Saravanan666/pypi-org huggingface dataset:
Package: blitzcrop
blitzcropGUI for interactivebatch image cropping:Drag along the diagonal of the image fromupper lefttolower rightcorner and release the mouse button.Move the mouse to the upper right corner and click.Accept or reject the cropped image in the dialog popping up.FeaturesBatch crop large amounts of images in a short amount of timeDrag and click to crop an imageCroprotatedimagesPass images via command lineNavigate between images usingleft arrow/right arroworA/DAccept cropped images byEnterorSpaceand reject them byEscInstallYou can installblitzcropusingpipwithpip3installblitzcropAlternatively, you can downloadblitzcrop.pyand then run it usingpython3withpython3blitzcrop.pyIn this case, you need to ensure thatPillowandtkinter(includingImageTk) is installed on your system and available topython3. If you work on an Ubuntu-based Linux distribution, you may achieve that by means ofsudoaptinstallpython3-tkpython3-pilpython3-pil.imagetkHistory0.3.0 (2022-10-17)Abort rectangle selection by clicking with therightmouse button or by pressingEscSpecify file name template by-f/--file-name-templatewith placeholdersimageandnowSpecify image quality by-q/--qualitySpecify-m/--forget-metadatato prevent storing original image metadata in cropped image; otherwise metadata will be preserved (including original image resolution)0.2.1 (2022-10-10)Support Pillow < 9.10 by monkey-patchingImage.Resampling0.2.0 (2022-10-09)Implement core cropping interaction with drag + clickSupport multiple images via command line argumentsSupport basic keybindings for image navigation and crop accept / reject0.1.0 (2022-04-03)Created usingcookiecutter-pyscriptCreditsMain developer is luphordluphord@protonmail.com.cookiecutter-pyscriptis used as project template.History0.1.0 (2022-04-03)Initial release.
Package: blitzcurve
Data analysis of time-resolved fluorescence anisotropy measurements (TRAMs).TRAMs are state-of-the-art techniques that can be used to analyse protein function and interaction.Why use TRAM techniques?To measure molecule rotation speeds (e.g. protein size, structure, ligand binding).To measure oligomerisation properties, via Foerster Resonance Energy Transfer (FRET) between two fluorescent molecules.What is blitzcurve for?fitting curves to experimental TRAM dataextracting useful fit parameterscomparing samplesHow does the experiment work?excitation of fluorescent moleculesmeasurement of the depolorisation of the emitted light (polarisation / anisotropy)time-resolved methods: pulse excitation, and measurement of the change in anisotropy over time in nanosecondsAnalysis methodsappropriate fitting methods are still under developmentcurrent input: csv with anisotropy and time (ns) valuescurrent fitting methods for anisotropy vs timeSavitzky Golay fit to all raw dataExponential fit to initial decay dataExponential fit to final decay datakey measured parameters:r_inf (predicted anisotropy at an infinite range in time)r_max (maximum anisotropy measured at any timepoint)Installationpip install blitzcurveBlitzcurve should be compatable withAnaconda python3.x or any scientific python packageUsageimportblitzcurve# define data directory with csv filesdata_dir=r"D:\data\20180229_TRdata"# OPTIONAL: define which data files will be analysedfile_list=["10nM-FGC1-2min_aniso.txt","10nM-FGC2-2min_aniso.txt"]# run blitzcurve function to fit curves to individual samplesblitzcurve.run_fit(data_dir,figs_to_plot=file_list)# setup a dictionary to shorten long sample namesname_dict={"10nM-FGC1-2min_aniso.txt":"FGC1","10nM-FGC2-2min_aniso.txt":"FGC2","10nM-FGC3-2min_aniso.txt":"FGC3"}# run blitzcurve function to compare curves and parameters for multiple samplesblitzcurve.run_compare(data_dir,name_dict=name_dict)ContributeCollaborators and pull requests are welcome. Send us an email.LicenseThis python package is released under the permissive MIT license.ContactContact details are available at the staff pages ofMark TeeseorPhilipp Heckmeierwithin theLangosch labof the Technical University of Munich.Examplesfit to obtain r_maxfit to obtain r_infbarchart comparing r_maxbarchart comparing r_inflinechart comparing fit to full data for three sampleslinechart comparing fit to r_inf for three samples
Package: blitzdb
Blitz is a document-oriented database toolkit for Python that is backend-agnostic.It comes with a flat-file database for JSON documents and provides MongoDB-like querying capabilities.Key FeaturesDocument-based, object-oriented interface.Powerful and rich querying language.Deep document indexes on arbitrary fields.Compressed storage of documents.Support for multiple backends (e.g. file-based storage, MongoDB).Support for database transactions (currently only for the file-based backend).DocumentationAn extensive documentation, including tutorials and installation instructions is available onReadTheDocs.Source CodeThe source code is available onGitHub.Isssue TrackerIf you should encounter any problems when using BlitzDB, please feel free tosubmit an issueon Github.Changelog0.4.4: SQL backend: Do not coerce server_default values via a CAST, as this can cause incompatibilities.0.4.3: Many small improvements to the SQL backend.0.3.3: Be more robust against corrupted data for foreign key objects. Fix problem with intersection of query sets in SQL backend.0.3.2: Give the user more control over cascading deletes for foreign keys and M2M objects in the SQL backend.0.3.1: Made intersect statement more efficient (and avoid using CTEs for that).0.3.0: Fully functionaly SQL backend.0.2.12: Added support for proper attribute iteration toDocument.0.2.11: Allow setting thecollectionparameter through aDocument.Metaattribute.0.2.10: Bugfix-Release: Fix Python 3 compatibility issue.0.2.9: Bugfix-Release: Fix serialization problem with file backend.0.2.8: Addedget,has_keyandclearmethods toDocumentclass0.2.7: Fixed problem with __unicode__ function in Python 3.0.2.6: Bugfix-Release: Fixed an issue with the $exists operator for the file backend.0.2.5: Bugfix-Release0.2.4: Added support for projections and update operations to the MongoDB backend.0.2.3: Bugfix-Release: Fixed bug in transaction data caching in MongoDB backend.0.2.2: Fix for slice operators in MongoDB backend.0.2.1: Better tests.0.2.0: Support for including additional information in DB references. Support for accessing document attributes as dictionary items.Added $regex parameter that allows to use regular expressions in queries.0.1.5: MongoDB backend now supports database transactions. Database operations are now read-isolated by default, i.e.uncommitted operations will not affect database queries before they are committed.0.1.4: Improved indexing of objects for the file backend, added support for automatic serialization/deserializationof object attributes when adding keys to or querying an index.0.1.3: Sorting of query sets is now supported (still experimental)0.1.2: Small bugfixes, BlitzDB version number now contained in DB config dict0.1.1: BlitzDB is now Python3 compatible (thanks to David Koblas)
Package: blitzly
blitzly ⚡️Lightning-fast way to get plots with PlotlyIntroduction 🎉Plotly is great and powerful. But with great power comes great responsibility 🕸. And sometimes you just want to get a plot up and running as fast as possible. That's where blitzly ⚡️ comes in. It provides a set of functions that allow you to create plots with Plotly in a lightning-fast way. It's not meant to replace Plotly, but rather to complement it.Check out some examples in theJupyter notebook.Install the package 📦If you are usingpip, you can install the package with the following command:pipinstallblitzlyIf you are usingPoetry, you can install the package with the following command:poetryaddblitzlyinstalling dependencies 🧑‍🔧Withpip:pipinstall-rrequirements.txtWithPoetry:poetryinstallAvailable plots (so far 🚀)ModuleMethodDescriptionbarmodel_feature_importancesCreates a bar chart with the feature importance of a model.barmulti_chartCreates a bar chart with multiple groups.dumbbellsimple_dumbbellPlots a dumbbell plot. This can be used to compare two columns of data to visualize changes.histogramsimple_histogramPlots a histogram with one ore more distributions.matrixbinary_confusion_matrixPlots a confusion matrix for binary classification data.matrixcramers_v_corr_matrixCramer's V correlation for categorical features.matrixpearson_corr_matrixPlots a Pearson product-moment correlation coefficients matrix.scatterscatter_matrixPlots a scatter matrix.scattermulti_scatterCreate a multi scatter plot. It can be used to visualize the relationship between multiple variables from the same Pandas DataFrame.scatterdimensionality_reductionCreates a plot to visualize higher dimensionality reduced data using matrix decompositionSubplots 👩‍👩‍👧‍👦ModuleMethodDescriptionsubplotsmake_subplotsCreate subplots using figure objects created with any of the above available plots.Usage 🤌Here are some examples. You can also open theplayground notebook📒.dimensionality_reduction:fromblitzly.plots.scatterimportdimensionality_reductionimportplotly.expressaspxdf=px.data.iris()dimensionality_reduction(df,n_components=2,target_column="species",reduction_funcs=["PCA","TNSE"],)Gives you this:multi_bar:fromblitzly.plots.barimportmulti_barimportnumpyasnpdata=np.array([[8,3,6],[9,7,5]])error_array=np.array([[0.1,0.2,0.3],[0.4,0.5,0.6]])multi_bar(data,x_labels=["Vienna","Berlin","Lisbon"],group_labels=["Personal rating","Global rating"],errors=error_array,title="City ratings 🏙",mark_x_labels=["Lisbon"],write_html_path="see_the_blitz.html",)Gives you this:scatter matrix:fromblitzly.plots.scatterimportscatter_matriximportnumpyasnpimportpandasaspdfoo=np.random.randn(1000)bar=np.random.randn(1000)+1blitz=np.random.randint(2,size=1000)licht=np.random.randint(2,size=1000)data=np.array([foo,bar,blitz,licht])df=pd.DataFrame(data.T,columns=["foo","bar","blitz","licht"])scatter_matrix(df,dimensions=["foo","bar","blitz"],color_dim=df["licht"],title="My first scatter matrix 🙃",show_upper_half=True,diagonal_visible=False,marker_color_scale="Rainbow",marker_line_color="blue",size=(500,500),)Gives you this:Contributing 👩‍💻Please check out theguideon how to contribute to this project.
Package: blitzmanager
BlitzManagerBlitzManager is a simple adjustable manager that uses package managers for C/C++ dependencies. It can also
be used to create CMake project templates.Quick StartHere is a simple example for installing dependencies usingvcpkg.fromblitzmanagerimportBlitzManager,Path,SupportedManagersimportoscwd=os.path.dirname(os.path.realpath(__file__))manager_output=Path(cwd,"out")build_output=Path(cwd,"out","dependencies")install_path=Path(cwd,"out","install")flags={"--output_dir":{"required":False,"default":None,"type":str,"help":"Chose another output directory."}}manager=BlitzManager()manager.add_flags(flags)manager.parse_arguments()ifmanager["output_dir"]isnotNone:manager_output=Path(manager["output_dir"])assertnotmanager_output.is_file()assertmanager_output.is_abs(check_if_exists=False)build_output=Path(manager_output.path,"dependencies")install_path=Path(manager_output.path,"install")manager.initialize(manager_output,build_output,install_path,SupportedManagers.VCPKG)manager.initialize_managers()manager.build_via_package_manager(["zlib","sqlite3"])manager.build_dependencies()DisclaimerThis tool is still under development and should be used with caution.
Package: blitz-work
Blitz WorkBlitz Work is a Django-based framework for rapid application developmentHow to useAdd blitz_work to installed apps in settings.py.INSTALLED_APPS=[...,...,'blitz_work',]Create the models.fromdjango.dbimportmodelsclassAuthor(models.Model):name=models.CharField(verbose_name="Name",max_length=255)birth_date=models.DateField(verbose_name="Birth date")classMeta:verbose_name="Author"verbose_name_plural="Authors"def__str__(self):returnself.nameclassBook(models.Model):title=models.CharField(verbose_name="Title",max_length=255)publication_date=models.DateField(verbose_name="Publication date")authors=models.ManyToManyField(Author,verbose_name="Authors")classMeta:verbose_name="Book"verbose_name_plural="Books"def__str__(self):returnself.titleCreate the template.{% extends 'blitz_base_offline.html' %}
    {% block main %}&lt;nav class="navbar navbar-expand-lg navbar-light bg-light"&gt;&lt;a class="navbar-brand" href="#"&gt;Test&lt;/a&gt;&lt;button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNavDropdown" aria-controls="navbarNavDropdown" aria-expanded="false" aria-label="Toggle navigation"&gt;&lt;span class="navbar-toggler-icon"&gt;&lt;/span&gt;&lt;/button&gt;&lt;div class="collapse navbar-collapse" id="navbarNavDropdown"&gt;&lt;ul class="navbar-nav"&gt;&lt;li class="nav-item"&gt;&lt;a class="nav-link" href="{% url 'book/view' %}"&gt;Libros&lt;/a&gt;&lt;/li&gt;&lt;li class="nav-item"&gt;&lt;a class="nav-link" href="{% url 'author/view' %}"&gt;Autores&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;/div&gt;&lt;/nav&gt;{% block content %}{% endblock %}
    {% endblock %}Create the views.fromBook.modelsimportAuthor,Bookfromblitz_work.blitzcrudimportBlitzCRUDclassBookCRUD(BlitzCRUD):show_title=Trueshow_caption=Falsecaption_is_title=Trueextend_template="base.html"data=BookclassAuthorCRUD(BlitzCRUD):show_title=Trueshow_caption=Falsecaption_is_title=Trueextend_template="base.html"data=AuthorInclude the URLs.fromapp.viewsimportAuthorCRUD,BookCRUDfromdjango.urlsimportpath,includefromblitz_work.blitzcrudimportget_urlsurlpatterns=[path('book/',include(get_urls(BookCRUD,"book"))),path('author/',include(get_urls(AuthorCRUD,"author"))),]More helpInclude Blitz Work help urls in urls.pyfromblitz_work.urlsimporturlpatternsurlpatterns=[path('',include(urlpatterns)),]Run the server.pythonmanage.pyrunserverlocalhost:8000Go to the urlblitz-doc-en/orblitz-doc-es/
Package: blive
B 站弹幕监听框架特点简单，只需房间号即可监听异步，io 不阻塞，及时获取消息B 站直播弹幕 websocket 协议分析PROTOCOL 分析快速开始安装pip install blive创建 appfrombliveimportBLiverapp=BLiver(123)#123为房间号创建处理器frombliveimportBLiver,Events,BLiverCtxfromblive.msgimportDanMuMsgapp=BLiver(123)# 标记该方法监听弹幕消息,更多消息类型请参考 Events 类源代码@app.on(Events.DANMU_MSG)asyncdeflisten_danmu(ctx:BLiverCtx):danmu=DanMuMsg(ctx.body)#ctx.body 套上相应的消息操作类即可得到消息的基本内容,也可直接操作 ctx.bodyprint(danmu.content)print(danmu.sender)print(danmu.timestamp)运行frombliveimportBLiver,Events,BLiverCtxfromblive.msgimportDanMuMsgapp=BLiver(123)@app.on(Events.DANMU_MSG)asyncdeflisten_danmu(ctx:BLiverCtx):danmu=DanMuMsg(ctx.body)print(danmu.content)print(danmu.sender)print(danmu.timestamp)app.run()# 运行app!同时监听多个直播间importasynciofrombliveimportBLiver,Events,BLiverCtxfromblive.msgimportDanMuMsg# 定义弹幕事件handlerasyncdeflisten(ctx:BLiverCtx):danmu=DanMuMsg(ctx.body)print(f'\n{danmu.sender.name}({danmu.sender.medal.medal_name}:{danmu.sender.medal.medal_level}): "{danmu.content}"\n')asyncdefmain():# 两个直播间ke=BLiver(605)azi=BLiver(510)# 注册handlerke.on(Events.DANMU_MSG,listen)azi.on(Events.DANMU_MSG,listen)# 以异步task的形式运行task1=ke.run_as_task()task2=azi.run_as_task()# await 两个任务awaitasyncio.gather(*[task1,task2])if__name__=="__main__":loop=asyncio.get_event_loop()loop.run_until_complete(main())作为协议解析工具在其他地方使用（伪代码）fromblive.coreimportBWS_MsgPackagepackman=BWS_MsgPackage()# 实例化一个消息包处理器whileTrue:data=ws.receive()# 当收到消息时msg=packman.unpack(data)# 使用packman解析消息,返回一个形如 [(header,body), (header,body), ... ] 数组print(msg)与 fastapi (其他asyncio生态框架) 配合使用fromfastapiimportFastAPIfrombliveimportBLiver,Eventsfromblive.msgimportDanMuMsgapp=FastAPI()BLIVER_POOL={}# 定义弹幕事件handlerasyncdefhandler(ctx):danmu=DanMuMsg(ctx.body)print(f'\n{danmu.sender.name}({danmu.sender.medal.medal_name}:{danmu.sender.medal.medal_level}): "{danmu.content}"\n')defcreate_bliver(roomid):b=BLiver(roomid)b.on(Events.DANMU_MSG,handler)returnb@app.get("/create")asyncdefcreate_new_bliver(roomid:int):room=BLIVER_POOL.get(roomid,None)ifnotroom:b=create_bliver(roomid)BLIVER_POOL[roomid]=b.run_as_task()# 启动监听return{"msg":"创建一个新直播间弹幕监听成功"}@app.get("/del")asyncdefrm_bliver(roomid:int):room=BLIVER_POOL.get(roomid,None)ifroom:room.cancel()BLIVER_POOL.pop(roomid)return{"msg":"移除直播间弹幕监听成功"}@app.get("/show")asyncdefshow():returnlist(BLIVER_POOL.keys())项目简介blive 文件夹为框架代码core.py 为B站ws直播聊天室协议包处理的核心代码eeframework.py 为框架代码msg.py 为消息操作类代码example/app.py
以框架形式运行例子example/multi_room.py
同时监听多个直播间的实现example/with_fastapi.py
与fastapi 配合使用的例子TODO更多的消息操作类（欢迎各位提pr）尝试加入中间件架构（目前感觉需求不大）
Package: blivedm
blivedmPython获取bilibili直播弹幕的库，使用WebSocket协议协议解释（有点过时了，总体是没错的）基于本库开发的一个应用：blivechat使用说明需要Python 3.8及以上版本安装依赖pipinstall-rrequirements.txt例程看sample.py
Package: blivet
Blivet is a python module for system storage configuration.CI statusLicenseSeeCOPYINGInstallationFrom Fedora repositoriesBlivet is available in Fedora repositories. You can install it using# dnf install python3-blivetDaily builds for FedoraDaily builds of Blivet are available in@storage/blivet-dailyCopr repository.
You can enable it using# dnf copr enable @storage/blivet-dailyDaily builds oflibblockdevandlibbytesizeare also in this repo.OBS repository for Ubuntu and DebianPackages for Debian (testing and unstable) and Ubuntu (19.04 and newer) are available through the Open Build Service.
Instructions for adding the repository are availablehere.Copr repository for openSUSE, Mageia and OpenMandrivaPackages for openSUSE Tumbleweed, Mageia (8 and newer) and OpenMandriva (Cooker and Rolling) are available in ourblivet-stable Copr repository.PyPIBlivet is also available through thePython Package Index.
You can install it using$ pip3 install blivetBlivet depends on some C libraries that are not available on PyPI so you need to install these manually.The main dependencies includelibblockdev,libbytesize, parted and their Python bindings.
These libraries should be available on most distributions in the standard repositories.To install these dependencies use following commands:On Fedora and RHEL/CentOS based distributions:# dnf install python3-blockdev libblockdev-plugins-all python3-bytesize libbytesize python3-pyparted parted libselinux-python3On Debian and Ubuntu based distributions:# apt-get install python3-blockdev python3-bytesize python3-parted python3-selinux gir1.2-blockdev-3.0 libblockdev-lvm3 libblockdev-btrfs3 libblockdev-swap3 libblockdev-loop3 libblockdev-crypto3 libblockdev-mpath3 libblockdev-dm3 libblockdev-mdraid3 libblockdev-fs3DevelopmentSeeCONTRIBUTINGDeveloper documentation is available on ourwebsiteor onRead the Docs.Additional information about the release process, roadmap and other development-related materials are also available in theGitHub Wiki.LocalizationBug reportingBugs should be reported tobugzilla.redhat.com.You can also report bug using theGitHub issues.
Package: blivomdeler-api
Blivomdeler-APIAn API wrapper for the danish Blivomdeler site:https://blivomdeler.nuThe words "Bliv Omdeler" in danish translates to "Become Distributor", as in a newpaper distributor.Changelog0.1.0First releaseAdded main classAdded function to get earned pointsAdded login functionalityAdded logout functionality0.2.0Added classes for some function returnsAdded some more exception handlingAdded function to get giftshop itemsAdded function to get history of points collected, earned or spentAdded function to get information about the current userAdded function to change information about the current userRemoved option to login when creating an instance of the APISession class, use APISession.login() after creating an instance.Removed APISession.earned_points property, use APISession.get_earned_points() instead.0.3.0Added function to download a route map
Package: blkinfo
blkinfo - Block Devices InformationLibraryAboutblkinfo is a python library to list information about all available or the specified block devices.It bases onlsblkcommand line tool, provided byutil-linux, in addition, it collects information about block
devices, using/sys/block,/sys/devices,/procdirectories.The main goal is to provide Python's binding tolsblk. Old versions oflsblk, provided byutil-linux-2.23.2on
Red Hat Enterprise Linux 7 and Centos 7 (and earlier versions) do not contain an option to output to JSON format.Additional features tolsblk:information about iSCSI target IP address and port number was addedblock device usage statisticsInstallationInstall python's package from PyPI repository usingpiputil (default is Python 3):pip install blkinfo

pip2 install blkinfoInstall rpm package from Copr (experimental).dnf copr enable galt/blkinfo

dnf install python2-blkinfo

dnf install python3-blkinfoUsage exampleInformation about all available block devices:importjsonfromblkinfoimportBlkDiskInfomyblkd=BlkDiskInfo()all_my_disks=myblkd.get_disks()json_output=json.dumps(all_my_disks)print(json_output)Passing filters as an argument to the get_disks() method:importjsonfromblkinfoimportBlkDiskInfomyblkd=BlkDiskInfo()filters={'tran':'iscsi'}my_filtered_disks=myblkd.get_disks(filters)json_output=json.dumps(my_filtered_disks)print(json_output)Filtersname:      device namename_glob:  globex for a device namekname:      internal kernel device namesize:       size of the devicemin_size:   min size for a devicemax_size:   max size for a devicemaj:min     major and minor device numbersra:         read-ahead device (e.g. type)ro:         read-only devicerm:         removable devicehotplug:    removable or hotplug device (usb, pcmcia, ...)model:      device identifier, including vendor nameserial:     disk serial numberstate:      state of the devicehctl:       string with 'Host:Channel:Target:Lun' string (for SCSI)rota:       rotational devicetran:       device transport typeiscsi_target_ip:      used together with 'tran': 'iscsi'iscsi_target_port:    used together with 'tran': 'iscsi'is_mounted:           does a disk have mounted partitionRoadmapNowblkinfolibrary is usinglsblkcommand line tool directly.
The good idea is to createlsblkcore library in C and just add bindings in Python.https://github.com/karelzak/util-linux/issues/839NOTE:If you have got a question or suggestion, please, file an issue on
GitHub or submit a PR.https://github.com/grinrag/blkinfo
Package: blkmautrix
A Python 3.6+ asyncio Matrix framework.Components:Basic HTTP request sender (mautrix.api)Client APIendpoints as functions (mautrix.client.api)Medium-level application service framework (mautrix.appservice)Basic transaction and user/alias query support (based on Cadair’spython-appservice-framework)Basic room state storageIntent wrapper around the client API functions (design based on matrix-appservice-bridge)Soon™: High-level bridging framework (mautrix.bridge).High-level client framework (mautrix.client). Currently only has an event handling helper.
Package: blkmenu
blkmenuTiny curses wrapper aroundlsblkandudisksctl.InstallationArch users can simply run the following command from the project directorymakepkg -siAnyone else can install the program withpippip install --user blkmenuOr by running the following commands from the project directoryinstall -Dm755 blkmenu "$HOME/.local/bin/blkmenu"
install -Dm644 blkmenu.1 "$HOME/.local/share/man/man1/blkmenu.1"UsageType?once you startblkmenufor a quick overview of all predefined key bindings.An overview of all command line options can be foundhereor by runningman blkmenu.Runblkmenu --helpfor a quick help.LicenseSeeLICENSE.txt.
Package: blk-utils
BLK UTILSA small utility library for my most commonly used functions across projects.Installationpip install blk-utilsExample Usagefrom blk_utils import get_relative_project_dir, cprint, ...



repo_name = 'my_repo'

project_dir = get_relative_project_dir(repo_name, partial=True)

data_dir = project_dir / 'data'



data_filepath = data_dir / 'my_table_data.csv'

df = pd.read_csv(data_filepath)

cprint(df)
Package: bllog
BLLog - A simple and easy-to-use loggerThe goal of the project was to create a very simple and easy to use logger
that can log both to console and to a file. It has a one-liner initialization but
also can be configured in various ways if you need to. Console color support is available
on Windows and Linux usingtermcolorandcoloramabut can be disabled.Feel free to make an issue or pull request on GitHub or even make a fork to add
more functionality.