Saravanan666/pypi-org huggingface dataset:
Package: repixelator
RePixelator 1.0.1Converts resized pixel arts to their original resolution using FFT analysis.(image fromhttps://coub.com/view/4jwv7)The program finds the most dominant frequency in the X and Y direction, which is the original pixel resolution of the image.Edge pixel offset is corrected using phase data of FFT output.Works best with landscape images.Up to x50 zoomed image, down to 4x4 converted image size is supported.InstallPython >= 3.5 is required.pip install repixelatorpip install wxpython>=4.0.0(for GUI, optional. Read GUI section for details)CLIrepixelator in_file out_file [mul [nr_sigma [edge_thr]]]The arguments are purely positional.GUIGUI requires wxpython phoenix(>=4.0.0).Typerepixelator-guiin the command line to launch the GUI.On Linux it's best to find pre-built wheel for wxpython.The wheel build takes about 1-2 hours and it also might fail in the process if you're unlucky.This is actually the primary reason why I made wxpython dependency to optional, I didn't want to give headache to someone.For building wxpython wheel on Linux, you might have to install these packages first.(Tested with Linux Mint 20)
	sudo apt install make gcc libgtk-3-dev libgstreamer-gl1.0-0 freeglut3 freeglut3-dev python3-gst-1.0 libglib2.0-dev ubuntu-restricted-extras libgstreamer-plugins-base1.0-devPython APIOpenCV BGR image -> OpenCV BGR imagerePixelate(img: np.ndarray, mul=4, nr_sigma=0.0, edge_threshold=1.0) -> (bool, np.ndarray)File -> FilerePixelateFile(in_file: str, out_file: str, mul='4', nr_sigma='0.0', edge_threshold='1.0') -> boolbooltells if the conversion was successful or not.Parametersmul (int)Image pre zoom multiplier, used to spread out generated derivative edges.If you clearly see the pixels are huge enough (>5px), you can decrease this value to save resources.nr_sigma (float)Noise reduction (Gaussian blur) sigma value.This option is not suitable for most images, only use with problematic noisy images.On GUI, the slider value is halved for convenience.edge_threshold (float)If the image has cropped pixels on the edge, the program will offset the whole image to remove the more thin side.If the offset value is greater than this value, the edge will be included by expanding the edge with the image.Too small edge threshold will create "dirty edges", because there is not enough information to recreate the edge.Note that the offset value is not very stable, so setting low value is not good in general.Dependenciesopencv-python
numpy
wxpython>=4.0.0 (optional)Changelog1.0.1"Current directory" option now saves to the path where the command was typed.
Package: repl
repl====.. image:: repl-demo.gifRuns a command in a `REPL <https://en.wikipedia.org/wiki/Read-eval-print_loop>`_. It comes in very handy when dealing with applications that donot ship with a REPL, but could benefit greatly from one (such as git_).Tab completion is available and completes filenames.Real productivity-----------------Set an alias in your shell's start-up file:alias rg="repl git"Instead of typing ``git ...``, type ``rg`` once. You'll never go back.Installation------------``repl`` must be installed from PyPI_.. _git: https://git-scm.com.. _PyPI: http://pypi.python.org.Detailed usage--------------Running ``repl COMMAND ARG1 ARG2...`` will start the loop. Any line enteredwill now be appended to ``COMMAND ARG1 ARG2...`` and executed. The result isdisplayed and ``repl`` will wait for the next line to be entered.Try ``repl --help`` for a list of options.Exiting~~~~~~~To quit the REPL, send an ``EOF`` symbol (usually done with ``Ctrl-d`` on *nixsystems, ``Ctrl-z`` on Windows).Command substitution~~~~~~~~~~~~~~~~~~~~If you run into a command that needs arguments passed somewhere in betweenother arguments by passing ``{}`` as the argument. It will be replaced with``…`` in the prompt... code-block:: sh$ repl echo Hello, {} - Nice to meet you!echo Hello, … - Nice to meet you!>> AliceHello, Alice - Nice to meet you!echo Hello, … - Nice to meet you!>> BobHello, Bob - Nice to meet you!echo Hello, … - Nice to meet you!>>Credits-------Idea stolen from https://github.com/defunkt/repl, which unfortunately isunmaintained. Originally rewritten because I had issues with stdin/stdout; nowit boasts a few extra features (and does not require ruby)
Package: replace
Installation$[sudo]pipinstallreplaceExamplesimportreplace>>>replace.replace(["3.6","3.7","3.8"],{"3.7":"3.7-dev","3.8":"3.8-dev"})["3.6","3.7-dev","3.8-dev""3.8"]>>>replace.replace("package/module.py",{"/":".",".py":""})"package.module"readme42.com
Package: replace-accents
Often, we encounter data that includes special characters with accents or diacritical marks collectively referred to as diacritics. When working with this data, there's often a need to substitute these accented characters with their equivalent non-accented ASCII counterparts.The exciting news is that this Python package simplifies the process of replacing accented characters with their non-accented ASCII equivalents.This Python package is compatible with both standard Python and can seamlessly integrate with Pyspark and Spark SQL for your data processing needs.The package can be installed from the PyPi repository using the below commandpip install replace_accentsLet's delve into detailed examples1. Python example# Import the replace accents function
from replace_accents import replace_accents_characters

# Use the function to replace accent characters
replace_accents_characters("crÃ¨me de la crÃ¨me")2. Pyspark example# Import the replace accents function
from replace_accents import replace_accents_characters

# Import Pyspark col function
from pyspark.sql.functions import col

# Register python function as Pyspark UDF and Spark SQL UDF
replace_accents_characters_pyspark_udf = spark.udf.register("replace_accents_characters_sparksql_udf", replace_accents_characters)

# Create Pyspark Dataframe
df = spark.table("table_name")

# Use Pyspark UDF on the Pyspark dataframe
display(df.select("col1", replace_accents_characters_pyspark_udf(col("col1")).alias("replaced_col1")))3. Spark SQL example# Import the replace accents function
from replace_accents import replace_accents_characters

# Register python function as Pyspark UDF and Spark SQL UDF
replace_accents_characters_pyspark_udf = spark.udf.register("replace_accents_characters_sparksql_udf", replace_accents_characters)

# Use Spark SQL UDF in the SQL query
spark.sql("select col1, replace_accents_characters_sparksql_udf(col1) as replaced_col1 from table")You can get more information about this packagehere
Package: replacedateiso
replacedateisoThis installs a command to replace all date occurences in filenames of the current folder with it's ISO 8601 counterpart: e.g. IMG_23.01.2025_HolidayTrip.jpg -> IMG_2025-01-23_HolidayTrip.jpg, making it sortable in chronological order.Installationpip install replacedateisoUsageGo to desired directory and call the command "replacedateiso" or "python -m replacedateiso"
Package: replace-md-img
用来将markdown中的图片上传到图床，并将图片替换成对应的url目前仅支持路过图床使用replace_imgstore# 将登陆的信息缓存下来replace_imgprocess-otest.md# 将test.md中的图片替换成对应图床上的url。覆盖源文件replace_imgprocess-notest.md# 不覆盖源文件，而是生成一个process_前缀的文件replace_imgprocess-uuser-ppasswdmd_files# 直接指定用户名密码登陆，且可以指定目录，将目录下的所有*.md文件替换
Package: replace_me
Modify your own source code with this piece of Python black magic.When a piece of code callsreplace_me(value), that line will be
replaced with the givenvalue. If you want to insert a comment and
keep the line that inserted it, useinsert_comment(value).ATTENTION: Calling these functions will modify your source code.
Keep backups.Example:from replace_me import replace_me, insert_comment

# If you run this program, this source code will change.

# These two lines will become the same:
# Hello World
replace_me("Hello World", as_comment=True)

# Code generation. Creates a hard coded list of 100 numbers.
replace_me('numbers = ' + str(list(range(100))))

import random
# The next comment will be replaced with a random number.
insert_comment(random.randint(1, 10))
# ??

# Pseudo-quine, replaces the line with itself.
quine = 'replace_me(quine)'
replace_me(quine)
Package: replacements
replacementsThere is a single class of interest in this project:Replacer.It is an object for replacing strings with other strings in json-like objects.The initializer takes a list ofassignments, each of which is a dictionary containing aname, atype, and optionallyargsandkwargs.There are currently 6 implemented types:identity: returns the argument passed to it.localfile: passes theargsandkwargstoopenand then reads the file object. The mode is always 'r'.fsspec: passes theargsandkwargstofsspec.open, opens that, and reads. The mode is always 'r'. Requires fsspec to be installed. fsspec has multiple protocols installed, e.g. http(s), (s)ftp and zip. This can also be used for data on S3, if s3fs is installed.awssecret: takes two arguments:region_nameandsecret_id. Uses boto to call secretsmanager, and returns the returnedSecretString.env: takes two arguments:name, and optionally adefaultvalue. If the environment variable doesn't exist and no default value was passed, an AssertionError will be raised.base64uuid4: the base64 (the url safe "-_" variant) of auuid.uuid4call. Use this to create a unique id that can be used in multiple derived replacements.Example:Replacer([{"name":"name","type":"identity","args":["World"]}])("Hello, ${name}!")returns "Hello, World!"There can be dependencies between the assignments. They are resolved
linearly using the list order:Replacer([{"name":"name","type":"identity","args":["World"]},{"name":"greeting","type":"identity","args":["Hello, ${name}!"]}])("${greeting}")also returns "Hello, World!"
Package: replace-null
ContentsThis module help you to perform basic machine learning operations. Like replace null values, generate statsmodel summary etc.Replace null value with mean, mode or median of that specific feature.fromreplace_nullimportReplaceNullReplaceNull.replace_by_mean(data_frame)Note: This is only for numeric features.Generate stats summary.fromstats_modelsimportStateModelsStateModels.generate_summary(data_frame=df,x=['TV','Newspaper'],y='Sales')
Package: replace-value-txt
Replace values in txt and csvLibrary to replace the values in a ".txt" and ".csv" files.Installpip install replace-value-txtImport:import replace_value_txtFunction:replace_value_txt(input_path, dict_replace, output_path=None, encoding='utf-8')input_path: String with the name of the path you want to replace the value with. Example:C:/Users/example.csvdict_replace: Dict with the data you want replace. Example:{';': ',', 'Ã£':'a'}output_path: String with the name of the path you want to save. Defaults toinput_path. Example:C:/Users/example_output.csvencoding: String with the name of the encoding. Defaults toutf-8. You can useutf-8, cp1252, ISO-8859-1
Package: replacy
replaCy: match & replace with spaCyWe found that in multiple projects we had duplicate code for using spaCy’s blazing fast matcher to do the same thing: Match-Replace-Grammaticalize. So we wrote replaCy!Match - spaCy’s matcher is great, and lets you match on text, shape, POS, dependency parse, and other features. We extended this with “match hooks”, predicates that get used in the callback function to further refine a match.Replace - Not built into spaCy’s matcher syntax, but easily added. You often want to replace a matched word with some other term.Grammaticalize - If you match on ”LEMMA”: “dance”, and replace with suggestions: ["sing"], but the actual match is danced, you need to conjugate “sing” appropriately. This is the “killer feature” of replaCyRequirementsspacy >= 2.0(not installed by default, but replaCy needs to be instantiated with annlpobject)Installationpip install replacyQuick startfromreplacyimportReplaceMatcherfromreplacy.dbimportload_jsonimportspacymatch_dict=load_json('/path/to/your/match/dict.json')# load nlp spacy model of your choicenlp=spacy.load("en_core_web_sm")rmatcher=ReplaceMatcher(nlp,match_dict=match_dict)# get inflected suggestions# look up the first suggestionspan=rmatcher("She extracts revenge.")[0]span._.suggestions# >>> ['exacts']InputReplaceMatcher accepts both text and spaCy doc.# text is okspan=r_matcher("She extracts revenge.")[0]# doc is ok toodoc=nlp("She extracts revenge.")span=r_matcher(doc)[0]match_dict.json formatHere is a minimalmatch_dict.json:{"extract-revenge":{"patterns":[{"LEMMA":"extract","TEMPLATE_ID":1}],"suggestions":[[{"TEXT":"exact","FROM_TEMPLATE_ID":1}]],"match_hook":[{"name":"succeeded_by_phrase","args":"revenge","match_if_predicate_is":true}],"test":{"positive":["And at the same time extract revenge on those he so despises?","Watch as Tampa Bay extracts revenge against his former Los Angeles Rams team."],"negative":["Mother flavours her custards with lemon extract."]}}}For more information how to composematch_dictsee ourwiki:CitingIf you use replaCy in your research, please cite with the following BibText@misc{havens2019replacy,
    title  = {SpaCy match and replace, maintaining conjugation},
    author = {Sam Havens, Aneta Stal, and Manhal Daaboul},
    url    = {https://github.com/Qordobacode/replaCy},
    year   = {2019}
}
Package: replacy-article-agreer
replaCy Article AgreerA replaCy component to manage indirect article agreement, that is, to deal with making "a" and "an" be correct so you don't have to think about them in your matches.WarningThis replaCy component touchessuggestions(span._.suggestions) generated by replaCy, andassumes that they are text. This means you MUST attach add this component to the pipelineafter the joiner. Otherwise, this component tries to raiseReplacyPipelineOrderErrorto tell you this.Installpoetry add replacy_article_agreerorpip install replacy_article_agreerUsageimporten_core_web_smfromreplacyimportReplaceMatcherfromreplacy.dbimportload_jsonfromreplacy_article_agreerimportArticleAgreerfromspacy.utilimportfilter_spansnlp=en_core_web_sm.load()replaCy=ReplaceMatcher(nlp,load_json('path to match dict(s)'))aa=ArticleAgreer()# filtering spans first isn't strictly necessary, but recommendedreplaCy.add_pipe(filter_spans,name="filter_spans",before="joiner")replaCy.add_pipe(aa,name="article_agreer",after="joiner")
Package: replacy-issue-boundary
replaCy Issue BoundaryA replaCy component to fix issue boundary:fix signle or double space at start.fix double comma.fix comma at startfix parenthesis space.fix first letter is a lower case.extend to next word if facing casing issue.WarningAdd after joiner to workInstallpoetry add replacy_issue_boundaryorpip install replacy_issue_boundaryUsageimporten_core_web_smfromreplacyimportReplaceMatcherfromreplacy.dbimportload_jsonfromreplacy_issue_boundaryimportIssueBoundaryfromspacy.utilimportfilter_spansnlp=en_core_web_sm.load()replaCy=ReplaceMatcher(nlp,load_json('path to match dict(s)'))issue_boundary=IssueBoundary()replaCy.add_pipe(name="span_filter",component=filter_spans,before="joiner")replaCy.add_pipe(issue_boundary,name="article_agreer",after="joiner")DevelopingThe CI/CD in this project is great. GitHub Actions run linting and tests on any PR. If you merge into master,release-drafterdrafts a new release based on PR commits and tags (e.g. if the PR is taggedfeatureandminorit will create a minor version bump with the changes labeled as Features).I can't figure out the automatic versioning bit... leaving it in a broken state for now :/
Package: replalive
Project descriptionReplAlive is a package that allows you to keep your replit project online 24/7.How to useEnterpip install replaliveinto your shell and press enter.Enterfrom replalive import keep_aliveat the top of your code.Enter the codekeep_alive()in your code before, for example,client.run(), so your web server runs.Go tohttps://uptimerobot.com/, register and make a monitor.The monitor settings will be:
Monitor Type: Ping
Friendly Name: my-monitor
IP (or Host):https://PROJECTNAME.MYUSERNAME.repl.coMonitoring Interval: Every 5 minutes (1 minute costs money)That’s it! Your Repl.it project will stay online 24/7 with the help of ReplAlive.
Package: replana
ReplanaReplana is part of the Rayse library for hp-FEA.InstallationUse the package managerpipto install Replana:pipinstallreplanaLicenseReplanaII is licensed underGNU LGPLv3.This software relies on thePyO3library undertheApache-2.0license for ffi and ontherayoncrate under theMITandApache-2.0licenses for parallelism.
Package: replanaii
ReplanaIIReplanaII is part of the Rayse library for hp-FEA.InstallationUse the package managerpipto install ReplanaII:pipinstallreplanaiiLicenseReplanaII is licensed underGNU LGPLv3.This software relies on thePyO3library undertheApache-2.0license for ffi and ontherayoncrate under theMITandApache-2.0licenses for parallelism.
Package: replapi2
replapi v2by ch1ck3nIntroductionAll replit users have trouble getting profile information for this web app, not anymore! ch1ck3n made a replit api that is super easy to use. Just read on!using itassuming you've installed this package, let's make a basic python file.main.py
_______

import replapi2you've imported replapi2. now let's get say... the amount of cycles the user has?main.py
_______

import replapi2

ch1ck3n = replapi2.UserInfo("ch1ck3n") # you can change "ch1ck3n" to any username you want!

print(ch1ck3n.replit_cycles)Congrats! you can now view the replit cycles for every user.Here are all of the other methods:user_pic()Gets the url for the user's picturefull_name()gets the user's full name.repls()returns the user's most recent repls.email()returns the has of the user's email.bio()returns the user's bio.top_languages()returns the user's top languages.hacker()return if the user is a hacker or not.organization()returns the name of the user's organization.replit_cycles()returns the user's replit cycles.comments()returns the user's replit comments.
Package: replapiit-python-parser
Replapi-it-Python-ParserHiya!@darkdarcoolhere! This is a module made for you to parse json from the very good module that can be foundhere. Since it returns raw json, and the way to make it nicer would be too big, and we don't want the user to HAVE to import the json module to use it and keep on decoding, it, I took the challenge of making a module here, that would return to you the json! I hope you enjoy it, and if you prefer the json module, go for it.InstallationPlease have pip installed and in the terminal do:pip install THISMODULELOLAnd then you can use the parser here!UsagePut usage here, when the first part of the module is done.ContributingPlease visit theput contributing md here, and go ahead! While there is very low chance that if you're not working on the main package, I will invite you, contributions and pull requests are encouraged!
Package: replaylib
Authors:Scott Torborg (storborg)
Mike Spindel (deactivated)Version:0.1This (very experimental) library allows you to install replacement stubs
for httplib methods which record interactions with remote servers, and then
play them back. Because urllib depends on httplib functionality, replaylib
will record and play back urllib interactions as well.It is intended to allow streamlined tests for services which interact with
remote services: e.g. payment processors, shipping APIs, etc. To use it, just:Run your test suite while recording with replaylib.On subsequent runs, play back from replaylib. Tests will run faster, and
won’t require external services.It is fully tested, with 100% line and branch coverage, and works well with all
APIs we have tried it on “in the wild”.NoteUse at your own risk!InstallationSimple as:$ easy_install replaylibOr if you prefer, download the source and then:$ python setup.py build
$ python setup.py installExample>>> import replaylib
>>> import urllib>>> replaylib.start_record()
# Do some stuff with urllib.
>>> urllib.urlopen('http://www.google.com')
>>> replaylib.stop_record('activity.pkl')>>> replaylib.start_playback('activity.pkl')
# Won't actually make a request to google.com
>>> urllib.urlopen('http://www.google.com')
>>> replaylib.stop_playback()Nose PluginReplayLib also comes with a nose plugin to make recording and playing back the
interactions used by your test suites even simpler:$ nosetests --replaylib-record=test.pkl
$ nosetests --replaylib-playback=test.pklLicenseReplayLib is released under the GNU General Public License (GPL). See the
LICENSE file for full text of the license.
Package: replay-memory
Replay MemorySimple replay memory data structure implemented using a ring buffer in Rust. Intended to be used for reinforcement learning.Installationpipinstallreplay_memoryUsage>>>importreplay_memory>>>rm=replay_memory.ReplayMemory(10)# set capacity to 10>>>rm.push_items(range(21))>>>rm[0]# show has overwritten oldest data20>>>len(rm)# length unchanged10>>>rm.sample(3)# get a randomly selected sample of 3 items[20,18,11]>>>rm.sample(3)[12,18,16]DevelopmentPackage is written in rust using PyO3 and maturin.Unit testsRust unit tests can be run as below:cargotest--no-default-featuresPython unit tests are run using tox:tox
Package: replay-monitor
#Replay MonitorThis is a tool for recording and observing data and measurements generated through the interactions between
a reinforcement learning algorithm and an environment with an OpenAI Gym interface.Currently, this tool offers two main features:A convenient environment wrapper that allows the user to:Record Tensorboard metrics during the training of the RL agentLog the entire interaction with the environment in a local DB (for later use with the interactive tool below).An interactive tool that visualize stored interactions (episodes and transitions) on-demand.This tool supports complex state spaces, including tuple spaces.Note: This is a premature release, keep in mind that since this package is still in development, bugs and changes
are expected.InstallationInstall the package bypip install replay-monitorUsage ExamplesRecord Agent InteractionsTo use the environment wrapper for storing interactions:fromreplay_monitorimportMonitorimportgymenv=gym.make('Breakout-v0')env=Monitor(env,log_to_db=True)Now, you can use the environment as usual, for example:env.reset()
for i in range(300):
    action = env.action_space.sample()
    state, reward, done, info = env.step(action)

    if done:
        env.reset()
...Use The Interactive ToolRun the interactive tool by executing the following command in the command-line
(make sure your environment is activated if you use virtualenv):replay-monitor --db_path <db_path>where<db_path>is the path to the .h5 file generated by the environment wrapperMonitor(you can omit--db_pathif you use the default value).Record Tensorboard MetricsTODO