Saravanan666/pypi-org huggingface dataset:
Package: ofxstatement-otp
Plugins to read statements provided by OTP (https://www.otpbank.hu).Current pluginIt’s a fork and adaptation ofhttps://github.com/Jacotsu/ofxstatement-intesaspLegacy pluginsThe plugins with “legacy” in their names parse the files exported by the previous
version of OTP’s netbank. That version is no longer available since September 2021.The exported XMLs are pretty much conformant to CAMT.053 (ISO-20022),
with some extra information thrown in here and there, or some missing data
in some other places. The ‘otp’ plugin handles these types of exports.For some weird reason credit card statements differed from debit
card statements and can only be exported in CSV format. The ‘otp_credit’
plugin handles such exports.The XML part is pretty much a copy-paste ofhttps://github.com/kedder/ofxstatement-iso20022at commit 6cd6d0317a801d466efb30322ab4d71a10771454 with modifications to accomodate
the idiosyncracies of OTP exported XMLs. The CSV side is some basic wrapping over
the built-in CSVStatementParser.Editing the pluginYou can follow the instructions athttps://github.com/kedder/ofxstatement-sampleif you want to make changes to this plugin. Pull requests are welcome!
Package: ofxstatement-paypal
ofxstatement-paypal# Paypal plugin for ofxstatementThis project provides a custom plugin forofxstatementfor Paypal. It is based
on the work done by gerasiov (https://github.com/gerasiov/ofxstatement-paypal/).ofxstatement_ is a tool to convert proprietary bank statement to OFX format, suitable for importing to GnuCash / Odoo. Plugin for ofxstatement parses a particular proprietary bank statement format and produces common data structure, that is then formatted into an OFX file.Users of ofxstatement have developed several plugins for their banks. They are listed on mainofxstatementsite. If your bank is missing, you can develop
your own plugin.InstallationFrom PyPI repositoriespip3 install ofxstatement-paypalFrom sourcegit clone git@github.com:EtsBIZ4Africa/ofxstatement-paypal.git 
python3 setup.py installUsageFrom Paypal Web interface, download a CSV personnalized report for the period you wish.$ ofxstatement convert -t paypal-ng input.csv output.ofx
Package: ofxstatement-revolut
ofxstatement-revolutThis is a plugin forofxstatement. It implements
a parser for the Revolut CSV-formatted bank statement.Issue reports and pull requests are welcome.InstallationFrom PyPI repositoriespip3 install ofxstatement-revolutFrom sourcegit clone https://github.com/mlaitinen/ofxstatement-revolut.git
python3 setup.py installConfiguration optionsOptionDescriptionaccountDefine the account of this bank statementcurrencyThe base currency of the accountdate_formatThe date format in the bank statement. Note that you have to use double%-marks in the settings file like this:date_format = %%b %%d, %%Y2.0.2Ignore other than COMPLETED transactions. Pending transactions have their own structure in OFX
called STMTTRNP, but ofxstatement doesn't support it.Include the "Started Date" as the date the user initiated the transaction.2.0.1Version 2.0.0 republished due to some issues with PyPI2.0.0Complete backwards-incompatible refactoring, support the new CSV formatRequires ofxstatement >= 0.7.2Any transactions with a fee will generate an additional fee transaction where the payee is "Revolut"1.6.0Since version 0.6.5 ofxstatement requires a statement line to have either id, refnum or check_no. To avoid failing
the conversion, there's now a unique MD5 hashed ID computed from the date, payee, amount and balance.1.5.0Improved the parser by making the column header verification less strict.1.4.0Support September 2019 iOS CSV format1.3.0Date format is now configurable in the settings"Payment from " is now also counted as a deposit1.2.0Support May 2018 CSV format1.1.0Support April 2018 CSV format1.0.0First release
Package: ofxstatement-simple
This is anofxstatementplugin forSimpleJSON statements downloaded
from the site.ofxstatementconverts the JSON into a series of “check”
transactions in an OFX file.ofxstatementis a tool for converting proprietary bank statements into the
OFX format, suitable for importing into GnuCash, Moneydance, and other compatible
applications. The plugin for ofxstatement parses a particular proprietary bank
statement format and produces a common data structure that is then formatted
into an OFX file.RequirementsAs withofxstatement, this plugin requires Python 3.  You will need to haveofxstatementinstalled; the package will be brought in as a dependency if
you install the plugin viapip.InstallationYou can install the plugin via most of the normal Python methods (be sure to
install using your environment’s python3 installation). Remove the–useroption if you wish to install the package globally.pippip3 install --user ofxstatement-simplesetup.pypython3 setup.py install --userConfigurationNote that you can specify ‘bank’ and ‘account’ in ofxstatement’s configuration file (accessible
using theofxstatement edit-configcommand or directly at~/.local/share/ofxstatement/config.ini(on Linux, at least).  Setting these values makes it
easier for your personal finance application to recognize which account the file’s data
belongs to.Also note that transactions for zero amounts are filtered by default.  If you wish to include
zero-amount transactions, set ‘zero_filter’ to ‘false’ in your settings.  Here is an example
of a settings block for the simple plugin:[simple]
account = 8675309
plugin = simple
zero_filter = falseUsageExport your Simple transactions into a JSON file (it’s currently<date>-exported_transactions.json). Then run:$ ofxstatement convert -t simple <date>-exported_transactions.json simple.ofxYou can then importsimple.ofxinto the personal finance application of your choice.History0.1.0 (2015-10-11)Uploaded to pypiAdded to github
Package: ofxstatement-sparkasse-de
This project provides a plugin for ofxstatement that imports German Sparkasse PDF statements.ofxstatementis a tool to convert proprietary bank statement to OFX format, suitable for importing to GnuCash and other programs.If you encounter any errors when using this plugin, feel free to open an issue.
It is expected that the payee of transactions is not extracted for recent PDFs since these mix the payee and the memo.
You should use the official CSV export instead of this tool whenever possible.The plugin was tested on the following PDF layouts:New one-column view (used currently)One-column view (used up to Kontoauszug 10/2021)Two-column view (used up to Kontoauszug 7/2020)DevelopmentRunpipenv shell.
Package: ofxstatement-transferwise
Transferwise plugin for ofxstatementThis plugins is able to parse CSV statements fromtransferwise.com. Note, that only "accounting"
type of statement is supported.ConfigurationConfiguration can be edited withofxstatement edit-configcommand. These
configuration parameters are understood by this plugin:NameRequired?DescriptionaccountoptionalName for this accountcurrencyrequiredCurrency for this account
Package: ofxstatement-zm-stanbic
ofxstatement-zm-stanbic# Stanbic Zambia plugin for ofxstatementThis project provides a custom plugin forofxstatementfor Stanbic Bank (ZM). It is based
on the work done by JBBandos (https://github.com/jbbandos/ofxstatement-be-ing).ofxstatement_ is a tool to convert proprietary bank statement to OFX format, suitable for importing to GnuCash / Odoo. Plugin for ofxstatement parses a particular proprietary bank statement format and produces common data structure, that is then formatted into an OFX file.Users of ofxstatement have developed several plugins for their banks. They are listed on mainofxstatementsite. If your bank is missing, you can develop
your own plugin.InstallationFrom PyPI repositoriespip3 install ofxstatement-zm-stanbicFrom sourcegit clone git@github.com:BIZ4Africa/ofxstatement-zm-stanbic.git 
python3 setup.py installUsage$ ofxstatement convert -t stanbiczm input.csv output.ofxNote: Stanbic does not provide csv export, but this plugin is based on the CSV from PDF using tabula-py module
Package: ofxtools
ofxtoolsis a Python library for working with Open Financial Exchange (OFX)
data - the standard format for downloading financial information from banks
and stockbrokers.  OFX data is widely provided by financial institutions so
that their customers can import transactions into financial management
software such as Quicken, Microsoft Money, or GnuCash.If you want to download your transaction data outside of one of these
programs - if you wish to develop a Python application to use this data -
if you need to generate your own OFX-formatted data…ofxtoolsis for you!What is it?ofxtoolsrequests, consumes and
produces both OFXv1 (SGML) and OFXv2 (XML) formats.
It converts serialized markup to/from native Python objects of
the appropriate data type, while preserving structure.
It also handles Quicken’s QFX format, although it ignores Intuit’s proprietary
extension tags.In a nutshell,ofxtoolsmakes it simple to get OFX data and extract it,
or export your data in OFX format.ofxtoolstakes a comprehensive, standards-based approach to processing OFX.
It targets compliance with theOFX specification, specifically OFX versions
1.6 and 2.03.ofxtoolsCoverage of the OFX SpecificationSection 7 (financial institution profile)Section 8 (service activation; account information)Section 9 (email over OFX)Section 10 (recurring bank transfers)Section 11 (banking)Section 12 (bill pay)Section 13 (investments)This should cover the great majority of real-world OFX use cases.  A particular
focus ofofxtoolsis full support of the OFX investment message set,
which has been somewhat neglected by the Python community.The major item remaining on theofxtools“to do” list is to implement the
tax schemas.  It’s currently a low priority to implement Section 14 (bill
presentment) or the extensions contained in OFX versions beyond 2.03, but
you’re welcome to contribute code if you need these.Some care has been taken with the data model to make it easily maintainable
and extensible.  Theofxtools.modelssubpackage contains simple, direct
translations of the relevant sections of the OFX specification.  Using existing
models as templates, it’s quite straightforward to define new models and
cover more of the spec as needed (the odd corner case notwithstanding).More than 10 years’ worth of OFX data from various financial institutions
has been run through theofxtoolsparser, with the results checked.  Test
coverage is high.Where is it?Full documentation is available atRead the Docs.For ease of installation,ofxtoolsis released onPyPI.Development ofofxtoolsis centralized atGitHub, where you will find
abug tracker.Installation Dependenciesofxtoolsrequires Python version 3.8+, and depends only on the standard
libary (no external dependencies).NOTE: As of version 0.6, ofxtools no longer supports Python version 2,
which went EOL 2020-01-01.
Package: ofxtoolslambda
ofxtoolsis a Python library for working with Open Financial Exchange (OFX)
data - the standard format for downloading financial information from banks
and stockbrokers.  OFX data is widely provided by financial institutions so
that their customers can import transactions into financial management
software such as Quicken, Microsoft Money, or GnuCash.If you want to download your transaction data outside of one of these
programs - if you wish to develop a Python application to use this data -
if you need to generate your own OFX-formatted data…ofxtoolsis for you!What is it?ofxtoolsrequests, consumes and
produces both OFXv1 (SGML) and OFXv2 (XML) formats.
It converts serialized markup to/from native Python objects of
the appropriate data type, while preserving structure.
It also handles Quicken’s QFX format, although it ignores Intuit’s proprietary
extension tags.In a nutshell,ofxtoolsmakes it simple to get OFX data and extract it,
or export your data in OFX format.ofxtoolstakes a comprehensive, standards-based approach to processing OFX.
It targets compliance with theOFX specification, specifically OFX versions
1.6 and 2.03.ofxtoolsCoverage of the OFX SpecificationSection 7 (financial institution profile)Section 8 (service activation; account information)Section 9 (email over OFX)Section 10 (recurring bank transfers)Section 11 (banking)Section 12 (bill pay)Section 13 (investments)This should cover the great majority of real-world OFX use cases.  A particular
focus ofofxtoolsis full support of the OFX investment message set,
which has been somewhat neglected by the Python community.The major item remaining on theofxtools“to do” list is to implement the
tax schemas.  It’s currently a low priority to implement Section 14 (bill
presentment) or the extensions contained in OFX versions beyond 2.03, but
you’re welcome to contribute code if you need these.Some care has been taken with the data model to make it easily maintainable
and extensible.  Theofxtools.modelssubpackage contains simple, direct
translations of the relevant sections of the OFX specification.  Using existing
models as templates, it’s quite straightforward to define new models and
cover more of the spec as needed (the odd corner case notwithstanding).More than 10 years’ worth of OFX data from various financial institutions
has been run through theofxtoolsparser, with the results checked.  Test
coverage is high.Where is it?Full documentation is available atRead the Docs.For ease of installation,ofxtoolsis released onPyPI.Development ofofxtoolsis centralized atGitHub, where you will find
abug tracker.Installation Dependenciesofxtoolsrequires Python version 3.7+, and depends only on the standard
libary (no external dependencies).NOTE: As of version 0.6, ofxtools no longer supports Python version 2,
which goes EOL 2020-01-01.
Package: ogame-stats
ogame statswrapper and logic around public game statistics forhttps://ogame.orgSome classes and methods to retrieve public data of the online gameogame.
This package isNOTintended to interact with an account - which is forbidden anyway.Might be used to query the data sets, visualize results and generally to do data analysis.requirementsdepends on:python >= 3.6 (uses f-string)xmltodict as a convenience to convert XML data to more basic python typesrequests to perform http requests andpandas to perform queries on the datainstallationcreate your virtualenv with your preferred versionin a new directoryvirtualenv -p python3.<6,7,8> venvinstall the wrapperpip install ogama_data_apiusagebasic usagethe most basic usage would look like.#%%importogame_stats#%% supply the two inputs to uniquely identify a universeuniverse_id=162community='en'#%% instantiate and thereby load the datauniverse=ogame_stats.UniverseQuestions(universe_id,community)than you could take a look at the data sets.#%% get a list of all the planetsuniverse.universeidplayernamecoords011Arakis1:1:2...............[4378rowsx4columns]#%% find some playersuniverse.playersidnamestatusalliance01LegoraNaN..............[751rowsx4columns]advanced usageNow, data itself is nice. But lets ask it some questions.This is needs your help since asking the right questions is the key.e.g. look up the planets of a user.##%% get the coordinates and names of all the planets of a playeruniverse.get_planets_of_player('someSpecialName')[{'coords':'1:45:4','name':'MotherPlanet'},{'coords':'1:144:2','name':'ColonyC'},{'coords':'1:145:3','name':'ColonyB'},{'coords':'1:303:5','name':'ColonyA'},{'coords':'5:119:9','name':'ColonyE'},{'coords':'1:289:9','name':'ColonyD'},{'coords':'1:389:9','name':'ColonyF'}]or ask for the status (active, inactive, banned, holiday etc.).universe.get_player_status('someSpecialName')'I'or just dump everything aboutsomeSpecialName:universe.get_player_data('someSpecialName')get the complete list of players within a specific allianceuniverse.get_players_of_alliance('someAlliance')idnamestatusalliance291103910reabuilderNaN50023429210393014Funv500234312104181nightowlNaN500234...get to see the distribution of the planets owned by the alliance members.universe.get_planets_distribution_by_galaxy('someAlliance'){'1':7,'2':17,'3':29,'4':38,'5':9,'6':9,'7':9,'8':2,'9':6}Update frequencies of dataDon't spam the servers with requests. Since the data sets and classes avoid the usage of
XML attributes, it's easy to just pickle yourUniverseDatafor tests, development and everything else.
These are the update frequencies I copied over at some point in time (might have changed):players.xml -> daily
universe.xml -> weekly
highscore.xml -> hourly
alliances.xml -> daily
serverData.xml -> daily
playerData.xml -> weekly
localization.xml -> static
universes.xml -> staticMaybe the easiest way would be to userequests_cache.import requests_cache
requests_cache.install_cache('demo_cache')issues/ideas... are generally welcome. saves us time.
Also, the overall design is far from being ideal.
Pull requests welcome. Be sure to include the tests.
Package: oganesson
Oganessonoganesson(ogfor short) is a python package that enables you to apply artificial intelligence workflows to your material discovery projects.InstallationYou can installogusing thepipcommand as follows:pip install oganessonFeaturesogis currently under active development. The following features are currently available.Machine learning descriptorsogwill bring together machine learning descriptors for materials and molecules within a unified framework.ogcurrently provides the following descriptors:The BACD, ROSA and SymmetryFunctions introduced in thispublicationMost of the descriptors fromDScribeEach descriptor has its own class, which extends theDescriptorsclass in theoganesson.descriptorsmodule. Here is an example of how to describe a structure using theBACDandSymmetryFunctionsdescriptor classes.fromoganesson.descriptorsimportBACD,SymmetryFunctionsfromoganesson.ogstructureimportOgStructurebacd=BACD(OgStructure(file_name='examples/structures/Li3PO4_mp-13725.cif'))print(bacd.describe())sf=SymmetryFunctions(OgStructure(file_name='examples/structures/Li3PO4_mp-13725.cif'))print(sf.describe())Genetic algorithmsThe main purpose ofogis to make complex artificial intelligence workflows easy to compose. Here is an example: running a genetic search for structures, where the structure optimization is performed using the M3GNET neural network model.fromoganesson.genetic_algorithmsimportGAga=GA(species=['Na']*4+['H']*4)foriinrange(10):ga.evolve()Generation of the diffusion path for NEB calculationsThe most painful part of doing transition state calculations in VASP is in building the images. The following code makes this happen in 2 lines of code. You only need to specify the structure file, and the atomic species you want to diffuse, and OgStructure will generate a folder for each path, and then write the POSCAR image files in each of these folders.In the following example, we explore the possible Li diffusion paths in Li3PO4, given there are 6 Li atoms in the cell.fromoganesson.ogstructureimportOgStructureog=OgStructure(file_name='examples/structures/Li3PO4_mp-13725.cif')og.generate_neb('Li')Note that the default value ofr, which is 3, is sufficient for lithium systems. However, for the case of larger atoms such as Na, a larger value ofrwould be required.Finding a reasonable adsorption site of an atom on a surfacefromoganesson.ogstructureimportOgStructureog=OgStructure(file_name='examples/structures/MoS2.vasp')og.add_atom_to_surface('Li').structure.to('MoS2_Li.vasp','poscar')
Package: ogarantia-streamlit-card
ogarantia-streamlit-cardStreamlit Component for a UI card - Adapted for Ogarantia applications.Authors:Wilder Lopes(wilder@ogarantia.com)
Based on the work by@gamcoh@Pernod RicardInstallationFrom pipInstallogarantia-streamlit-cardwith pippipinstallogarantia-streamlit-cardFrom sourceBuild the react frontendGo inside the frontend folder:cd ogarantia_streamlit_card/frontendInstall npm packages (if you run into problems, just deletepackage-lock.jsonand run the install command again):npm installBuild the frontend:npm run buildBuild the python wheelGo back to the project root and run (you might need topip install buildfirst):python -m build .This generates the folderdistthat contains the python wheel. Finally,pip install dist/*.whlUsageImport thecardfunction fromogarantia-streamlit_cardfromogarantia_streamlit_cardimportcardhasClicked=card(title="Hello World!",text="Some description",image="https://get.ogre.run/images/ogarantia_logoBlue.png"url="https://github.com/Ogarantia/st-card")
Package: ogb-lite
Open Graph Benchmark Lite (ogb_lite)Open Graph Benchmark Lite (ogb_lite) is a subset of the ogb project. It supports library-agnostic loaders and it does not require torch.99.99% of the code is copied from the OGB project:https://github.com/snap-stanford/ogb <https://github.com/snap-stanford/ogb>_We only make some small changes such that you can use ogb_lite without installing torch.Installation.. code-block:: bashpip install ogb_liteTutorialogb_lite only contains three library-agnostic loaders:NodePropPredDataset\ ,LinkPropPredDataset\ , andGraphPropPredDataset.NodePropPredDataset:.. code-block:: pythoncoding=utf-8from ogb_lite.nodeproppred import NodePropPredDatasetdataset = NodePropPredDataset(name="ogbn-proteins")split_idx = dataset.get_idx_split()
train_idx, valid_idx, test_idx = split_idx["train"], split_idx["valid"], split_idx["test"]
graph, label = dataset[0] # graph: library-agnostic graph objectprint(graph, label)
print(train_idx, valid_idx, test_idx)LinkPropPredDataset:.. code-block:: pythoncoding=utf-8from ogb_lite.linkproppred import LinkPropPredDatasetdataset = LinkPropPredDataset(name="ogbl-ppa")split_edge = dataset.get_edge_split()
train_edge, valid_edge, test_edge = split_edge["train"], split_edge["valid"], split_edge["test"]
graph = dataset[0]  # graph: library-agnostic graph objectprint(graph)
print(train_edge, valid_edge, test_edge)GraphPropPredDataset:.. code-block:: pythoncoding=utf-8from ogb_lite.graphproppred import GraphPropPredDatasetdataset = GraphPropPredDataset(name="ogbg-molhiv")split_idx = dataset.get_idx_split()
train_idx, valid_idx, test_idx = split_idx["train"], split_idx["valid"], split_idx["test"]graph, label = dataset[0]  # graph: library-agnostic graph object
print(graph, label)
print(train_idx, valid_idx, test_idx)Citing OGBIf you use OGB datasets in your work, please cite the OGB paper (Bibtex below)... code-block:: HTML@article{hu2020ogb,
title={Open Graph Benchmark: Datasets for Machine Learning on Graphs},
author={Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec},
journal={arXiv preprint arXiv:2005.00687},
year={2020}
}
Package: ogcFeatureApiCollectionDownloader
ogcFeatureApiCollectionDownloaderA python package to automatically download data from an OGC Feature API Collection.Installpip install ogcFeatureApiCollectionDownloaderHow to useimport os

from ogcFeatureApiCollectionDownloader import downloader

download_location = f"{os.getcwd()}/downloads"

downloader.DownloadCollection(
    url="https://demo.pygeoapi.io/stable/collections/lakes/"
).download(
    download_path=download_location
)