you can run bash scripts).
The following method uses scikit-build to invoke cmake for compiling and linking the shared libaries, and builds a python wheel../scripts/clean.sh
python setup.py sdist bdist_wheel
pip install dist/*.whlThere is also a script called build that will run the three commands from above. (build.sh should be called from the root)./scripts/build.shTestsThere is a tests directory with a file that can be run using pytest for unit tests. All of the tests that are currently available
are very basic, and mainly only test functions that are not utilized in either of the examples. Both of the examples are working,
and therefore all of the critical functions that those use are working. It is more important that the example functions are running
properly than the tests passing since the examples use more critical functions.
To run the tests:pytest tests/test_msx.py
Package: epann
IntroductionA crucial difference between artificial neural networks (ANNs) and biological neural networks (BNNs) is that BNNs can acquire new skills across variant tasks on their own. Motivated by BNNs, we try to implement the "Learning By Interaction" principle in the meta-learning framework. We aim to unify supervised learning, reinforcement learning, and unsupervised learning in a model-based / plasticity-based manner. The learning no longer relies on human-designed target function and optimization but through the black-box mechanism of the neural networks and plasticity rules. We build this evolving plasticity repo to facilitate the research on this topic.Requirementpython >= 3.7.4parl == 1.4.1numpy >= 1.8.1metagym >= 0.1.0Run Meta-Training in Random Maze-2D environmentspythonrun_train.pyconfig_maze_trainRun Meta-Testing in Random Maze-2D environmentspythonrun_test.pyconfig_maze_testIf you are to use parallelization mode, start xparl master on your remote server by using:xparlstart--cpu_num$cpu_num--port$port_idand change the "server" configuration to "$IP_ADDRESS:$port_id".
Also be sure that "$cpu_num" surpass the "actor_number" in the configuration file
Package: epa-regions
epa-regions-pythonEPA regionswithGeoPandas/regionmask.Codepython-mepa_regions-r50m--states-only--saveInstallationconda activate ...
conda install -c conda-forge geopandas regionmask pooch pyogrio
pip install epa-regionsUsageimportepa_regions# GeoPandas GeoDataFrameepa=epa_regions.get(resolution="50m")# Convert to regionmask Regions for use with gridded dataepa=epa_regions.to_regionmask(epa)Point dataCodeimportgeopandasasgpdimportmatplotlib.pyplotaspltimportnumpyasnpimportepa_regionsrng=np.random.default_rng(seed=123)epa=epa_regions.get(resolution="50m")# CONUSlonmin,lonmax=-125,-66latmin,latmax=24,50n=250lon=rng.uniform(lonmin,lonmax,n)lat=rng.uniform(latmin,latmax,n)points=gpd.GeoDataFrame(geometry=gpd.points_from_xy(lon,lat,crs="EPSG:4326"))fig,ax=plt.subplots(constrained_layout=True,figsize=(4,2.5))epa.plot(column="number",ax=ax,alpha=0.6)points.sjoin(epa,predicate="within").plot(column="number",ax=ax,ec="0.3",lw=1)ax.set(xlim=(lonmin,lonmax),ylim=(latmin,latmax))ax.axis("off")fig.savefig("points.png",dpi="figure",bbox_inches="tight")Gridded dataCodeimportcartopy.crsasccrsimportcartopy.featureascfeatureimportmatplotlib.pyplotaspltimportnumpyasnpimportpandasaspdimportxarrayasxrimportepa_regionsepa=epa_regions.to_regionmask(epa_regions.get(resolution="50m"))# CONUSlonmin,lonmax=-125,-66latmin,latmax=24,50ds=(xr.tutorial.open_dataset("air_temperature").sel(lon=slice(lonmin+360,lonmax+360),lat=slice(latmax,latmin)))mask=epa.mask(ds.isel(time=0))proj=ccrs.LambertConformal(central_longitude=-100)tran=ccrs.PlateCarree()fig=plt.figure(figsize=(6,6),constrained_layout=True)ax=fig.add_subplot(3,1,(1,2),projection=proj)mask.plot.pcolormesh(levels=np.arange(mask.min()-0.5,mask.max()+1),ax=ax,transform=ccrs.PlateCarree(),cmap="tab10",cbar_kwargs=dict(orientation="horizontal",fraction=0.075,pad=0.05,ticks=np.arange(mask.min(),mask.max()+1),format="R{x:.0f}",label="EPA Region",),)ax.add_feature(cfeature.STATES,linewidth=0.7,edgecolor="0.3")ax.coastlines()ax.set_extent([lonmin,lonmax-2,latmin,latmax],crs=tran)ax.set_title("")ax=fig.add_subplot(3,1,3)(dt,)=np.unique(ds.time.diff("time"))window=pd.Timedelta("30D")(ds["air"].groupby(mask).mean().rolling(time=int(window/dt),center=True).mean().plot(hue="mask",ax=ax,add_legend=False,))ax.set_xlabel("")ax.text(0.01,0.97,f"{window.total_seconds()/86400:g}-day rolling mean",ha="left",va="top",transform=ax.transAxes,fontsize=11,)fig.savefig("gridded.png",dpi="figure",bbox_inches="tight")
Package: eparkhontos
eparkhontosConversion between calendar years (mostly BCE but also CE),
astronomical dates, and the convention used for most ancient Greek
dates, a span of two Julian years (for example, “431/430”).The name comes from the ancient Greek formula for refering to years asep' arkhontos... (ἐπ᾽ ἄρχοντος ...) “when so-and-so was arkhon.”Installationpip install eparkhontosUsageParsing Arkhon Yearseparkhontoscan parse strings like “431/430”, “431/30”, “431/30
BCE”, “431-430 b.c.”, all of which will return an“astronomical
year”—an
integer which, for years BCE is negative and offset by 1 because 1 BCE
is numbered as 0. The astronomical year is assigned to the year in the
ancient Greek year begins, so "431/430" becomes -430 (meaning 431
BCE):>>> import eparkhontos as epi
>>> epi.parse_arkhon("431/430")
-430
>>> epi.parse_arkhon("431/430 B.C.")
-430
>>> epi.parse_arkhon("431/430 BCE")
-430
>>> epi.parse_arkhon("431-30")
-430If the string contains any form of “CE” or “AD” the year will be treated accordingly:>>> epi.parse_arkhon("100/101 CE")
100Formatting Astronomical YearsYou can get a formatted arkhon year from an astronomical year,
including BCE/CE appended if you want, or prepended if you want:>>> epi.to_arkhon(-430)
'431/430'
>>> epi.to_arkhon(-430, with_era=True)
'431/430 BCE'
>>> epi.to_arkhon(-430, with_era=True, prefix_era=True)
'BCE 431/430'
>>> epi.to_arkhon(-430, True)
'431/430 BCE'
>>> epi.to_arkhon(-430, True, True)
'BCE 431/430'
>>> epi.to_arkhon(430, True)
'430/431  CE'Note that “CE” is padded with leading space to align with “BCE.”Getting an Astronomical YearSo you don’t have to remember how to correctly offset for an
astronomical year, you can convert anintorstr. For instance, if
you want “431” to be interpreted as “431 BCE”:>>> epi.to_astronomical(431)
-430
>>> epi.to_astronomical("431")
-430If it is, in fact, a year CE:>>> epi.to_astronomical("431", is_bce=False)
431
>>> epi.to_astronomical("431", False)
431ContributingBug reports and pull requests are welcome on GitHub athttps://github.com/seanredmond/eparkhontos
Package: eparsecis
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                                   ░A Pythonic Approach to Parsing EPCIS DataThe EParseCIS python package utilizes the lxml python package along with
the EPCPyYes EPCIS python package to enable the quick and easy parsing of
EPCIS data from it’s native format into python EPCPyYes class instances that
can be quickly manipulated, inspected and serialized to other formats with
minimal effort.Note: Line-by-line code-coverage files can be found in the build artifacts.Python lxml Parser for EPCIS EventsFree software: GNU General Public License v3Documentation:https://serial-lab.gitlab.io/EParseCISFeaturesFast-forward lxml parsing of EPCIS xml-formatted dataEasy handling of EPCIS events as EPCPyYes python class instances as events are parsed.Simplifies the building of EPCIS-enabled applications.
Package: epath
epathThis package provides easy and dynamic way to import parent files in Python.Sample folder structure can be seen below.--main_folder

--app.py

  --folder_1

    --sample.txt

  --folder_2

    --target.pyHere, it is desired to read the sample.txt file from the target.py file. Then it will be used by calling the say_hello and say_goodBye functions in the app.py file.app.pydef say_hello():
  print("Hello")

def say_goodBye():
  print("GoodBye")sample.txtThis is a sample.txttarget.pyfrom epath import Path

pt = Path()
txt_path = pt.get("/../folder_1/sample.txt")
with open(txt_path) as f:
    lines = f.readlines()

print(lines)
>>>['This is a sample.txt ']

#----------------------------------
app = pt.importer("/../app")
app.say_hello()
>>>Hello

app.say_goodBye()
>>>GoodBye
Package: epb
Energy performance of buildingsThis library provides helpers for energy performance of buildings computation.InstallingWith PIPpipinstallepbWith PoetrypoetryaddepbUsagefromepb.utilsimportRegulator,energy_class,total_consumptioneclass=energy_class(Regulator.BRUSSELS,100)# eclass == "C+"tconsum=total_consumption(100,250)# tconsum == 25_000