Saravanan666/pypi-org huggingface dataset:
Package: sensenova
Sensenova Python LibraryThe Sensenova Python library provides convenient access to the Sensenova API from applications written in the Python
language.InstallationYou don't need this source code unless you want to modify the package. If you just
want to use the package, just run:pipinstall--upgradesensenovaUsageConfigure API KEYSet environment variable:exportSENSENOVA_ACCESS_KEY_ID=exportSENSENOVA_SECRET_ACCESS_KEY=Or set sensenova.access_key_id and sensenova.secret_access_key to its value:importsensenovasensenova.access_key_id="..."sensenova.secret_access_key="..."APIclisensenovaapichat_completions.create-mxxx-guser"Say this is a test!"--streampythonimportsensenova# create a chat completionchat_completion=sensenova.ChatCompletion.create(model="xxx",messages=[{"role":"user","content":"Say this is a test!"}])# print the chat completionprint(chat_completion.data.choices[0].message)python asyncAsync support is available in the API by prepending a to a network-bound method:importsensenovaimportasyncioasyncdefcreate_chat_completion():chat_completion_resp=awaitsensenova.ChatCompletion.acreate(model="xxx",messages=[{"role":"user","content":"Say this is a test!"}])print(chat_completion_resp.data.choices[0].message)asyncio.run(create_chat_completion())To make async requests more efficient, you can pass in your own aiohttp.ClientSession, but you must manually close the
client session at the end of your program/event loop:importsensenovafromaiohttpimportClientSessionsensenova.aiosession.set(ClientSession())# At the end of your program, close the http sessionawaitsensenova.aiosession.get().close()ToolsRun the following command on data.json to get the cleaned_data.json filesensenovatoolsfine_tunes.prepare_data-fdata.jsonRequirementsPython 3.7.1+
Package: senseppi
SENSE-PPISENSE-PPI is a Deep Learning model for predicting physical protein-protein interactions based on amino acid sequences.
It is based on embeddings generated by ESM2 and uses Siamese RNN architecture to perform a binary classification.InstallationSENSE-PPI requires Python 3.9 or higher. To install the package, run:pipinstallsenseppiN.B.: if you intend to use thecreate_datasetcommand to generate new datasets from STRING,
do not forget to additionally install the MMseqs2 software (instructions can be found at:https://github.com/soedinglab/MMseqs2).
Themmseqscommand should be available in your PATH.UsageThere are 5 commands available in the package:train: trains SENSE-PPI on a given datasettest: computes test metrics (AUROC, AUPRC, F1, MCC, Presicion, Recall, Accuracy) on a given datasetpredict: predicts interactions for a given datasetpredict_string: predicts interactions for a given dataset using STRING database:
the interactions are taken from the STRING database (based on seed proteins).
Predictions are compared with the STRING database. Optionally, the graphs can be constructed.create_dataset: creates a dataset from the STRING database based on the taxonomic ID of the organism.The package already comes with one pretrained version of the modelfly_worm_human_chiken.ckpt(checkpoint with weights) that is used bydefaultif model path is not specified.
This model was trained on dataset that combined PPIs from D. melanogaster, C. elegans, H. sapiens and G. gallus, and it provides the best performance with respect to the other pretrained models.The original SENSE-PPI repository also contains two human-based models pretrained on human PPIs:senseppi.ckptanddscript.ckptpretrained on SENSE-PPI and DSCRIPT human datasets respectively.senseppi.ckpt: Download fromheredscript.ckpt: Download fromhereFor information about the other models that can be found in the pretrained_models folder, please refer to the original article.N.B.: All pretrained models were made to work with proteins in range 50-800 amino acids.By running the 'predict' command the model will automatically take 1 as the minimum length and the maximum length will be the length of the longest protein in the dataset. However, it isstrongly recommendedto use the proteins in range 50-800 amino acids for the best performance.if you use --min_len and --max_len arguments your fasta file will be filtered automatically, so make sure you have a backup.In order to cite the original SENSE-PPI paper, please use the following link:https://doi.org/10.1101/2023.09.19.558413The documentation for the package can be foundhere.
Package: sense-python-client
This is a client for the Sen.se API.Installation:$ pip install sense-python-clientDocumentation:https://sen.se/developers/DevelopmentSource code:$ git clone https://github.com/Sense-API/sense-python-client.gitRequirements:$ pip install -r requirements.txtRun the tests:$ python tests.py
$ coverage run tests.py
$ coverage report --show-missing --include="sense/*"
Package: sensestreet
sensestreetThis is a Python client for Sense Street API.Run the clientIn order to use the client, import SenseStreetClient from sensestreet:from sensestreet import SenseStreetClientand provide the app_id and api_url:client = SenseStreetClient(app_id="test", api_url="https://server.com/api")To simply ping the server, use:client.ping()Overview of all functions:Pingsping()Sends ping to the server to check if server is up and responding.ping_auth()Similar to ping but with authorisation - easy way to check if you're authorised to send requests to the server.Requests to prediction server:predict_rfqs(conversation, options)Sends request to predict rfqs in a conversation. Conversation has to be either a dict or a json.chat_snippet_predict_rfqs(chat_snippet, options)Sends request to predict rfqs in the conversation. Conversation has to be either a dict or a json. The difference between this function and the one above is the structure of the conversation,predict_rfqsis for a conversation in the Sense Street's format, whilechat_snippet_predict_rfqsis for conversation that is a cutout from the chat.Batch job requests:upload_files_with_conversations(files_paths)Uploads specified files with conversation to be processed by the server. It returns an id for each file that will be nedded later on to obtain processed conversations. To run this function you need to have permission to open these files. Make sure you're not trying to upload over 1Gb of files in a single request.upload_file_with_bond(file_path)Uploads file with bond data to the server.get_processed_conv_file(file_id, save_path)Returns file with processed conversations,file_idis the id that was returned during the files upload - by theupload_files_with_conversationsfunction.get_conv_file_status(file_id)Returns the status of the uploaded file. With this function you can check if the file has already been processed by the server and is ready for download.How to use your key to authorise requestsIn order to send requests to the server you need to obtain a pair of keys - public and private (if you don't have a key contact the Sense Street to get one). In order to be correctly authorised by the server initialised the SenseStreetClient with the paths to both of the keys:client = SenseStreetClient(
    app_id="id of your app",
    api_url="https://server.com/api",
    priv_key_path='path to your private key',
    pub_key_path='path to your public key'
    )How to define proxiesIn order to use proxy provide a dict of proxies when initializing Sense Street Client, eg.:client = SenseStreetClient(
    app_id="id of your app",
    api_url="https://server.com/api",
    request_args= { 'proxies': {
        "https": "https://10.10.1.10:1080",
            }
        }
    )To read more about proxies refer to:https://requests.readthedocs.io/en/latest/user/advanced/#proxiesSimilarly any additional request argument can be added:client = SenseStreetClient(
    app_id="id of your app",
    api_url="https://server.com/api",
    request_args= { 'verify': 'path'
        }
    )
Package: sense-text-extractor
sense-text-extractorsense-text-extractor是正文抽取客户端库安装方式(当前版本0.0.1)pip install sense-text-extractor使用指南基于sense-core的settings.ini的label配置调用：from sense_text_extractor import SenseTextExtractor
extractor = SenseTextExtractor(label='text_extractor')
text = extractor.extract_text("http://sports.sina.com.cn/g/pl/2019-01-11/doc-ihqhqcis5048507.shtml", "穆里尼奥在等待复出")
print(text)使用host和port的调用：extractor = SenseTextExtractor('52.83.143.61', '6681')
text = extractor.extract_text("http://sports.sina.com.cn/g/pl/2019-01-11/doc-ihqhqcis5048507.shtml", "穆里尼奥在等待复出")
print(text)使用说明extract_text方法可能抛出异常，需要自己捕捉。返回结果是string，如果是''字符串，表示可能没有抽取出正文。
如果用于爬虫，extract_text需要传入第三个参数，也就是下载的html源码，否则extractor的sever端因为获取超时而抛出异常，也容易被反爬虫限制。
Package: senseye-api-client
Example client-side code for use with the Senseye API in Python.This version of the Senseye API Client supports API versions >= v0.4.0.DocumentationOur documentation can be found at:https://senseye-api-client.readthedocs.io/For FAQs please visithttps://support.senseye.co.Currently, the best API documentation available is to read through the protos directly. They can be downloaded fromhereContributingBefore submitting a bug or pull request, please take a second to review thecontribution guidelinesIf you would like to generate language-specific stubs from our API protos, please download the latest protos fromhereLicenseSenseye-Api-Client is available under theBSD License 2.0.A full list of 3rd party software and respective licenses can be foundhere
Package: senseye-cameras
The senseye-cameras module is a generic camera interface written by SenseyeInc.  It allows Python developers to easily grab frames from multiple types of cameras and write them to disk.DocumentationOur documentation can be found at:https://senseye-cameras.readthedocs.io/en/latest/For FAQs please visithttps://support.senseye.co.ContributingTo report an issue or to contribute, please visit:https://github.com/senseye-inc/senseye-cameras. Before submitting a bug or pull request, please take a second to review the contribution guidelines.Licensesenseye-cameras is available under the BSD License 2.0.A full list of 3rd party software and respective licenses can be foundhere
Package: sensi
Libraryanalisis sentimen Bahasa Indonesia, berbasis Naive-Bayes.DependensibahasanltknumpypandassqlalchemyInstalasaipipinstallsensiPenggunaanWIKIContoh penerapan dapat dilihat pada directory 'apis' pada repositoryflask-skBacaresources/predictor.pyuntuk berbagai contoh lainnya.Creditsbahasaoleh@kangfend.LisensiMIT
Package: sensibleconfig
So you have some configuration variables, and you want them to be available to
be in any number of ini-like files, as well as overridable from the environment,
and overridable from the command line. Define once, and use.>>> options = [
...    Option('debug', 'Run in debug mode', False,
...           short_name='d', converter=bool, action='store_true'),
... ]
>>> conf = Config(options)
>>> conf.debug # Will start as the default value
FalseThis time we shall pass an env prefix to look up on, so as not to pollute any
environment namespace too badly:>>> conf = Config(options, 'PONY')
>>> conf.grab_from_env({'PONY_DEBUG': '1'})
>>> conf.debug
TrueNoteThe optional env dict parameter will default to os.environ if it is omitted.Now we can grab some stuff from argv:>>> conf = Config(options)
>>> conf.grab_from_argv(['--debug'])
[]
>>> conf.debug
TrueAlso, remember that you can serialize these things:>>> conf = Config(options)
>>> conf.to_dict()
{'debug': False}NoteIn real life you would import this:from sensibleconfig import Config, OptionSo as you can see above, the options were declared, and then the config object
was created from those options. It is imagined that an application may collate
the options from many different places, such as plugins which wish to define
their own options.
Package: sensiml-dev
The SensiML Python SDK provides a programmatic interface to SensiML REST API’s for
building machine learning pipelines including data processing, feature
generation and classification for developing smart sensor algorithms optimized
to run on embedded devices.Installation/Setup InstructionsThe SensiML Python SDK requirespython version 3.7 or greaterto be installed on your computer.We recommend running the SensiML Python SDK using Jupyter Notebook. Install Jupyter Notebook by opening a command prompt window on your computer and run the following commandpip install jupyterNext, to install the SensiML Python SDK open a command prompt window on your computer and run the following commandpip install SensiMLThis command will install the SensiML Python SDK and all of the required dependencies to your computer.Connect to SensiML CloudOnce you have installed the software, you can connect to the server by running the followingfrom sensiml import *client = SensiML()Connecting to SensiML servers requires and account, you can register athttps://sensiml.comDocumentation can be found herehttps://sensiml.com/documentation/
Package: sensirion-ble
sensirion-bleParser for Sensirion BLE devices.Supported devicesMyCO2 (aka SCD4x CO2 Gadget)Untested devicesSHT3x based gadgetsSHT4x based gadgetsOther devices could be supported at a later time, but I don't have any at hand.ReferenceThe parser is based on theSensirion Bluetooth Low Energy (BLE) Specification(also available in thereferencefolder).
Package: sensirion-driver-adapters
Installpipinstallsensirion-driver-adaptersRecommended usage is within a virtualenv.Usageimportsensirion_driver_adaptersCHANGELOG2.1.9fix usage of I2cChannel without CRC2.1.8Make mocks availableAdd channel providerProvide i2c_general_call_reset2.1.4Add support for post processing timeout2.1.3Fix and generalize packing/ unpacking of sequence data2.1.2Update readme2.1.1Fix dynamic_sized_unpack2.1.0Allow to use directly pack sequence type arguments.2.0.1Fix version 2.0.02.0.0Change package name to sensirion-driver-adapters.Allows to use the i2c and shdlc sensors with the
standard sensirion drivers.1.2.0Single byte array response can be represented as integer.1.1.0Support to work with multiple sensors at the same time1.0.1First public releaseExtended documentation1.0.0added support for ignore_ack0.9.0Initial release
Package: sensirion-gas-index-algorithm
Sensirion’s Gas Index Algorithm software provides a VOC and an NOx Index output signal calculated from the SGP40/41 raw
signal inputsSRAW_VOCandSRAW_NOX. Note: for SGP40, onlySRAW_VOCis available. This algorithm enables robust detection of
ambient changes of VOCs and NOx with minimal sensor-to-sensor variation. The algorithm is based on a statistical gain-offset
normalization and adapts both parameters constantly applying an exponentially decaying function of the learned parameters to
be able to adapt to changing environments.For the VOC Index output, the software must be instanced as VOC Algorithm while for the NOx Index output, the software must
be instanced as NOx Algorithm. It is important to feed the raw signals to the corresponding algorithm (i.e.,SRAW_VOCto the
VOC Algorithm andSRAW_NOXto the NOx Algorithm) at a constant sampling interval which must coincide with the sampling
interval that is used to read out the raw signals from the SGP40/41 sensor. The default sampling interval applied in the
algorithm is 1 s. In case, a different sampling interval should be used the definition of the sampling interval in the h.file
of the algorithm must be changed, too.The algorithm calculates the VOC and NOx Index signals recursively from a single raw tick value ofSRAW_VOCandSRAW_NOX,
respectively, which are both measured by the SGP40/41 sensor at each time step, as well as internal states that are updated
at each time step. These internal states are most importantly the recursively estimated mean and variance of the
correspondingSRAWsignal as well as some additional internal states such as uptime and other counters. After estimating the
states, the algorithm converts the raw signals in ticks into either VOC or NOx Index, respectively, and applies an adaptive
low-pass filter.Installpipinstallsensirion-gas-index-algorithmRecommended usage is within a virtualenv.Usage VOC Algorithmfromsensirion_gas_index_algorithm.voc_algorithmimportVocAlgorithmvoc_algorithm=VocAlgorithm()s_voc_raw=27000# read out from SGP41for_inrange(100):voc_index=voc_algorithm.process(s_voc_raw)print(voc_index)Usage NOx Algorithmfromsensirion_gas_index_algorithm.nox_algorithmimportNoxAlgorithmnox_algorithm=NoxAlgorithm()s_nox_raw=18000# read out from SGP41for_inrange(100):nox_index=nox_algorithm.process(s_voc_raw)print(nox_index)CHANGELOG3.2.1Use floating point version of Gas Index Algorithm3.2.0Add low power examplesAllow chaning of sampling interval3.1.0Add VOC gas index algorithm version 3.1.0Add NOx gas index algorithm version 3.1.0
Package: sensirion-i2c-adapter
Installpipinstallsensirion-i2c-adapterRecommended usage is within a virtualenv.Usageimportsensirion_i2c_adapterCHANGELOG1.2.0Single byte array response can be represented as integer.1.1.0Support to work with multiple sensors at the same time1.0.1First public releaseExtended documentation1.0.0added support for ignore_ack0.9.0Initial release
Package: sensirion-i2c-driver
This package contains the base I²C driver for various Sensirion sensors.
It handles low-level things like type conversions, checksum calculation,
error handling etc.NoteNormally you shouldn’t use this driver directly - instead you should use the
device-specific driver for your actual device as it provides easy-to-use
commands. But this driver is still useful if you want to transceive raw I²C
frames, or if there is no specific driver available yet for your device.Installation and UsageThe user manual is available athttps://sensirion.github.io/python-i2c-driver/.CHANGELOG1.0.0First public releaseAdd support for post processing time of commandsAdd propertyis_multi_channeltoI2cConnectionMake API ofSensirionWordI2cCommandbyte-orientedRename classSensirionWordI2cCommandtoSensirionI2cCommandRemove methodsread()andwrite()fromI2cConnectionRemove asynchronous mode (including theread()method) fromI2cDeviceLog transceived raw data withlog.debug()Various documentation improvements0.1.0Initial release
Package: sensirion-i2c-scd
This repository contains the Python driver to communicate with Sensirion
CO2 sensors using the I²C interface.Installation and UsageThe user manual is available athttps://sensirion.github.io/python-i2c-scd/CHANGELOG0.1.2[changed] Increase timing for single shot from 1350ms to 5000ms[changed] Increase timing for self test from 5500ms to 10000ms0.1.1[fixed] Fix typo: Carbon Dioxide0.1.0Initial release
Package: sensirion-i2c-sen5x
This package contains the driver for the Sensirion SEN5x sensors using
the I²C interface.The driver provides all I²C commands as Python methods and handles all the
low-level things like type conversions, CRC calculation, error handling
etc.Installation and UsageThe user manual is available athttps://sensirion.github.io/python-i2c-sen5x/.CHANGELOG0.1.1Fix encoding oflong_descriptioninsetup.pyon Windows, leading
to rendering issues on pypi.org0.1.0Initial release
Package: sensirion-i2c-sfm-sf06
Python I2C Driver for Sensirion SFM-SF06This repository contains the Python driver to communicate with a Sensirion sensor of the SFM-SF06 family over I2C.Clickhereto learn more about the Sensirion SFM-SF06 sensor family.Not all sensors of this driver family support all measurements.
In case a measurement is not supported by all sensors, the products that
support it are listed in the API description.Supported sensor typesSensor nameIÂ²C AddressesSFM43000x2A, 0x2B, 0x2C, 0x2DSFM31190x29SFM30030x28, 0x2DSFM30130x2FSFM30190x2EThe following instructions and examples use aSFM4300.Connect the sensorYou can connect your sensor over aSEK-SensorBridge.
For special setups you find the sensor pinout in the section below.Sensor pinoutPinCable ColorNameDescriptionComments1ADDRsee data sheet section 4.12SDAI2C: Serial data input / outputSerial data, bidirectional3GNDGround4VDDSupply Voltage3.0V to 5.0V5SCLI2C: Serial clock input6IRQnActive low. see data sheet section 3.3Documentation & QuickstartSee thedocumentation pagefor an API description and aquickstartexample.ContributingWe develop and test this driver using our company internal tools (version
control, continuous integration, code review etc.) and automatically
synchronize themasterbranch with GitHub. But this doesn't mean that we
don't respond to issues or don't accept pull requests on GitHub. In fact,
you're very welcome to open issues or create pull requests :-)Check coding styleThe coding style can be checked withflake8:pipinstall-e.[test]# Install requirementsflake8# Run style checkIn addition, we check the formatting of files witheditorconfig-checker:pipinstalleditorconfig-checker==2.0.3# Install requirementseditorconfig-checker# Run checkLicenseSeeLICENSE.
Package: sensirion-i2c-sgp43
Python I2C Driver for Sensirion SGP43This repository contains the Python driver to communicate with a Sensirion SGP43 sensor over I2C.Clickhereto learn more about the Sensirion SGP43 sensor.Air Quality Sensor for VOC and NOx Measurements.The default IÂ²C address ofSGP43is0x59.Connect the sensorYou can connect your sensor over aSEK-SensorBridge.
For special setups you find the sensor pinout in the section below.Sensor pinoutPinCable ColorNameDescriptionComments1redVDDSupply Voltage1.7V to 3.6V2blackGNDGround3greenSDAI2C: Serial data input / output4blueNCDo not connect5VDDHSupply voltage hotplate; see data sheet on how to connect.6yellowSCLI2C: Serial clock inputDocumentation & QuickstartSee thedocumentation pagefor an API description and aquickstartexample.ContributingWe develop and test this driver using our company internal tools (version
control, continuous integration, code review etc.) and automatically
synchronize themasterbranch with GitHub. But this doesn't mean that we
don't respond to issues or don't accept pull requests on GitHub. In fact,
you're very welcome to open issues or create pull requests :-)Check coding styleThe coding style can be checked withflake8:pipinstall-e.[test]# Install requirementsflake8# Run style checkIn addition, we check the formatting of files witheditorconfig-checker:pipinstalleditorconfig-checker==2.0.3# Install requirementseditorconfig-checker# Run checkLicenseSeeLICENSE.
Package: sensirion-i2c-sgp4x
This package contains drivers to communicate with Sensirion
VOC sensor SGP40 and VOC/NOx sensor SGP41 using the I²C interface.Installation and UsageThe user manual is available athttps://sensirion.github.io/python-i2c-sgp4x/CHANGELOG0.1.0Initial release of SGP40 and SGP41 I²C drivers
Package: sensirion-i2c-sht
This repository contains the Python driver to communicate with Sensirion
temperature and humidity sensors using the I²C interface.Installation and UsageThe user manual is available athttps://sensirion.github.io/python-i2c-sht/CHANGELOG0.4.0Add ART mode for SHT3x driver0.3.0AddShtc3I2cDevice0.2.2AddSht4xI2cDevice0.2.1AddSht2xI2cDeviceSHT3x: Add post processing time for soft reset commandSHT3x: Add command to read serial number0.2.0Initial public releaseUpdatesensirion-i2c-driverto version 1.0.0Rename response and data types0.1.0Initial release