Saravanan666/pypi-org huggingface dataset:
Package: metio
# MetioMetio is a simple API to extract TopoWX and Gridmet from the web to a geographic extent and time period.  The data can then be easily saved to a GeoTiff file and used in GIS analysis.I built this module to be used in Landsat image analysis, so it has functionality that allows one to extract gridded met
data to the same geometry as any Landsat 5, 7, ot 8 image.The easiest way to get this package is by usingpip` pip install Metio `
Package: metis
Wrapper for the METIS library for partitioning graphs (and other stuff).This library is unrelated to PyMetis, except that they wrap the same library.
PyMetis is a Boost Python extension, while this library is pure python and will
run under PyPy and interpreters with similarly compatible ctypes libraries.NetworkXis recommended for representing graphs for use with this wrapper,
but it isn’t required. Simple adjacency lists are supported as well.Please see the fulldocumentationfor examples or the GitHubrepositoryfor bug reports
Package: metis-client
Metis API clientThis library allows for programmatic interactions with theMetis infrastructure.Installationpip install metis_clientUsageThere are two client flavors:asyncronousasyncioclient
and simplifiedsynchronousclient.Asynchronous clientAn asynchronous client isMetisAPIAsync. Example of usage:frommetis_clientimportMetisAPIAsync,MetisTokenAuthasyncdefmain():asyncwithMetisAPIAsync(API_URL,auth=MetisTokenAuth("VERY_SECRET_TOKEN"))asclient:print(awaitclient.v0.auth.whoami())data=awaitclient.v0.datasources.create(content)results=awaitclient.v0.calculations.create_get_results(data["id"])print(resuls)Seeexamplesdirectory for more examples.Synchronous clientA synchronous client isMetisAPI. Example of usage:frommetis_clientimportMetisAPI,MetisTokenAuthclient=MetisAPI(API_URL,auth=MetisTokenAuth("VERY_SECRET_TOKEN"),timeout=5)data=client.v0.datasources.create(content)results=client.v0.calculations.create_get_results(data["id"],timeout=False)print(results)NB in development one can replace aVERY_SECRET_TOKENstring with the development user email, e.g.admin@test.com(refer tousers_emailsBFF table).ContributingPlease give a minute to thecontribution guide. Note, that ourchangelogis maintained fully automatically viaGitHub actions.LicenseAuthor Sergey Korolev, Tilde Materials InformaticsCopyright 2023 BASF SEBSD 3-Clause
Package: metispi
Metis is an application to make your home a safer place to live by watching and
recording any movements. It also (optionally) supports notifications via
Telegram.RequirementsRaspberry Pi 3HC-SR501 PIR Motion SensorRaspberry Pi Camera Board v22 LEDsQuickstartInstall Metis:$pipinstallmetispiRun Metis:$[sudo]python-mmetis--conf=path/to/config.yamlNoteBased on Linux you use, you may or may not need root privileges to run Metis.ConfigurationIt’s mandatory to pass a config file because some of the options are required.
Here’s an example:pins:motion_sensor:4# pin number HC-SR501 attached toled_motion_on:17# pin number LED "motion detected" attached toled_motion_off:20# pin number LED "no motions" attached totelegram:token:XXXXXXXXX:YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYrecipient:000000001One more thing, a wholetelegramnode is optional and may be omitted if you
are not interested in notifications via Telegram. If you do, you need to create
a Telegram bot and pass its token astelegram.tokenoption.
Package: metis-utils
Metis UtilsThis is a collection of utility functions to help speed you through the OSEMN (obtain - scrub - explore - model - interpret) lifecycle of data science project development.Metisis a data science education company with campuses in New York, Chicago, San Francisco, and Seattle, and corporate training services throughout the U.S. Themetis-utilspackage is a collection of some our favorite scripts and functions that we use to teach data science in our bootcamps, and to help students to rapidly put together prototypes for their data science projects. We hope that the included modules will boost your productivity, and that reading through the source code will deepen your understanding of data science best practices!
Package: metlib
metlibPython package to performs meteorological calculations.Version0.0.1.3RequirementsnumpyxarrayTip: If you install the GOES package using pip, you don't need to worry about installing these packages because they will be installed automatically.UsageYou can find jupyter notebook examples in thisfile.The functions of this package and their descriptions can be found in thisfile.InstallationYou can installmetlibon Python 2 or 3 on Linux, Windows or other using the following commands.Using pip(recommended):pip install metlibCheck if package was installed with:pip show metlibIf you already have the package installed, update it to the latest version with:pip install --upgrade metlibUsing clone:clone https://github.com/joaohenry23/metlib.git
cd metlib
python setup.py installUsing python:Downloadmetlib-master.zipfrom github and following the next commands:unzip metlib-master.zip
cd metlib-master
python setup.py installChange logAll notable changes to this project will be documented in thisfile.SupportIf you have any questions, do not hesitate to write to:joaohenry23@gmail.comYou can write to me in spanish, portuguese or english.
Package: metlinkpid-http
Themetlinkpid-httpscript
provides an HTTP endpoint for a Metlink LED passenger information display:$ metlinkpid-http --serial=/dev/ttyUSB0
Serving on http://127.0.0.1:8080

$ curl 'http://127.0.0.1:8080?12:34+FUNKYTOWN~5|Limited+Express|_Stops+all+stations+except+East+Richard'
{"error":null,"message":"12:34 FUNKYTOWN~5|Limited Express|_Stops all stations except East Richard"}InstallationInstall fromPyPIusingpip:pip install metlinkpid-httpBasic usageFind the deviceDetermine the device to which the display is connected.
On Linux, this can be achieved by disconnecting the display from the computer & reconnecting,
then inspecting the contents ofdmesgoutput for USB attachment messages:[    3.010816] usb 1-1.4: FTDI USB Serial Device converter now attached to ttyUSB0The above output indicates that the display is reachable through/dev/ttyUSB0.Start the HTTP serverRun the script passing that device location as the--serialoption:$ metlinkpid-http --serial=/dev/tty/USB0The script accepts the following options:--serial=PORTThe PID serial device name,
such as/dev/ttyUSB0on Linux orCOM1on Windows.
If not specified, defaults to the value of environment variableMETLINKPID_SERIAL;
if no such variable, defaults to/dev/ttyUSB0.--http=HOST:PORTThe hostname/IP address and port to listen on, separated by a colon (:).
If not specified, defaults to the value of environment variableMETLINKPID_HTTP;
if no such variable, defaults to127.0.0.1:8080.-hor--helpDisplays usage information similar to above,
and provides a link to this documentation.If the PID successfully connects, the URL is confirmed:Serving on http://127.0.0.1:8080Display a messageNext, browse to the specified URL in a browser,
adding anappropriately encoded query stringto the end:http://127.0.0.1:8080?MY+MESSAGEYou should see a plain-text JSON result similar to this:{"error":null,"message":"MY MESSAGE"}The same result can be obtained on the terminal usingcurl:$ curl 'http://127.0.0.1:8080?MY+MESSAGE'
{"error":null,"message":"MY MESSAGE"}You could do the same thing in Python like this, using the“requests” library:>>> import requests
>>> requests.get('http://127.0.0.1:8080?MY+MESSAGE').json()
{'error': None, 'message': 'MY MESSAGE'}By exposing the display via HTTP in this way,
you can operate it using almost any programming language or toolkit.See the“metlinkpid” module documentationfor full details about message formatting.The HTTP server also periodically pings the display in the background,
preventing message display timeout.SupportBug reports, feature requests, and questions are welcome via the issue tracker.Issue tracker:https://github.com/Lx/python-metlinkpid-http/issuesContributePull requests for both code and documentation improvements
are gratefully received and considered.GitHub repository:https://github.com/Lx/python-metlinkpid-httpLicenseThis project is licensed under theMIT License.
Package: metlo
Metlo API SecuritySecure Your API.InstallationCurrently Metlo's Python Agent supports 2 servers:DjangoFlaskIt can be installed frompypiby running :pipinstallmetloConfigurationDjangoOnce installed, Metlo's middleware can be added by modifying middlewares list (in the projectssettings.py) like so:MIDDLEWARE=[...,"metlo.django.MetloDjango",]and configuring aMETLO_CONFIGattribute in the projectssettings.pylike this :METLO_CONFIG={"API_KEY":"<YOUR_METLO_API_KEY>","METLO_HOST":"<YOUR_METLO_COLLECTOR_URL>"}METLO_CONFIGcan take an optional key-value pair representing the max number of workers for communicating with Metlo.FlaskOnce installed, Metlo middleware can be added simply like:fromflaskimportFlask...frommetlo.flaskimportMetloFlaskapp=Flask(__name__)MetloFlask(app,"<YOUR_METLO_COLLECTOR_URL>","<YOUR_METLO_API_KEY>")The Flask Middleware takes the flask app, Metlo collector url, and the Metlo API Key as parameters. As an optional
parameter, a named value can be passed for max number of workers for communicating with Metlo.MetloFlask(app,"<YOUR_METLO_COLLECTOR_URL>","<YOUR_METLO_API_KEY>",workers="<WORKER-COUNT>")
Package: metlog-cef
metlog-cef is a plugin extension forMetlog
<http://github.com/mozilla-services/metlog-py>.  metlog-cef
provides an extension to log send CEF messages to a logstash server.More information about how Mozilla Services is using Metlog (including what is
being used for a router and what endpoints are in use / planning to be used)
can be found on the relevantspec page.
Package: metlog-psutils
metlog-psutils is a plugin extension forMetlog
<http://github.com/mozilla-services/metlog-py>.  metlog-psutils
provides details about network connections, memory usage, cpu usage
and even some thread details.This plugin works best on Linux.  Running the plugin under OSX will
skip some functionality and will require root privileges.More information about how Mozilla Services is using Metlog (including what is
being used for a router and what endpoints are in use / planning to be used)
can be found on the relevantspec page.
Package: metlog-py
metlog-py is a Python client for the “Metlog” system of application logging and
metrics gathering developed by theMozilla Servicesteam. The Metlog system is meant to make
life easier for application developers with regard to generating and sending
logging and analytics data to various destinations. It achieves this goal (we
hope!) by separating the concerns of message generation from those of message
delivery and analysis. Front end application code no longer has to deal
directly with separate back end client libraries, or even know what back end
data storage and processing tools are in use. Instead, a message is labeled
with a type (and possibly other metadata) and handed to the Metlog system,
which then handles ultimate message delivery.The Metlog system consists of three pieces:generatorThis is the application that will be generating the data that is to be sent
into the system.routerThis is the initial recipient of the messages that the generator will be
sending. Typically, a metlog router deserializes the messages it receives,
examines them, and decides based on the message metadata or contents which
endpoint(s) to which the message should be delivered.endpointsDifferent types of messages lend themselves to different types of
presentation, processing, and analytics. The router has the ability to
deliver messages of various types to destinations that are appropriate for
handling those message types. For example, simple log messages might be
output to a log file, while counter timer info is delivered to astatsdserver, and Python exception information
is sent to aSentryserver.The metlog-py library you are currently reading about is a client library meant
to be used by Python-based generator applications. It provides a means for
those apps to insert messages into the system for delivery to the router and,
ultimately, one or more endpoints.More information about how Mozilla Services is using Metlog (including what is
being used for a router and what endpoints are in use / planning to be used)
can be found on the relevantspec page.
Package: metmap
metmapDNA methyltransferase binding motif plasmid assemblerOverall purpose:To identify the motifs of multiple DNA methyltransferases (DNA MTase) simultaneously.Quick startThis script requires python 3.6 or newer.Install using "pip install metmap"This will put a script named "run_metmap.py" in your pythons bin folder.Linux: You should just be able to type "run_metmap.py" from terminalWindows: The script will be placed in your python folders "Scripts" subfolder and you can run it with "python path\to\python\Scripts\run_metmap.py" from command lineMac: Who knows..probably works like linux?TestYou can download the tests/test_data.txt and runrun_metmap.py test_data.txtThis should generate a cas1.fa and cas1.gb file.Overview:You have an organism with multiple identified DNA MTases and you wish to know their individual motifs.You use NGS to obtain motifs of all methylated DNA sites.Some of those motifs will contain ambiguous bases and some will notYou submit those motifs to this programThis program then stitches these motifs together in random orderMotifs may contain ambiguous bases per the IUPAC nucleotide codeWe can't synthesize lots of ambiguous bases, so we "de-ambigulate" them before putting them into the final construct.De-ambigulation happens according to 1 of 2 rules:Rule 1:Pick L random variants of the motif. E.g. Motif ATGNNTTA have a total of 16 possible actual sequences. If L<16 then the program will random pick L variants (without duplicates). If L>16 then each possible variant will be picked at least L/16 times and some will be picked 1 more than that.Rule 2:Make K copies of each completely "de-ambigulated" variant: E.g. the sequence "SATC" will then be treated as 2 sequences: "GATC" and "CTAC" that will each appear in K copies.We put M N's between each motifAnd the program will output P versions of these cassettesYou then clone this cassette into a plasmid with 1 DNA MTase in each plasmid.You then transform this library into an organism that doesnt natively methylate DNA.Grow, Harvest, Sequence plasmids.?Profit!Motif file formatThe motifs should be stored in a standard text fileOne motif per line, then a comma then a 1 or a 2 to indicate whether either rule 1 or 2 should be used for this motif
Example:ATGCATGCATGC, 1STGCAGTCATCGTTK, 1ATCNNNNAAA, 2CGTAGCANNNATCGATGC, 2IUPAC nucleotide code:codenucsRA or GYC or TSG or CWA or TKG or TMA or CBC or G or TDA or G or THA or C or TVA or C or GNany base
Package: metnet
MetNet and MetNet-2PyTorch Implementation of Google Research's MetNet for short term weather forecasting (https://arxiv.org/abs/2003.12140), inspired fromhttps://github.com/tcapelle/metnet_pytorch/tree/master/metnet_pytorchMetNet-2 (https://arxiv.org/pdf/2111.07470.pdf) is a further extension of MetNet that takes in a larger context image to predict up to 12 hours ahead, and is also implemented in PyTorch here.InstallationClone the repository, then runpipinstall-rrequirements.txt
pipinstall-e.Alternatively, you can also install a usually older version throughpip install metnetPlease ensure that you're using Python version 3.9 or above.DataWhile the exact training data used for both MetNet and MetNet-2 haven't been released, the papers do go into some detail as to the inputs, which were GOES-16 and MRMS precipitation data, as well as the time period covered. We will be making those splits available, as well as a larger dataset that covers a longer time period, withHuggingFace Datasets! Note: The dataset is not available yet, we are still processing data!fromdatasetsimportload_datasetdataset=load_dataset("openclimatefix/goes-mrms")This uses the publicly avaiilable GOES-16 data and the MRMS archive to create a similar set of data to train and test on, with various other splits available as well.Pretrained WeightsPretrained model weights for MetNet and MetNet-2 have not been publicly released, and there is some difficulty in reproducing their training. We release weights for both MetNet and MetNet-2 trained on cloud mask and satellite imagery data with the same parameters as detailed in the papers on HuggingFace Hub forMetNetandMetNet-2. These weights can be downloaded and used using:frommetnetimportMetNet,MetNet2model=MetNet().from_pretrained("openclimatefix/metnet")model=MetNet2().from_pretrained("openclimatefix/metnet-2")Example UsageMetNet can be used with:frommetnetimportMetNetimporttorchimporttorch.nn.functionalasFmodel=MetNet(hidden_dim=32,forecast_steps=24,input_channels=16,output_channels=12,sat_channels=12,input_size=32,)# MetNet expects original HxW to be 4x the input sizex=torch.randn((2,12,16,128,128))out=[]forlead_timeinrange(24):out.append(model(x,lead_time))out=torch.stack(out,dim=1)# MetNet creates predictions for the center 1/4thy=torch.randn((2,24,12,8,8))F.mse_loss(out,y).backward()And MetNet-2 with:frommetnetimportMetNet2importtorchimporttorch.nn.functionalasFmodel=MetNet2(forecast_steps=8,input_size=64,num_input_timesteps=6,upsampler_channels=128,lstm_channels=32,encoder_channels=64,center_crop_size=16,)# MetNet expects original HxW to be 4x the input sizex=torch.randn((2,6,12,256,256))out=[]forlead_timeinrange(8):out.append(model(x,lead_time))out=torch.stack(out,dim=1)y=torch.rand((2,8,12,64,64))F.mse_loss(out,y).backward()Contributors ✨Thanks goes to these wonderful people (emoji key):Jacob Bieker💻Jack Kelly💻Valter Fallenius📓terigenbuaa💬Kan.Dai💬Sailesh Bechar💬This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: metofficeamd
MetOfficeAMDPython wrapper around MetOffice Atmospheric Model Data REST APIIN DEVELOPMENTMetOfficeAMD is a simple wrapper for the API provided by the British Met Officehttps://metoffice.apiconnect.ibmcloud.com/metoffice/production/_ known as Weather DataHub. It can be used to retrieve weather observations and forecasts. The aim is to forecus on the AMD - Atmosphere Model Data REST APIhttps://metoffice.apiconnect.ibmcloud.com/metoffice/production/product/17502/api/16908AccessYour need to register and obtain a API key and secret. This should be placed in environment variables asAPI_KEYandAPI_SECRETInstallationpip install metofficeamdData variablesWhen the data is loaded they are given a short namelcc   : Low-level cloud cover in %.mcc   : Medium-level cloud cover in %.hcc   : High-level cloud cover in %.sde   : Snow depth in meters.dswrf : Downward longwave radiation flux - groundt     : Air temperature at 1 meter above surface in Kelvin.r     : Relative humidty in %.vis   : Visibility in meters.si10  : Wind speed in meters per second, 10 meters above surface.prate : Precipitation rate at the surface in kg/m^2/s.
Package: metoffice-weather-cli
metoffice-weather-cliA CLI tool for fetching and printing weather data from theMet Office Weather DataHub API.InstallationPyPIOpen the command line and typepython3 -m pip install metoffice-weather-cli. You can then run the program anywhere
by typingpython3 -m metoffice_weather_cli <flags>.Note: you may need to replacepython3with your OS's equivalent.UsageTo use this program, you must have a Met Office Weather DataHub API key and
a geocode.xyz Auth token (optional, used for geocoding only). These can be added by running the program with
the-cflag or manually added in a .env file placed in themetoffice-weather-clipackage directory as such:DATAHUB_API_KEY=xxxxxxxx
DATAHUB_SECRET=xxxxxxxx
GEOCODE_AUTH=xxxxxxxxRunpython3 -m metoffice_weather_cliin the command line (optionally with the-hflag) to view the help page.TodoPick all 'useful' information out of the Met Office data - some is currently omittedAllow preferences to be set in a config file for the data printed outSwitch from .env-based saving of API keys to another format (e.g. JSON) to avoid wiping files containing
environment variables unrelated to the program
Package: metoffice-weather-datahub
MetOfficeDataHubPython wrapper around MetOffice Atmospheric Model Data REST APIMetOfficeDataHub is a simple wrapper forthe API provided by the British Met Officeknown as Weather DataHub.
It can be used to retrieve weather observations and forecasts. The aim is to focus on the AMD -
Atmosphere Model Data REST APIhttps://metoffice.apiconnect.ibmcloud.com/metoffice/production/product/17502/api/16908This wrapper currently only downloads the latest results. No historic data can be fetched.
The timestamp can be seen in the grib/xarray files.⚠️ This (unofficial) library has been built and is maintained byOpen Climate Fix, not theUK MetOffice.AccessYouneed to register with the Weather DataHuband obtain an API key and secret. These should be placed in environment variables
asAPI_KEYandAPI_SECRET.PythonInstallationInstall directly from pypi usingpip install metoffice-weather-datahubExamplefrommetofficedatahub.multiple_filesimportMetOfficeDataHub# 1. Get data from API, download grib filesdatahub=MetOfficeDataHub(client_id="fake",client_secret="fake")datahub.download_all_files(order_ids=["test_order_id"])# 2. load grib files to one Xarray Datasetdata=datahub.load_all_files()CLIYou can run the script directly as a CLI using:python3metofficedatahub/app.py--save-dir="s3://bucket/folder"which will download all the files from Weather DataHub, join them together into a xarray dataset, and then save them.You can set the environmental variableLOG_LEVELto define whatlog levelyou would like.It may also be worth setting 'RAW_DIR' so that the raw files are saved to a certain folder,
and not downloded again if they are already there.DockerThe application can be run using dockerYou can pull the production docker image from docker hub usingdockerpullopenclimatefix/metoffice_weather_datahublocalYou can also build your own docker image locally usingdockerbuild-tmetofficedatahub-finfrastructure/docker/Dockerfile.and then to run the docker file usedockerrun-it-eAPI_KEY=change-eAPI_SECRET=change-eSAVE_DIR='save_dir'-eORDER_IDS='id1 id2 id3'metofficedatahubData variablesWhen the data is loaded they are given a short name. Here is are some common examples:lcc   : Low-level cloud cover in %.mcc   : Medium-level cloud cover in %.hcc   : High-level cloud cover in %.sde   : Snow depth in meters.dlwrf : Downward longwave radiation flux - groundt     : Air temperature at 1 meter above surface in Kelvin.r     : Relative humidty in %.vis   : Visibility in meters.si10  : Wind speed in meters per second, 10 meters above surface.prate : Precipitation rate at the surface in kg/m^2/s.Contributors ✨Thanks goes to these wonderful people (emoji key):Peter Dudfield💻Flo💻Jack Kelly👀Jacob Bieker👀This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: metomi-rose
RoseRose: a framework for managing and running meteorological suites.Python 2 or Python 3 ?Rose 2019Python 2PyGTK GUI2019.01.xbranch in the source codeRose 2Python 3No GUIsWeb-based GUIs will follow in later Rose 2 releasesmasterbranch in the source codeInstallation|User Guide|How to ContributeCopyright and Terms of UseCopyright (C) 2012-2024British Crown (Met Office) & ContributorsRose 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
(at your option) any later version.Rose 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 Rose. If not, seehttp://www.gnu.org/licenses/.Rose documentation is licensed under the British Open Government
Licence. See doc/rose-terms-of-use.html andhttp://www.nationalarchives.gov.uk/doc/open-government-licence/Seehttp://metomi.github.io/rose/doc/html/terms.html.Acknowledgement for non-Rose WorkSeeAcknowledgement for Non-Rose Work.