Saravanan666/pypi-org huggingface dataset:
Package: s3-browser-cli
S3 Browser基于Streamlit开发，可在线查看S3存储内容的工具。特性文件夹/文件浏览丰富的文件查看模式针对JSONL格式优化，可按行预览前1MB的内容存在图片的路径，支持预览查看图片支持配置多个S3服务，灵活切换支持通过浏览器下载文件注：对象存储没有文件夹概念，仅为模拟文件系统方式进行查看。出于性能考虑，一个文件夹仅支持查看前1000个文件。使用编写配置文件secrets.toml，多套S3服务配置[S3_Servers][S3_Servers.S1]AK="<Your S3 AK>"SK="<Your S3 SK>"ENDPOINT_URL="<Your S3 Endpoint Url>"[S3_Servers.S2]AK="<Your S3 AK>"SK="<Your S3 SK>"ENDPOINT_URL="<Your S3 Endpoint Url>"单个S3也可以配置为[S3]
AK = "<Your S3 AK>"
SK = "<Your S3 SK>"
ENDPOINT_URL = "<Your S3 Endpoint Url>"启动服务 - docker启动$dockerrun-p8501:8501-v$(pwd)/secrets.toml:/s3_browser/.streamlit/secrets.tomlzhchbin/s3_browser:latest在浏览器中访问：http://127.0.0.1:8501您也可以使用pip进行安装，secrets.toml配置文件需要存放在当前运行目录.streamlit/secrets.toml或者HOME目录下~/.streamlit/secrets.toml$pipinstalls3-browser-cli
$s3_browser--help

Usage:s3_browser[OPTIONS]Options:-p,--portINTEGERSpecifyalternateport[default:8501]-a,--addressTEXTspecifyalternatebindaddress(default:127.0.0.1)--helpShowthismessageandexit.源码运行/开发下载仓库$gitclonehttps://github.com/opendatalab/s3_browser.gitPython版本要求：^3.10，建议使用虚拟环境编写配置文件.streamlit/secrets.toml方式一：Poetry安装poetry:https://python-poetry.org/安装依赖并运行$poetryinstall
$poetryrunstreamlitruns3_browser/Welcome.py方式二：pip安装依赖$pipinstall-rrequirements.txt运行$streamlitruns3_browser/Welcome.py作者@jinzhenj@zhchbin
Package: s3cache
S3 Cache for PythonNiall McCarrollwrote a neat littleAWS
S3 cacheon his
blog that I found really useful, but could not find onPyPI, so here it is in a refactored
form as a public service.Instructionsfrom s3cache import S3Cache

s3 = S3Cache("/tmp", "t13d-misc")
s3.connect()
s3.create_bucket()
assert(s3.bucket_exists())

s3.set_verbosity(True)
s3.set_caching(True)

f = s3.open("/tmp/world.txt", "w")
f.write("Hello")
f.close()

f = s3.open("/tmp/world.txt", "a")
f.write(" World")
f.close()

f2 = s3.open("/tmp/world.txt", "r")
f2.close()

assert(s3.object_exists("/tmp/world.txt"))
s3.remove_object("/tmp/world.txt")ReferencesA local file cache for amazon S3 using python and
boto
Package: s3-cas
S3 Content-Addressable StorageStore files in S3 indexed by their SHA256 hash instead of by filename.$ echo 'Hello World!' > foo
$ cp foo foo2
$ cat test.py
import s3_cas
c = s3_cas.S3CasClient("my-bucket", "blobs")
c.upload_file("foo")
c.upload_file("foo2")
$ python test.py
INFO:s3cas:Uploaded file to s3://my-bucket/blobs/03ba204e50d126e4674c005e04d82e84c21366780af1f43bd54a37816b6ab340
INFO:s3cas:File already exists with hash 03ba204e50d126e4674c005e04d82e84c21366780af1f43bd54a37816b6ab340, name foo, not uploading.
Package: s3cat
s3cat lets you fetch all files under a certain directory (either raw or gzipped) into stdout.Installing:sudo pip install s3catUsage:usage: s3cat [-h] [-r RETRIES] [-w WORKERS] urlpositional arguments:url                   S3 URL or local file pathoptional arguments:-h,--helpshow this help message and exit-rRETRIES,--retriesRETRIESNumber of attempts-wWORKERS,--workersWORKERSNumber of concurrent downloadsAuthor:Ron Reiter <ron@crosswiselabs.com>
Package: s3-client-lib
S3 client libLibrary for client calls to S3.InstallingInstallbotos3system packagesBuild & Install s3-client-lib with poetry:pipinstallpoetrygitclonehttps://github.com/CESNET/s3-client-libcds3-client-libpoetrybuildcddisttar-xvfs3-client-lib-0.1.0.tar.gzpipinstall-es3-client-lib-0.1.0/
Package: s3clumper
Makes a tarball (optionally compressed with gzip) of the contents of
an S3 prefix (preserving interior paths and filenames), posts the
tarball to a stated S3 URL and optionally deletes the source files.s3clumper: Aggregate S3 prefixes into tarballs in S3

Usage: s3clumper {{arguments}} {{options}}

Arguments:
  from [text]  S3 URL prefix to clump
  to [text]    S3 URL for target clump

Options:
  -h, --help      Show this help message and exit
  -H, --HELP      Help for all sub-commands
  -c, --check     Don't check for target (may over-write)
  -C, --nocolour  Suppress colours in reports
  -D, --debug     Enable debug logging
  -d, --delete    Don't delete source files
  -q, --quiet     Be quiet, be vewy vewy quiet
  -v, --verbose   Verbose output
  -V, --version   Report installed version
  -z, --compress  Don't compress the targetExample:$ s3clumper s3://bucket1/data/ s3://bucket2/archive/logs-20170302.tar.gz
Fetching |################################| 55/55
Sending |################################| 100/100
Deleting |################################| 55/55
Package: s3cmd
S3cmd lets you copy files from/to Amazon S3
(Simple Storage Service) using a simple to use
command line client. Supports rsync-like backup,
GPG encryption, and more. Also supports management
of Amazon’s CloudFront content delivery network.Authors:Florent Viard <florent@sodria.com>Michal Ludvig  <michal@logix.cz>Matt Domsch (github.com/mdomsch)
Package: s3-concat
Python S3 ConcatS3 Concat is used to concatenate many small files in an s3 bucket into fewer larger files.Installpip install s3-concatUsageCommand Line$ s3-concat -hImportfroms3_concatimportS3Concatbucket='YOUR_BUCKET_NAME'path_to_concat='PATH_TO_FILES_TO_CONCAT'concatenated_file='FILE_TO_SAVE_TO.json'# Setting this to a size will always add a part number at the end of the file namemin_file_size='50MB'# ex: FILE_TO_SAVE_TO-1.json, FILE_TO_SAVE_TO-2.json, ...# Setting this to None will concat all files into a single file# min_file_size = None  ex: FILE_TO_SAVE_TO.json# Init the jobjob=S3Concat(bucket,concatenated_file,min_file_size,content_type='application/json',#  session=boto3.session.Session(),  # For custom aws session# s3_client_kwargs={}  # Use to pass arguments allowed by the s3 client: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html)# Add files, can call multiple times to add files from other directoriesjob.add_files(path_to_concat)# Add a single file at a timejob.add_file('some/file_key.json')# Only use small_parts_threads if you need to. See Advanced Usage section below.job.concat(small_parts_threads=4,main_threads=2)Advanced UsageDepending on your use case, you may want to use more threads then just 1.main_threadsis the number of threads to use when uploading files to s3. This will help when there are a lot of files that are already over themin_file_sizethat is setsmall_parts_threadsis only used when the files you are trying to concat are less then 5MB. These are spawned frominsideof themain_threads. Due to the limitations of the s3 multipart_upload api (seeLimitationsbelow) any files less then 5MB need to be downloaded locally, concated together, then re uploaded. By setting this thread count it will download the parts in parallel for faster creation of the concatenation process.The values set for these arguments depends on your use case and the system you are running this on.LimitationsThis uses the multipart upload of s3 and its limits arehttps://docs.aws.amazon.com/AmazonS3/latest/dev/qfacts.html
Package: s3-connection
s3_connectionDescriptionA package that allows an easy connection to be made to anAWS S3bucket, provided a validAWS Access Key & AWS Secret Keyare given (if no credentials are provided then only public buckets can be accessed). The package contains a class which stores the keys provided, and allows the user to read/write certain file formats to/from s3 buckets, through the use of class methods.This package is essentially a wrapper for thes3fs package. It was created to be used as a subpackage in a wider project - PSUSANNX.Package Functionsread_csv_from_s3()write_csv_to_s3()read_json_from_s3()write_json_to_s3()read_h5_from_s3()write_h5_to_s3()read_pkl_from_s3()write_pkl_to_s3()Installationpipinstalls3_connectionUsage# Import the class object from the packagefroms3_connection.s3_conn_classimportS3Connection# Get some info about the class objecthelpS3ConnectionOnce the class has been imported and you've read the help, you can create an instance of the class to allow you to interact with an s3 bucket in your aws account. Make sure you have the AWS Access key & the AWS secret key at hand.# Create an instance of the class with AWS credentialss3_conn=S3Connection(aws_access_key='<AWS-ACCESS-KEY>',aws_secret_key='<AWS-SECRET-KEY>')The s3_conn object can now be used to call the functions to read/write to s3 buckets.If you dont have access or secret keys and you want to access objects inpublic buckets, all you need to do is instantiate an instance of the class with no arguments, like this.# Create an instance of the class with no credentialss3_conn=S3Connection()Theread_from_s3functionsThe read___from_s3 functions just take the bucket name & object name as arguments then return the object.# Use the s3_conn to read a csv from a bucketpandas_df=s3_conn.read_csv_from_s3(bucket_name="<bucket-name>",object_name="<path/to/file/within/bucket.csv>")Thewrite_to_s3functionsThe write___to_s3 functions take the bucket name, object name & the data as arguments and return nothing.If you already have a dataframe stored in a variable called existing_df then you can put it into an s3 bucket with the following function (index=False is automatically applied).# Put the existing_df dataframe into the s3 bucket as a csv files3_conn.write_csv_to_s3(bucket_name="<bucket-name>",object_name="<path/to/save/file.csv>",data=existing_df)NotesThe package is quite restricted in what it can do, but it only needs to do things that are required by the parent project so there won't be much development.A potential new feature to add to the package would be the ability to manage S3 resources, like create/delete buckets & objects from S3 from within the package.
Package: s3-consistency-checker
aws s3 syncis great!But if you are truly paranoid about your precious files safety,
it’s always better to double check what was uploaded to S3 before deleting
them from your local file system.This tool does exactly that:List recursively your local filesAsk S3 for their sizes and ETagsCheck this against locally computed ETagsUsage$times3-consistency-checker/data/foos3://bucketname/foo2017/10/14 16:30:58.729 INFO Comparing 2093 files from /data/foo with s3://bucketname/foo
2017/10/14 17:43:18.222 INFO success=2093 errors=0 files=2093 bytes=1.3TiB

real    72m20.097s
user    55m6.975s
sys     778m45.112s$times3-consistency-checker/data/bars3://bucketname/baz2017/10/14 18:47:08.620 INFO Comparing 26531 files from /data/bar with s3://bucketname/baz
2017/10/14 19:21:48.425 INFO success=26531 errors=0 files=26531 bytes=220.1GiB

real    34m42.023s
user    40m22.292s
sys     33m57.729s$times3-consistency-checker/data/foobars3://bucketname/foobar2017/10/15 02:11:00.904 INFO Comparing 11224 files from /data/foobar with s3://bucketname/foobar
2017/10/15 02:25:18.397 INFO success=11224 errors=0 files=11224 bytes=84.8GiB

real    14m18.873s
user    17m3.899s
sys     10m33.841sInternalsThis tool is designed to process a lot of big files as quickly as possible.
It uses thesplitcommand to split big files in chunks,
stores them in/dev/shm,
then computes their checksums using themd5sumcommand.
It does this in parallel using separate processes and threads to drive them.Installation$pipinstalls3-consistency-checkerRequirementsPython 3.xboto3coreutils: md5sum, split
Package: s3cps3
## 命令功能
#### 实现数据桶到数据桶之间的数据传输功能，无需先下载到本地再上传；
#### 考虑到可能遇到大批量小文件传输的需求，本包可实现通过扫描分割大小文件，并将大文件通过aws包的cp命令传输，为小文件分配python多线程传输，提高传输效率;
#### 考虑到可能遇到各种因素导致传输中断，在中断后为了节省时间可以通过读取上一次扫描后生成的大小文件列表，跳过重新扫描这一步骤；## 安装
### linux命令
s3cps3及其依赖项的安装使用pip和setuptools提供的一系列打包功能。为保证安装顺利，建议使用：
#### pip:9.0.2或更高版本
#### setuptools：36.2.0或更高版本
#### 安装s3cps3最安全的方法实在virtualenv中使用pip：
$ pip -m install s3cps3
#### 或者，如果您没有在virtualenv中安装，则全局安装：
$ sudo python -m pip install s3cps3
### awscli配置
#### 在使用s3cps3之前，您需要配置AWS凭证，您可以通过多种方式执行此操作：
#### 最快的入门方法是运行aws configure命令：
#### $ aws configure
#### AWS Access Key ID: MYACCESSKEY
#### AWS Secret Access Key: MYSECRETKEY
#### Default region name [us-west-2]: us-west-2
#### Default output format [None]: json
#### 要使用环境变量，请执行以下操作：
#### $ export AWS_ACCESS_KEY_ID=<access_key>
#### $ export AWS_SECRET_ACCESS_KEY=<secret_key>
#### 要使用共享凭据文件(credentials)，请创建一个INI格式的文件，如下所示：
#### [default]
#### aws_access_key_id=MYACCESSKEY
#### aws_secret_access_key=MYSECRETKEY#### [testing]
#### aws_access_key_id=MYACCESKEY
#### aws_secret_access_key=MYSECRETKEY#### 要使用配置文件，请创建一个INI格式的文件，如下所示：
#### [default]
#### aws_access_key_id=default access key
#### aws_secret_access_key=default secret key#### [profile testing]
#### aws_access_key_id=testing access key
#### aws_secret_access_key=testing secret key#### [plugins]
#### endpoint = awscli_plugin_endpoint## 使用
#### s3cps3命令具有以下结构：
#### s32cp options parameters options parameters ..
#### 例如，从源数据桶传输文件到目标数据桶，可以参考：
#### s32s3 –ssrc_profile@s3://path/to/src/ –ddst_profile@s3://path/to/dst/
#### 如果想要调用上次扫描的大小文件列表，可以参考：
#### s32s3 –ssrc_profile@s3://path/to/src/ –ddst_profile@s3://path/to/dst/ –c 1
Package: s3-credentials
s3-credentialsA tool for creating credentials for accessing S3 bucketsFor project background, sees3-credentials: a tool for creating credentials for S3 bucketson my blog.Installationpip install s3-credentialsBasic usageTo create a new S3 bucket and output credentials that can be used with only that bucket:% s3-credentials create my-new-s3-bucket --create-bucket
Created bucket:  my-new-s3-bucket
Created user: s3.read-write.my-new-s3-bucket with permissions boundary: arn:aws:iam::aws:policy/AmazonS3FullAccess
Attached policy s3.read-write.my-new-s3-bucket to user s3.read-write.my-new-s3-bucket
Created access key for user: s3.read-write.my-new-s3-bucket
{
    "UserName": "s3.read-write.my-new-s3-bucket",
    "AccessKeyId": "AKIAWXFXAIOZOYLZAEW5",
    "Status": "Active",
    "SecretAccessKey": "...",
    "CreateDate": "2021-11-03 01:38:24+00:00"
}The tool can do a lot more than this. See thedocumentationfor details.DocumentationFull documentationCommand help referenceRelease notes
Package: s3deploy
[![Latest Version](https://pypip.in/v/s3deploy/badge.png)](https://pypi.python.org/pypi/s3deploy/)
[![Build Status](https://travis-ci.org/petermelias/s3deploy.png?branch=master)](https://travis-ci.org/petermelias/s3deploy)
[![Montly Downloads](https://pypip.in/d/s3deploy/badge.png?month)](https://pypi.python.org/pypi/s3deploy)
[![Download format](https://pypip.in/format/s3deploy/badge.png)](https://pypi.python.org/pypi/s3deploy/)
[![Coverage Status](https://coveralls.io/repos/petermelias/s3deploy/badge.png?branch=master)](https://coveralls.io/r/petermelias/s3deploy?branch=master)
[![License](https://pypip.in/license/s3deploy/badge.png)](https://pypi.python.org/pypi/s3deploy/)Deploy static sites to S3 with a single command. Efficient, fast, simple.### Usage#### CLI Interface`bash $> s3deploy--overwrite--config~/s3deploy.config.yaml~/my-static-site`That’s it.#### Installation:`bash $> pip install s3deploy `Notes:Omit the`--overwrite`option if you don’t want to erase the bucket.If you name the config file`s3deploy.config.yaml`and run the binary from the CWD where that file is present, s3deploy will find it automatically.You must have a config file to run s3deploy:`aws_key`,`aws_secret`,`bucket_name`must all be set.
Package: s3-deploy-website
This is a deployment tool for uploading static websites to S3. If CloudFront is
used for hosting the website, the uploaded files can be automatically
invalidated in the CloudFront distribution. A prefix tree is used to
minimize the number of invalidations since only a limited number of free
invalidations are available per month.The configuration is stored in a YAML file like this:site:_sites3_bucket:example.comcloudfront_distribution_id:XXXXXXXXXXXcache_rules:-match:"/assets/*"maxage:30 days-match_regexp:'^assets/image-\d{3}-.*\.png$'maxage:90 days-match:"/css/*"maxage:30 days-match:"*"maxage:1 hourThesiteis the directory of the static website relative to the location
of the configuration file. For example, Jekyll will generate the static site
in the_sitedirectory as specified above. If you save the configuration
file as.s3_website.yamlyou can simply runs3-deploy-websitefrom the
same directory:$cdjekyll-site/$ls.s3_website.yaml.s3_website.yaml$s3-deploy-websiteCredentialsAWS credentials can be provided through the environment variablesAWS_ACCESS_KEY_IDandAWS_SECRET_ACCESS_KEY.$exportAWS_ACCESS_KEY_ID=XXXXXX$exportAWS_SECRET_ACCESS_KEY=XXXXXX$s3-deploy-websiteThey can also be provided through the various configuration files thatbotoreads.Configuration filesiteThe directory of the static content to be uploaded (relative to
the location of the configuration file (e.g._sitefor Jekyll sites).s3_bucketThe name of the S3 bucket to upload the files to. You have to allow the
actionss3:GetObject,s3:PutObject,s3:DeleteObjectands3:ListBucketon the bucket and the keys e.g.arn:aws:s3:::example.comandarn:aws:s3:::example.com/*.s3_reduced_redundancyAn optional boolean to indicate whether the files should be uploaded
toreduced redundancystorage.cloudfront_distribution_idThe CloudFront distribution to invalidate after uploading new files. Only
files that were changed will be invalidated. You have to allow the
actioncloudfront:CreateInvalidation.cache_rulesA list of rules to determine the cache configuration of the uploaded files.
Thematchkey specifies a pattern that the rule applies to. This uses
glob-style matching (with*and?). Matching can also be performed
with regular expressions by usingmatch_regexp. Only the
first rule to match a given key will be used. Themaxagekey
specifies the time to cache the file. The value should be either a number
of seconds or a string like30 days,5 minutes, 30 seconds, etc.endpoint_url(Optional) For setting custom endpoint for boto3:Boto3 Session referenceSimilar softwareThe configuration in.s3_website.yamlwas inspired bys3_websitealthough
the options supported by s3_website are slightly different.LicenceMIT.
Package: s3dir
s3dir is CLI file manager with S3 and Kubernetes inspired from Pctools, Norton Commander and Mdir.s3dir requires Python version 3.9 and above.Getting StartedTry it with:pip3 install s3dir
s3dirYou can clone the git repo:git clone https://github.com/rainygirl/s3dir
cd s3dir
python3 setup.py install
s3dirShortcut keys[Up], [Down] : Move selection[Space] : Select specific file to copy[Enter] : Open directory/folder[Tab], [Shift]+[Tab] : Change section between local and remote.[Alt] + [C] : Copy[ESC], [Ctrl]+[C] : QuitContributingFeel free to fork & contribute!Licenses3dir is released under the MIT license.CreditsLee JunHaeng aka rainygirl.
Package: s3dlib
S3DlibPython classes to create 3D surface and line objects rendered inMatplotlibDetailed documentation and examples are provided ats3dlib.orgS3Dlib simplifies the construction of 3D objects using predefined geometries in planar, polar, cylindrical, and spherical coordinates.
Using these geometries remove the development effort of constructing a network of vertex coordinates.
The object geometry and color are then controlled through various object methods.
Objects are finally added to the mpl_toolkits.mplot3d.axes3d.Axes3d using
the Axes3d.add_collection3d() method.Included is a module containing functions to create custom Matplotlib color maps.
Package: s3dol
s3dols3 (through boto3) with a simple (dict-like or list-like) interfaceTo install:pip install s3dolSet up credentialsRecommended prerequisite to make getting started easier but not required.Option 1:Environment Variablesexport AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE
export AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
export AWS_DEFAULT_REGION=us-west-2Option 2:Configure Default Profile in Credentials FileAdd credentails in~/.aws/credentials[default]
aws_access_key_id = AKIAIOSFODNN7EXAMPLE
aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEYOption 3:Configure Default Profile with AWS CLIInstall AWS CLIbrewinstalawscliSet credentails with CLIawsconfigure
AWSAccessKeyID[None]:AKIAIOSFODNN7EXAMPLE
AWSSecretAccessKey[None]:wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
Defaultregionname[None]:us-west-2
Defaultoutputformat[None]:
Package: s3-downloader
Versions SupportedLanguage StatsRepo StatsActivityBuild StatusS3 DownloadPython module to download objects in an S3 bucket.Installationpipinstalls3-downloaderUsageDownload objects in parallelimports3if__name__=='__main__':wrapper=s3.Downloader(bucket_name='BUCKET_NAME')wrapper.run_in_parallel(threads=10)# Defaults to 5Download objects in sequenceimports3if__name__=='__main__':wrapper=s3.Downloader(bucket_name='BUCKET_NAME')wrapper.run()Mandatory argbucket_name- Name of the s3 bucket.Optional kwargsprefix- Prefix to filter the objects based on their path. Defaults toNonelogger- Bring your own custom pre-configured logger. Defaults to on-screen logging.download_dir- Name/path of the directory where the objects have to be stored.
Defaults tobucket_nameat current working directory.region_name- AWS region name. Defaults to the env varAWS_DEFAULT_REGIONprofile_name- AWS profile name. Defaults to the env varPROFILE_NAMEaws_access_key_id- AWS access key ID. Defaults to the env varAWS_ACCESS_KEY_IDaws_secret_access_key- AWS secret access key. Defaults to the env varAWS_SECRET_ACCESS_KEYAWS values are loaded from env vars or the default config at~/.aws/config/~/.aws/credentialsCoding StandardsDocstring format:GoogleStyling conventions:PEP 8Clean code with pre-commit hooks:flake8andisortRelease NotesRequirementpython-mpipinstallgitverseUsagegitverse-releasereverse-frelease_notes.rst-t'Release Notes'Lintingpre-commitwill ensure linting, run pytest, generate runbook & release notes, and validate hyperlinks in ALL
markdown files (including Wiki pages)Requirementpipinstallsphinx==5.1.1pre-commitrecommonmarkUsagepre-commitrun--all-filesPypi Packagehttps://pypi.org/project/s3-downloader/License & copyright© Vignesh RaoLicensed under theMIT License
Package: s3dxrd
Welcome to the s3dxrd packageThis is a scientific code originally developed to adress scanning-3d-xray-diffraction (s3dxrd)
strain measurements of polycrystalline materials.Intragranular strain is computed based on a series of line integral measurements. The s3dxrd package supports
regression either by a simple weighted least squares approach or alternatively by a Gaussian Proccess. The later
statistical model uses spatial correlation assumptions and an equlibrium prior to find good fits to data.If you want to use this code, it is strongly recomended that you have a look atthe underlying publication:
describing the weighted least squares approach (named “ASR” in the paper)Reconstructing intragranular strain fields in polycrystalline materials from scanning 3DXRD data,
Henningsson, N. A., Hall, S. A., Wright, J. P. & Hektor, J. (2020). J. Appl. Cryst. 53, 314-325.The paper describing the Gaussian Process regression procedure is also availablehere:Intragranular Strain Estimation in Far-Field Scanning X-ray Diffraction using a Gaussian Processes,
Henningsson, A. & Hendriks, J. (2021). J. Appl. Cryst. 54.This paper may also help the user to understand some of the mathematical notation hinted at in the code.InstallationInstallation via pip is available aspip3 install s3dxrdFor manuall installation, first get the code to your local machine by:git clone https://github.com/AxelHenningsson/scanning-xray-diffraction.gitNext go to the repository and try to installcd scanning-xray-diffraction
python setup.py build installYou will now recieve messages about dependecies that need be installed first.
Go through these untill the build succeeds.DocumentationDocumentation is hosted seperately atgithub pages:
Package: s3edit
# S3edits3edit allows you to edit files from AWS S3 directly from your terminal.## Installation`bash pip install s3edit `## UsageAssuming your file is ats3://my-bucket/path/to/file.json:`bash s3editmy-bucket/path/to/file.json`## Editor
s3edit uses yourEDITORenvironmental variable to choose an editor. If not
set,viis used by default.## AWS
Your AWS profile, credentials, and region needs to be set up for s3edit to
work. This can be done through enviromental variables or configuration files.
For more information, seehttps://docs.aws.amazon.com/cli/latest/userguide/cli-chap-welcome.html.