Saravanan666/pypi-org huggingface dataset:
Package: gemini-pro-code-translator
gemini-pro-code-translatorEver wondered about translating code from one programming language to another quickly?Gemini Pro Code Translatoris the tool to do so.Source CodeThe source code of the applicationGemini Pro Code Translatoris available inSource Code.Installationpip install gemini-pro-code-translatorHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_CODE_TRANSLATOR_DIRECTORY> and has the value of GEMINI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.cd <GEMINI_PRO_CODE_TRANSLATOR_DIRECTORY>
python3 main.pyNote:Replace <GEMINI_PRO_CODE_TRANSLATOR_DIRECTORY> with the path to the directory of the applicationGemini Pro Code Translator.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.You will be required to input the following pieces of information.The name of the programming language you want to translate code from.The path of the file containing the code to be translated.The name of the programming language you want to translate code to (must be different from the one in step 1).The name of the file you want the translated code to be placed in (without the extension).Once you enter the values mentioned above, the file containing the code will be created inside "codes" directory.
Then, you will be asked whether you still want to continue unit testing or not. If you enter 'Y', you will be
redirected to an application window like in screenshot above. Else, you will exit the application.Below demonstrates how the file containing the translated code looks like.
Package: gemini-pro-translator
gemini-pro-translatorGemini Pro Translatoris a translation application inspired by Google Translate and integrated with Gemini Pro.Source CodeThe source code of the applicationGemini Pro Translatoris available inSource Code.Installationpip install gemini-pro-translatorHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_TRANSLATOR_DIRECTORY> and has the value of GEMINI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.cd <GEMINI_PRO_TRANSLATOR_DIRECTORY>
python3 main.pyNote:Replace <GEMINI_PRO_TRANSLATOR_DIRECTORY> with the path to the directory of the applicationGemini Pro Translator.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.You will be required to input the following pieces of information.The name of the language you want to translate text from.The path of the file containing the text to be translated.The name of the language you want to translate text to (must be different from the one in step 1).The name of the file you want the translated text to be placed in (include the file name and its extension only).Once you enter the values mentioned above, the file containing the translated text will be created inside "texts"
directory. Then, you will be asked whether you still want to continue unit testing or not. If you enter 'Y', you will
be redirected to an application window like in screenshot above. Else, you will exit the application.Below demonstrates how the file containing the translated text looks like.
Package: gemini-pro-unit-tester
gemini-pro-unit-testerEver wondered about running unit tests without even to write a single line of code? Well,Gemini Pro Unit Testerallows you to do so easily!Source CodeThe source code of the applicationGemini Pro Unit Testeris available inSource Code.Installationpip install gemini-pro-unit-testerHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_UNIT_TESTER_DIRECTORY> and has the value of GEMINI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.cd <GEMINI_PRO_UNIT_TESTER_DIRECTORY>
python3 main.pyNote:Replace <GEMINI_PRO_UNIT_TESTER_DIRECTORY> with the path to the directory of the
applicationGemini Pro Unit Tester.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.You are required to enter the following values.The programming language you want to run unit tests in - must be an existing programming language.The path of the file you want to test - the file mentioned must be a file of the programming language you entered in
step number 1 above (i.e., if you entered "Python" in step 1, the path of the file you entered must be a Python file).Once you enter the values mentioned above, the application will display the command used to run unit tests, together
with the test results. Then, you will be asked whether you still want to continue unit testing or not. If you enter
'Y', you will be redirected to an application window like in screenshot above. Else, you will exit the application.ProgressSupports creating and running unit tests for one file. (ongoing)Supports creation of unit tests based on code in multiple files. (pending)Version HistoryVersion 0.5 (Release Date: 29 December 2023):Supports creating and running unit tests for one file.Version 1 (Release Date: TBA, 2024):Supports creation of unit tests based on code in multiple files.
Package: gemini-pro-web-scraper
gemini-pro-web-scraperEver wondered about scraping a website without running a single line of code? Well,Gemini Pro Web Scraperis the
tool to do so. This tool automatically scrapes the data you want from a website of your choice.Source CodeThe source code of the applicationGemini Pro Web Scraperis available inSource Code.Installationpip install gemini-pro-web-scraperHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_WEB_SCRAPER_DIRECTORY> and has the value of GEMINI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.cd <GEMINI_PRO_WEB_SCRAPER_DIRECTORY>
python3 main.pyNote:Replace <GEMINI_PRO_WEB_SCRAPER_DIRECTORY> with the path to the directory of the applicationGemini Pro Web Scraper.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.You will be required to input the following pieces of information.The URL of the website you want to scrape (e.g.,https://sandbox.oxylabs.io/products).What the URL entered in step 1 contains (e.g.,gamesforhttps://sandbox.oxylabs.io/products).The number of elements you want to scrape.The details of each element you want to scrape (i.e., the name and the corresponding CSS selector for each element).The name of the file you want the code to be in (without the extension).Once you enter the values mentioned above, the file containing the code will be created inside "scrapers" directory.
Moreover, the CSV file containing the scraped data will be generated inside "csvs" directory. Then, you will be asked
whether you still want to continue unit testing or not. If you enter 'Y', you will be redirected to an application
window like in screenshot above. Else, you will exit the application.The Python file generated which contains the web scraping code looks like below.Below is how the generated CSV file looks like.
Package: gemini-public-api
Gemini Public APIThe gemini-public-api is an unofficial Python implementation of the public Gemini REST API. It provides a simple interface for interacting with the Gemini cryptocurrency exchange, supporting both synchronous and asynchronous communication.InstallationTo get the Gemini Public API Python client running on your local machine, use pip:pip3 install gemini-public-apiPlease make sure that you have Python 3.6 or newer, as this library requires it.UsageSynchronous Usagefromgemini_public_apiimportapisymbols=api.get_symbols()print(symbols.json())Asynchronous UsageThe library relies on theaiohttppackage for truly asynchronous execution. TheSessionContextManagercontext manager is used for making async requests. Here's how to fetch the available symbols asynchronously:fromgemini_public_api.aiohttpimportapifromgemini_public_api.aiohttp.session_context_managerimportSessionContextManagerasyncwithSessionContextManager()assession:response=awaitapi.get_symbols(session)asyncwithresponseasresp:data=awaitresp.json()print(data)Alternatively, without the context manager:importaiohttpfromgemini_public_api.aiohttpimportapisession=aiohttp.ClientSession()response=awaitapi.get_symbols(session)asyncwithresponseasresp:data=awaitresp.json()print(data)awaitsession.close()Dependenciesgemini-public-apiis built with:poetry-  A tool for dependency management and packaging in Python.hypothesis- A powerful, flexible, and easy-to-use library for property-based testing.requests- The definitive library for making HTTP requests in Python.aiohttp- An asynchronous HTTP client/server framework for asyncio and Python.Authorsmpol1tLicenseThis project is licensed under the MIT License
Package: geminipy
# Geminipy
A library for the Gemini bitcoin exchange APIEasily communicate with the Gemini Bitcoin exchange API without
having to deal with HTTP requests.RequirementsPlease get an API key from [https://exchange.gemini.com/settings/api](https://exchange.gemini.com/settings/api)Installationshell
pip install geminipyExamplepython
from geminipy import Geminipy# The connection defaults to the Gemini sandbox.
# Add ‘live=True’ to use the live exchange
con = Geminipy(api_key=’your API key’, secret_key=’your secret key’, live=True)# public request
symbols = con.symbols()# a Requests response is returned.
# So we can access the HTTP reponse code,
# the raw response content, or a json object
print symbols.status_code
print symbols.content
print symbols.json()# authenticated request
order = con.new_order(amount=’1’, price=’200’,side=’buy’)print order.json()#send a heartbeat
con.heartbeat()The required nonce is the current millisecond timestamp.
Package: geminitools
geminitoolsGeminitools is a Python package that can help you talk to the Gemini Exchange REST API.Geminitools is a simple API. You can't interface 1:1 with the Gemini Exchange API with geminitools. There are other packages for that. Instead, the main thing you can do is buy. As of yet there is no sell option (why would you want to anyway?).Installationpip install geminitoolsExample Usageimport geminitools

gem = geminitools.Gem('https://api.gemini.com', 'key', 'secret')

gem.place_cost_buy_order('BTCUSD', 10, 70000)APIclass geminitools.Gem(base_url, key, secret)get_supported_symbols()Make a call to the/v1/symbolsendpoint and return a list of accepted symbols.get_ticker_price(symbol, price_type='ask')Make a call to the/v1/pubticker/endpoint and return the value defined byprice_type- defaults to 'ask', the asking price.convert_cost_to_asset_amount(symbol, cost, rounded=8)Dividescostby the current ticker price given bysymbolrounding toroundeddecimal places, and returns the resulting asset amount.E.g. ifsymbolis 'btcusd',costis 50 (USD) and the current ticker price is 60000 (USD), the result would be 50 / 60000 = 0.00083333 (BTC)place_amount_buy_order(symbol, amount, price)Make a call to the/v1/order/newendpoint, placing a buy order foramountwith a limit ofprice, and returns the API response. If you passsymbol'BTCUSD',amountwould be the quantity of BTC you want to buy, whilepricewould be the max USD market price you're willing to pay.E.g.amount= 0.1 andprice= 10000 would cause 0.1 BTC to be bought if the price of BTC is less than or equal to 10000 USD.place_cost_buy_order(symbol, cost, price)Similar toplace_asset_buy_orderbut calculates the amount of the asset to buy based on thecostpassed. Returns the API response.E.g. Passingsymbol'BTCUSD' and acostvalue of 10 would cause the order of 10 USD worth of BTC to be bought.
Package: gemlog-from-rss
Gemlog-from-RSSA simple RSS to Gemlog (Gemini log) converter.The original version is developed forSPIP, but I am going to also work on a
version for WordPress.Usage (SPIP)A working example for the SPIP version of this library can be ran
using theexample.pyclass. It also allows for a quick preview of the code without having to go intogemlog_from_rss/examples.py.(Main) file structure - minimum working codeTo run this code the following structure is required:fromgemlog_from_rss.spipimportMainPage,Pageimportxml.etree.ElementTreeasETimportshutilfrompathlibimportPathPath("resources").mkdir(parents=False,exist_ok=True)main_page=MainPage(feed="https://url.to.feed")Path(main_page.root).mkdir(parents=True,exist_ok=True)tree=ET.parse("resources/all_posts.xml")root=tree.getroot()main_page.root=root# Adding those pages is optional!page=Page()page.download_html("http://url.to.html.resource/file.html")page.fetch_content()page_2=Page()page_2.download_html("http://url.to.html.resource/file.html")page_2.fetch_content()main_page.add_page(page)main_page.add_page(page_2)# alternatively:main_page.add_pages([page,page_2])main_page.add_posts()main_page.create_files()withopen(f"{main_page.root_dir}/index.gmi","w")asf:f.write(main_page.make_main_page())# Remove temporary resources directorytry:shutil.rmtree('resources')exceptOSErrorase:print("Error:%s:%s"%('resources',e.strerror))Running the serverTo run the Gemini server, please use Gemini server software.
This package doesn't come with a Gemini server, but I recommendagate.
It is super easy to install and run, and you can make this library work with it by outputting the articles and index.gmi
to a directory used by agate.Please make sure that the files outputted bygemlog_from_rssare either located in the root directory of your Gemini
server or that they are linked to from your main Gemini page.Contributing and further developmentThis librarywillbe developed further. If you want to contribute to development, please fork this repository
and start a pull request when you are ready to submit.
Package: gemmaai
Llama API ClientGemmaAI is a Python SDK for interacting with the Llama API. It abstracts away the handling of aiohttp sessions and headers, allowing for a simplified interaction with the API.InstallationYou can install the GemmaAI SDK using pip:pipinstallgemmaaiUsageAfter installing the SDK, you can use it in your Python projects like so:importjsonfromgemmaaiimportGemmaAI# Initialize the gemmaai with your api_tokenllama=GemmaAI("<your_api_token>")# Define your API requestapi_request_json={"messages":[{"role":"user","content":"Extract the desired information from the following passage.:\n\nHi!"},],"functions":[{'name':'information_extraction','description':'Extracts the relevant information from the passage.','parameters':{'type':'object','properties':{'sentiment':{'title':'sentiment','type':'string','description':'the sentiment encountered in the passage'},'aggressiveness':{'title':'aggressiveness','type':'integer','description':'a 0-10 score of how aggressive the passage is'},'language':{'title':'language','type':'string','description':'the language of the passage'}},'required':['sentiment','aggressiveness','language']}}],"stream":False,"function_call":{"name":"information_extraction"},}# Make your request and handle the responseresponse=llama.run(api_request_json)print(json.dumps(response.json(),indent=2))Other parameters that you can pass in the request json is:{
  ...
  "max_length" = 500,
  "temperature"= 0.1,
  "top_p"= 1.0,
  "frequency_penalty"=1.0
  ...
}Note: Stream is still not working, so it is recommended to submit withstream: False.Change LogVersion 0.1: Initial releaseContributingWe welcome contributions to this project. Please see the Contributing Guidelines for more details.Licensegemmaai SDK is licensed under the MIT License. Please see the License File for more details.
Package: gemmaapi
Llama API ClientGemmaAPI is a Python SDK for interacting with the Llama API. It abstracts away the handling of aiohttp sessions and headers, allowing for a simplified interaction with the API.InstallationYou can install the GemmaAPI SDK using pip:pipinstallgemmaapiUsageAfter installing the SDK, you can use it in your Python projects like so:importjsonfromgemmaapiimportGemmaAPI# Initialize the gemmaapi with your api_tokenllama=GemmaAPI("<your_api_token>")# Define your API requestapi_request_json={"messages":[{"role":"user","content":"Extract the desired information from the following passage.:\n\nHi!"},],"functions":[{'name':'information_extraction','description':'Extracts the relevant information from the passage.','parameters':{'type':'object','properties':{'sentiment':{'title':'sentiment','type':'string','description':'the sentiment encountered in the passage'},'aggressiveness':{'title':'aggressiveness','type':'integer','description':'a 0-10 score of how aggressive the passage is'},'language':{'title':'language','type':'string','description':'the language of the passage'}},'required':['sentiment','aggressiveness','language']}}],"stream":False,"function_call":{"name":"information_extraction"},}# Make your request and handle the responseresponse=llama.run(api_request_json)print(json.dumps(response.json(),indent=2))Other parameters that you can pass in the request json is:{
  ...
  "max_length" = 500,
  "temperature"= 0.1,
  "top_p"= 1.0,
  "frequency_penalty"=1.0
  ...
}Note: Stream is still not working, so it is recommended to submit withstream: False.Change LogVersion 0.1: Initial releaseContributingWe welcome contributions to this project. Please see the Contributing Guidelines for more details.Licensegemmaapi SDK is licensed under the MIT License. Please see the License File for more details.
Package: gemmapy
This is a Python wrapper forGemma’s
RESTfulAPI. Gemma is a web
site, database and a set of tools for the meta-analysis, re-use and
sharing of genomics data, currently primarily targeted at the analysis
of gene expression profiles. Gemma contains data from thousands of
public studies, referencing thousands of published papers.Installation instructionsThe package requires Python3.6+.Install it from a local copygitclonegit@github.com:PavlidisLab/gemmapy.gitcdgemmapypipinstall.Install it from PyPIpipinstallgemmapyUsageTo get started withgemmapy, read theTutorial.The full documentation can be found athttps://pavlidislab.github.io/gemmapy/.CitationTo cite Gemma, please use:Lim, N. et al., Curation of over 10 000
transcriptomic studies to enable data reuse, Database, 2021.
Package: gemma-zds-client
The Common Ground API Client is a generic client for Common Ground APIs built with
OpenAPI 3.0 specifications.Contents1Features2Installation and usage1FeaturesDriven by OAS 3.0 specification(Pluggable) caching of api specificationsCreate/mutate resources according to the api specificationsSupport for multiple authentication schemesZGW auth (JWT based)API-key via HTTP headersor none, for open APIsGeneric approach with some builtins for the “Zaakgericht Werken API’s” standardBuilt on top of battle-provenrequestslibrary.2Installation and usageSee thedocumentation
Package: gem-metrics-fork
Automatic metrics for GEM benchmark tasks. Can also be used standalone for evaluation of various natural
language generation tasks.InstallationGEM-metrics require recent Python 3, virtualenv or similar is recommended. To install, simply run:` git clonehttps://github.com/GEM-benchmark/GEM-metricscdGEM-metricspip install-rrequirements.txt-rrequirements-heavy.txt`If you want to just run the metrics from console (and don’t need direct access to the source code), you can just run:` pip install'gem-metrics[heavy]@git+https://github.com/GEM-benchmark/GEM-metrics.git'`Note that some NLTK stuff may be downloaded upon first run into a subdirectory where the code is located,
so make sure you have write access when you run this.
Also note that all the required Python libraries are around 3 GB in size when installed.If you don’t need trained metrics (BLEURT, BERTScore, NUBIA, QuestEval), you can ignore the “heavy” part,
i.e. only install dependencies fromrequirements.txtor only usegem-metricsinstead ofgem-metrics[heavy]if installing without checkout. That way, your installed libraries will be ~300 MB.Script UsageTo compute all default metrics for a file, run:` <script>[-rreferences.json] outputs.json `Where<script>is either./run_metrics.py(if you created a checkout) orgem_metricsif you installed directly viapip.See [test_data](test_data/) for example JSON file formats.For calculating basic metrics with the unit test data, run:` ./run_metrics.py-stest_data/unit_tests/sources.json-rtest_data/unit_tests/references.json test_data/unit_tests/predictions.json `Use./run_metrics.py -hto see all available options.By default, the “heavy” metrics (BERTScore, BLEURT, NUBIA and QuestEval) aren’t computed. Use–heavy-metricsto compute them.Library UsageYou can compute metrics for the same JSON format as shown in [test_data](test_data/), or you can work
with plain lists of texts (or lists of lists of texts in the case of multi-reference data).Import GEM-metrics as a library:` import gem_metrics `To load data from JSON files:` preds =gem_metrics.texts.Predictions('path/to/pred-file.json')refs =gem_metrics.texts.References('path/to/ref-file.json')`To prepare plain lists (assuming the same order):` preds = gem_metrics.texts.Predictions(list_of_predictions) refs = gem_metrics.texts.References(list_of_references)  # input may be list of lists formulti-ref`Then compute the desired metrics:` result = gem_metrics.compute(preds, refs,metrics_list=['bleu','rouge'])# add list of desired metrics here `List of supported metricsReferenceless:local_recall– LocalRecallmsttr– MSTTRngrams– n-gram statisticsttr– TTRReference-based:bertscore– BERTScore (heavy)bleu– BLEUbleurt– BLEURT (heavy)chrf– CHRFcider– CIDERmeteor– Meteor (heavy)moverscore– MoverScore (heavy)nist– NISTnubia– NUBIA (heavy)prism– Prismquesteval– QuestEval (heavy)rouge– ROUGEter– TERwer– WERyules_i– Yules_ISource + reference based:sari– SARILicenseLicensed under [the MIT license](LICENSE).
Package: gemmforge
GPU-GEMM generator for the Discontinuous Galerkin methodInstallationFor userspip install gemmforgeFor developersgit clone https://github.com/ravil-mobile/gemmforge.git gemmforgecd gemmforgepip install -e .UsagefromgemmforgeimportDenseMatrix,GemmGenerator,GenerationErrorfromgemmforgeimportarcharch=arch.produce("nvidia","sm_60")mat_a=DenseMatrix(num_rows=56,num_cols=9,addressing="strided",bbox=[0,0,55,8],transpose=False)mat_b=DenseMatrix(num_rows=9,num_cols=9,addressing="strided",bbox=[0,0,8,8],transpose=False)mat_c=DenseMatrix(num_rows=56,num_cols=9,bbox=[0,0,55,8],addressing="strided",transpose=False)try:gen=GemmGenerator(arch,"float")gen.generate(mat_a,mat_b,mat_c,alpha=1.1,beta=1.1)print(gen.get_kernel())print(gen.get_launcher())print(gen.get_launcher_header())exceptGenerationErroraserr:print("ERROR:{}".format(err))raiseerr