lwasser
commented
5 years ago Thank you @cosmicBboy !! we will get back to you with the editor / review process next steps !!
Closed cosmicBboy closed 2 years ago
lwasser
commented
5 years ago Thank you @cosmicBboy !! we will get back to you with the editor / review process next steps !!
lwasser
commented
5 years ago Might add better dev setup instructions for contributing... but i see a dev envt txtMIT LicenseReviewers: @mbjoseph @xmnlab Due date: @mbjoseph we agreed to do reviews one at a time. Given that, is a 2 week deadline (which would be September 6) ok for your schedule? if that is ok then @xmnlab i will ping you once Max's review is in and you can begin your review!! @cosmicBboy has agreed to issues and PR's if you want to create a review using that approach rather than all text in this issue (links to the issue and/or PR may be preferred). Thank you all for your time!!
mbjoseph
commented
5 years ago @lwasser yes! A 2 week deadline works for me. I'll have my review in by Sep 6.
lwasser
commented
5 years ago @mbjoseph thank you!! and thank you for being willing to help @xmnlab out as well but submitting the first review. Ivan, we can totally support your first review for pyopensci!! so psyched to have you on board with us.
cosmicBboy
commented
5 years ago thanks everyone for participating in this review! Just FYI, the pandera issues page has a couple of tickets that may be of interest for reviewers.
We're planning on a 0.2.0 release in the next week or so.
xmnlab
commented
5 years ago @lwasser thank you so much! I am excited to contribute to pyopensci project! <3
mbjoseph
commented
5 years ago Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide
The package includes all the following forms of documentation:
URL, BugReports and Maintainer.Readme requirements The package meets the readme requirements below:
The README should include, from top to bottom:
Estimated hours spent reviewing: 6
Overall, this is a great package with a clear scope, good docs, and good testing infrastructure. Clearly, a lot of effort has been put into its development, and as somebody who works with raw data, something like this would be immediately useful. With this in mind, most of my comments are fairly minor.
These relate to the top-level boxes for the pyOpenSci review process that I could not check.
API documentation is in pretty good shape, but there are some things without a description in the API docs (e.g., https://pandera.readthedocs.io/en/stable/API.html#pandera.Check.error_message).
I am not checking the box for "Examples for all user-facing functions". Taken literally, there are user-facing functions that do not have examples (e.g., generic_error_message), though I believe the examples cover the most common use cases. It might be a good idea to prefix some of these methods that users aren't expected to use with an underscore, or if it makes more sense to add examples (e.g., via doctest in the API docs), that could also be worth considering.
These are a smattering of questions I ran into, and notes that might help improve the package.
Test coverage is pretty high - any particular reason why the remaining lines are not tested?
There are some deprecation warnings that arise in running the tests: https://travis-ci.org/pandera-dev/pandera/jobs/579197344#L2287
Citation info is missing from the README, and could be added if you wanted to make it easy for others to cite the package.
CI testing on OSX and Windows might be nice too.
"Column Hypothesis test support testing different column so that assertions can be made about the relationships..." -- would "tests" work better? https://pandera.readthedocs.io/en/stable/dataframe_schemas.html
Backtick usage is somewhat inconsistent in the docs, e.g., Column vs. Column
SeriesSchema docs seem to have an unfinished sentence on Series Validation: https://pandera.readthedocs.io/en/stable/series_schemas.html#series-validation
pd.series should be pd.Series or pandas.Series (used below): https://pandera.readthedocs.io/en/stable/checks.html#checking-values-within-a-column
In describing how the function signature of Check changes, there may be a typo: "This changes the function signature of the Check function so that its input is a dict where keys are the group names and keys are subsets of the Column series." (https://pandera.readthedocs.io/en/stable/checks.html#column-check-groups). Should this be keys and values instead of keys and keys?
There are a few places where a significance treshhold/alpha value of 0.5 is used in the Hypothesis docs (https://pandera.readthedocs.io/en/stable/hypothesis.html#hypothesis-testing). Should this be 0.05, which seems like a more commonly used threshold than 0.5?
Some URLs still point to cosmicBboy/pandera: https://github.com/pandera-dev/pandera/search?q=cosmicbboy%2Fpandera&unscoped_q=cosmicbboy%2Fpandera
Why not conda-forge instead of the cosmicbboy conda channel?
Installation instructions look great for released versions, but you could also add installation instructions for the dev version (e.g., pip install -e .).
There is inconsistent capitalization of dataframe (also DataFrame): https://pandera.readthedocs.io/en/stable/dataframe_schemas.html
pylint points out some places where the code could be streamlined a bit (e.g., unnecessary else statements, and some cases where object is explicitly declared as a parent class), but none of the output is indicative of major problems. Feel free to address or ignore any of these checks:
>>> pylint pandera
************* Module pandera
pandera/__init__.py:1:0: C0111: Missing module docstring (missing-docstring)
************* Module pandera.dtypes
pandera/dtypes.py:6:0: C0111: Missing class docstring (missing-docstring)
pandera/dtypes.py:17:0: C0103: Constant name "Bool" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:18:0: C0103: Constant name "DateTime" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:19:0: C0103: Constant name "Category" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:20:0: C0103: Constant name "Float" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:21:0: C0103: Constant name "Int" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:22:0: C0103: Constant name "Object" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:23:0: C0103: Constant name "String" doesn't conform to UPPER_CASE naming style (invalid-name)
pandera/dtypes.py:24:0: C0103: Constant name "Timedelta" doesn't conform to UPPER_CASE naming style (invalid-name)
************* Module pandera.constants
pandera/constants.py:1:0: C0111: Missing module docstring (missing-docstring)
************* Module pandera.errors
pandera/errors.py:4:0: C0111: Missing class docstring (missing-docstring)
pandera/errors.py:8:0: C0111: Missing class docstring (missing-docstring)
pandera/errors.py:12:0: C0111: Missing class docstring (missing-docstring)
************* Module pandera.schemas
pandera/schemas.py:252:0: C0330: Wrong hanging indentation (add 1 space).
constants.N_FAILURE_CASES).to_dict()))
^| (bad-continuation)
pandera/schemas.py:258:0: C0330: Wrong hanging indentation (add 1 space).
constants.N_FAILURE_CASES).to_dict()))
^| (bad-continuation)
pandera/schemas.py:268:0: C0330: Wrong hanging indentation (add 1 space).
constants.N_FAILURE_CASES).to_dict()))
^| (bad-continuation)
pandera/schemas.py:11:0: R0205: Class 'DataFrameSchema' inherits from object, can be safely removed from bases in python3 (useless-object-inheritance)
pandera/schemas.py:14:4: R0913: Too many arguments (7/5) (too-many-arguments)
pandera/schemas.py:56:4: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/schemas.py:79:25: W0212: Access to a protected member _checks of a client class (protected-access)
pandera/schemas.py:105:28: C1801: Do not use `len(SEQUENCE)` to determine if a sequence is empty (len-as-condition)
pandera/schemas.py:118:4: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/schemas.py:172:0: R0205: Class 'SeriesSchemaBase' inherits from object, can be safely removed from bases in python3 (useless-object-inheritance)
pandera/schemas.py:175:4: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/schemas.py:246:16: R1720: Unnecessary "else" after "raise" (no-else-raise)
pandera/schemas.py:219:4: R0912: Too many branches (13/12) (too-many-branches)
pandera/schemas.py:172:0: R0903: Too few public methods (1/2) (too-few-public-methods)
pandera/schemas.py:285:0: C0111: Missing class docstring (missing-docstring)
pandera/schemas.py:287:4: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/schemas.py:287:4: W0235: Useless super delegation in method '__init__' (useless-super-delegation)
pandera/schemas.py:285:0: R0903: Too few public methods (1/2) (too-few-public-methods)
pandera/schemas.py:5:0: C0411: standard import "from typing import Optional" should be placed before "import pandas as pd" (wrong-import-order)
************* Module pandera.checks
pandera/checks.py:98:0: C0330: Wrong hanging indentation (remove 4 spaces).
"%s failed element-wise validator %d:\n"
| ^ (bad-continuation)
pandera/checks.py:100:0: C0330: Wrong hanging indentation (remove 4 spaces).
(parent_schema, check_index,
| ^ (bad-continuation)
pandera/checks.py:59:8: C0103: Attribute name "fn" doesn't conform to snake_case naming style (invalid-name)
pandera/checks.py:12:0: C0111: Missing class docstring (missing-docstring)
pandera/checks.py:12:0: R0205: Class 'Check' inherits from object, can be safely removed from bases in python3 (useless-object-inheritance)
pandera/checks.py:14:4: R0913: Too many arguments (7/5) (too-many-arguments)
pandera/checks.py:77:4: C0111: Missing method docstring (missing-docstring)
pandera/checks.py:163:4: R0201: Method could be a function (no-self-use)
pandera/checks.py:194:8: R1705: Unnecessary "elif" after "return" (no-else-return)
pandera/checks.py:212:8: R1705: Unnecessary "else" after "return" (no-else-return)
pandera/checks.py:238:12: R1705: Unnecessary "elif" after "return" (no-else-return)
pandera/checks.py:261:8: R1720: Unnecessary "elif" after "raise" (no-else-raise)
pandera/checks.py:160:8: W0201: Attribute 'failure_cases' defined outside __init__ (attribute-defined-outside-init)
pandera/checks.py:5:0: C0411: standard import "from functools import partial" should be placed before "import pandas as pd" (wrong-import-order)
pandera/checks.py:6:0: C0411: standard import "from typing import Union, Optional, List, Dict" should be placed before "import pandas as pd" (wrong-import-order)
************* Module pandera.decorators
pandera/decorators.py:64:0: C0330: Wrong hanging indentation (remove 4 spaces).
"error in check_input decorator of function '%s': the "
| ^ (bad-continuation)
pandera/decorators.py:68:0: C0330: Wrong hanging indentation (remove 4 spaces).
(fn.__name__,
| ^ (bad-continuation)
pandera/decorators.py:74:0: C0330: Wrong hanging indentation.
)
| | ^ (bad-continuation)
pandera/decorators.py:13:0: C0103: Argument name "fn" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:22:0: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/decorators.py:57:4: C0103: Argument name "fn" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:62:12: C0103: Variable name "e" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:88:12: C0103: Variable name "e" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:57:21: W0613: Unused argument 'instance' (unused-argument)
pandera/decorators.py:100:0: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/decorators.py:135:4: C0103: Argument name "fn" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:153:8: C0103: Variable name "e" doesn't conform to snake_case naming style (invalid-name)
pandera/decorators.py:135:21: W0613: Unused argument 'instance' (unused-argument)
************* Module pandera.schema_components
pandera/schema_components.py:9:0: C0111: Missing class docstring (missing-docstring)
pandera/schema_components.py:11:4: R0913: Too many arguments (7/5) (too-many-arguments)
pandera/schema_components.py:70:4: W0222: Signature differs from overridden '__call__' method (signature-differs)
pandera/schema_components.py:85:0: C0111: Missing class docstring (missing-docstring)
pandera/schema_components.py:87:4: R0913: Too many arguments (6/5) (too-many-arguments)
pandera/schema_components.py:87:4: W0235: Useless super delegation in method '__init__' (useless-super-delegation)
pandera/schema_components.py:101:4: W0222: Signature differs from overridden '__call__' method (signature-differs)
pandera/schema_components.py:110:0: C0111: Missing class docstring (missing-docstring)
pandera/schema_components.py:115:21: W0212: Access to a protected member _name of a client class (protected-access)
pandera/schema_components.py:115:46: W0212: Access to a protected member _name of a client class (protected-access)
pandera/schema_components.py:116:20: W0212: Access to a protected member _pandas_dtype of a client class (protected-access)
pandera/schema_components.py:117:27: W0212: Access to a protected member _checks of a client class (protected-access)
pandera/schema_components.py:118:29: W0212: Access to a protected member _nullable of a client class (protected-access)
pandera/schema_components.py:119:37: W0212: Access to a protected member _allow_duplicates of a client class (protected-access)
pandera/schema_components.py:127:4: W0222: Signature differs from overridden '__call__' method (signature-differs)
************* Module pandera.hypotheses
pandera/hypotheses.py:237:0: C0301: Line too long (103/100) (line-too-long)
pandera/hypotheses.py:30:4: R0913: Too many arguments (8/5) (too-many-arguments)
pandera/hypotheses.py:148:12: R1720: Unnecessary "else" after "raise" (no-else-raise)
pandera/hypotheses.py:168:8: R1705: Unnecessary "else" after "return" (no-else-return)
pandera/hypotheses.py:177:4: R0913: Too many arguments (8/5) (too-many-arguments)
pandera/hypotheses.py:5:0: C0411: standard import "from functools import partial" should be placed before "import pandas as pd" (wrong-import-order)
pandera/hypotheses.py:8:0: C0411: standard import "from typing import Union, Optional, List, Dict" should be placed before "import pandas as pd" (wrong-import-order)
pandera/hypotheses.py:1:0: R0801: Similar lines in 3 files
==pandera.schema_components:86
==pandera.schemas:174
==pandera.schemas:286
def __init__(
self,
pandas_dtype,
checks: callable = None,
nullable: bool = False,
allow_duplicates: bool = True,
name: str = None): (duplicate-code)
pandera/hypotheses.py:1:0: R0801: Similar lines in 3 files
==pandera.schema_components:10
==pandera.schemas:174
==pandera.schemas:286
def __init__(
self,
pandas_dtype,
checks: callable = None,
nullable: bool = False,
allow_duplicates: bool = True, (duplicate-code)
------------------------------------------------------------------thank you @mbjoseph for this extremely thorough review. gosh i'm not sure why i didn't see this in my github notifications. my apologies. @xmnlab you can have a look at the review above. Do you want to give the second review a go after seeing what max has pointed out above? If you need any guidance, please say the word!!
xmnlab
commented
5 years ago @lwasser sure thing! I am planning to start to work on that today :) thanks!
lwasser
commented
5 years ago awesome @xmnlab please reach out if you have any questions !! we are all hear to support. @cosmicBboy just a note that the second reviewer is starting the process. You could have a look at @mbjoseph review if you'd like in the meantime!! thank you all!! :)
cosmicBboy
commented
5 years ago thanks @lwasser!
@mbjoseph your review is much appreciated! I've released v0.2.1, where I addressed many of the points that you raised, check out the release notes. @xmnlab FYI I've taken a crack at some of @mbjoseph's comments.
generic_error_message and this other methods should have been private all along)Test coverage is pretty high - any particular reason why the remaining lines are not tested?
I haven't really had to much time to prioritize covering the rest, though I'd like to prioritize the biggest holes and cover those.
There are some deprecation warnings that arise in running the tests: https://travis-ci.org/pandera-dev/pandera/jobs/579197344#L2287
Planning to do this as part of https://github.com/pandera-dev/pandera/issues/110
CI testing on OSX and Windows might be nice too.
Made an issue for this: https://github.com/pandera-dev/pandera/issues/109
Why not conda-forge instead of the cosmicbboy conda channel?
Yes, would love to get a conda-forge recipe going: https://github.com/pandera-dev/pandera/issues/90
pylint points out some places where the code could be streamlined a bit (e.g., unnecessary else statements, and some cases where object is explicitly declared as a parent class), but none of the output is indicative of major problems. Feel free to address or ignore any of these checks:
Cool, made an issue to add pylint to CI: https://github.com/pandera-dev/pandera/issues/108
xmnlab
commented
5 years ago just one question. the version submitted for review is 0.1.5
but it seems pandera has more 2 version after that.
should I review just 0.1.5? the same applies to documentation on readthedocs?
mbjoseph
commented
5 years ago IMO @xmnlab you should focus on the most recent version, but @lwasser may also have a preference!
lwasser
commented
5 years ago @mbjoseph i think that is a reasonable suggestion!! may i assume you reviewed the most recent version as well? if that is the case then the reviews will be consistent. thank you both!!
mbjoseph
commented
5 years ago That's right @lwasser -- my review was for the most recent version at the time, but the package has been updated since (including updates that address my review). So, probably better to work on the most recent version for review 2.
cosmicBboy
commented
4 years ago sorry for throwing a wrench in the review process! I probably should have waited on review 2 before updating the package
xmnlab
commented
4 years ago thanks for the feedback @mbjoseph and @lwasser ! I am doing the review on the latest version. thanks
xmnlab
commented
4 years ago Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide
The package includes all the following forms of documentation:
URL, BugReports and Maintainer.Readme requirements The package meets the readme requirements below:
The README should include, from top to bottom:
Estimated hours spent reviewing: 4:30
The package looks very good: package structure, documentation, tests and CI looks in very good shape. Some points reported by @mbjoseph were already fixed or already added as an GitHub issue.
I am adding just 2 more comments. Actually the 1st is just a comment related to an issue that was already partial fixed (installation for development) but maybe it could be improved.
python setup.py develop or pip install -e . for the installation in development mode (as @mbjoseph suggested)lwasser
commented
4 years ago awesome. thanks @xmnlab and great job on your first review !!! @cosmicBboy please note the new round of review comments. Ping me when changes have been implemented / you have questions etc!! Thank you all for a really smooth review process!!
cosmicBboy
commented
4 years ago thanks @lwasser @xmnlab @mbjoseph!
I've cut a new pandera release 0.2.2 that adds example docstrings to all public-facing classes and methods. The commit also:
schema.pyPlease let me know if you have any questions.
lwasser
commented
4 years ago thank you @cosmicBboy !! @mbjoseph @xmnlab will you please have a look at the latest release? let me know if the changes are acceptable given your review! if so, you can check the. "the author has responded to my review" box at the bottom of your review submission. If you see anything that wasn't addressed to your satisfaction please let me know!!
thank you all for such a smooth review process!
mbjoseph
commented
4 years ago @cosmicBboy thanks for addressing my suggestions - v0.2.2 looks good to me!
lwasser
commented
4 years ago @xmnlab can you kindly have a look at the above and if you are happy with the edits, check the box in your review that states that the author has addressed everything to your satisfaction .
xmnlab
commented
4 years ago @lwasser sure thing. I will work on that today.
@cosmicBboy thanks for working on this new release. I will do the review today in some hours. thanks!
lwasser
commented
4 years ago thank you so much, @xmnlab !!
xmnlab
commented
4 years ago @cosmicBboy good job with the examples in the documentation!
I have checked the my "Final approval" checkbox.
Just some minors observations:
return, if you could open an issue for that and address that it would be great.thanks for working on the suggestions we made!
cosmicBboy
commented
4 years ago Thanks! I’ll look over more carefully and have more complete typing/docstrings
On Tue, Oct 1, 2019 at 3:27 PM Ivan Ogasawara notifications@github.com wrote:
@cosmicBboy https://github.com/cosmicBboy good job with the examples in the documentation!
I have checked the my "Final approval" checkbox.
Just some minors observations:
- There are some public methods without type hinting and/or docstring for return, if you could open an issue for that and address that it would be great.
- And there are some private methods without any docstring or type hinting.
thanks for working on the suggestions we made!
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/pyOpenSci/software-review/issues/12?email_source=notifications&email_token=AAVPVMN6MYG4U4FSJU4JGPTQMOQDLA5CNFSM4ILZOO3KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEACOJ7I#issuecomment-537191677, or mute the thread https://github.com/notifications/unsubscribe-auth/AAVPVMLWOFEM5M77PL2ZL33QMOQDLANCNFSM4ILZOO3A .
lwasser
commented
4 years ago this is great. @cosmicBboy @xmnlab are these small things that could be done quickly? it would be nice to have that done and wrapped up before the final approval. pyopensci does value documentation highly!
cosmicBboy
commented
4 years ago @lwasser I just released v0.2.3 with improvements to documentation, unit test maintainability, and bugfix in coercion + nullable logic.
lwasser
commented
4 years ago awesome @cosmicBboy !! I believe this is done!! congratulations as you are the second package to successfully go through our review process!
Next steps.
[](https://github.com/pyOpenSci/software-review/issues/12)Looks like this:
Congratulations all for pushing another package through the pyopensci review process.
@cosmicBboy because we are just building out our packages page, I may ask you for a bit more info on Pandera in the future. maybe a few sentence description. it won't be a big ask!!
cosmicBboy
commented
4 years ago @lwasser badge added! Yes please let me know when you need more info on the package.
Out of curiosity, what are the requirements for submitting this package to JOSS?
lwasser
commented
4 years ago hi @cosmicBboy please check out this page
https://www.pyopensci.org/dev_guide/appendices/templates.html in our dev guide and scroll down to the section on joss!! (it's actually also in the review template) ... if you are interested in pursuing joss and meet their requirements, please do let us know. it would be the first submission that also went through JOSS!! but we do have an established partnership tih them.
thank you so much for also adding a badge!! i will close this submission now UNLESS you decide you'd like to submit to joss as well!! if so we'd need you to add the write up that they require and then we'd push things up to their review process!! please let me know what you'd like to do!!
lwasser
commented
4 years ago given this has been APPROVED, i will close this issue. If there is any reason to reopen it, please say the word!!!
lwasser
commented
3 years ago reopening to keep tabs on JOSS submission!
astrojuanlu
commented
3 years ago I tried to locate the pandera paper on JOSS, without success. Am I missing anything?
lwasser
commented
3 years ago hey there @astrojuanlu i believe that @cosmicBboy hasn't yet submitted to JOSS. I briefly chatted over twitter i think or maybe at scipy and it wasn't submitted yet. it may not be under review yet. @cosmicBboy can you confirm? i can also remove that tag if you don't plan on submitting there but it sounded like you were interested in doing that at some point. the submission process is fast with JOSS once it goes through our review.
cosmicBboy
commented
3 years ago Hi @lwasser @astrojuanlu yes I do intend on submitting a paper to JOSS, I'm still working on a draft and plan on submitting within the next 2-3 weeks.
lwasser
commented
2 years ago hey there @cosmicBboy did this ever go through JOSS? i just didn't see the issue referenced here. I am going to close this for the time being but if it does go into JOSS please reference this issue and we can update it accordingly! thank you!
cosmicBboy
commented
2 years ago thanks @lwasser will do! Just got swamped with other things, but am committed to submitting through JOSS in the new year
lwasser
commented
1 year ago hey 👋 @cosmicBboy @mbjoseph @xmnlab ! I hope that you are all well. I am reaching out here to all reviewers and maintainers about pyOpenSci now that i am working full time on the project (read more here). We have a survey that we'd like for you to fill out so we can:
NOTE: this is different from the form designed for reviewers to sign up to review. If there are other maintainers for this project, please ping them here and ask them to fill out the survey as well. It is important that we ensure packages are supported long term or sunsetted with sufficient communication to users. Thus we will check in with maintainers annually about maintenance.
Thank you in advance for doing this and supporting pyOpenSci.
lwasser
commented
1 year ago hey there @cosmicBboy @mbjoseph 👋 Just a friendly reminder to take 5-10 minutes to fill out our survey . We really appreciate it. Thank you in advance for helping us by filling out the survey!! 🙌 Niels, it's really important for us to collect information from our maintainers so that we can both stay in touch with you regarding package maintenance and also support you through time. We really appreciate your time in filling this out. Also are you the sole maintainer of this package? if not, please have your co-maintainers also fill it out and please list them here as well. Many thanks in advance!
✨ Ivan you only need to do this once :) ping me on slack with any questions!! 🙌
lwasser
commented
1 year ago hi again @cosmicBboy and @mbjoseph i'd be super appreciative if your filling our our survey
I know you are busy and Niels I know you have super exciting job transition life happening now. But i'd appreciate your time. We'd like to check in with maintainers once a year to ensure all is well with package maintenance. Also your input on the survey helps us improve and show funders we are doing good things! Many thanks for your time!
cosmicBboy
commented
1 year ago just filled it out!
lwasser
commented
1 year ago You rock!! thanks Niels!
NickleDave
commented
1 year ago Hi @cosmicBboy we are updating our metadata to be consistent.
When you have a second, can you please confirm for me that at the time of this review you were the only core maintainer? I have added that in the "all current maintainers" field above (as in #109)
cosmicBboy
commented
1 year ago Hi @NickleDave sorry for the late response 😅
can you please confirm for me that at the time of this review you were the only core maintainer? Yes, confirmed
Submitting Author: Niels Bantilan (@cosmicbboy) All current maintainers: (@cosmicbboy) Package Name: pandera One-Line Description of Package: validate the types, properties, and statistics of pandas data structures Repository Link: https://github.com/unionai-oss/pandera Version submitted: 0.1.5 Editor: @lwasser Reviewer 1: @mbjoseph Reviewer 2: @xmnlab Archive: https://github.com/pandera-dev/pandera/releases/tag/v0.2.3 Version accepted: v0.2.3 Date Accepted: 10/10/2019
Description
pandasdata structures can hide a lot of information, and explicitly validating them at runtime in production-critical or reproducible research settings is a good idea for building reliable data transformation pipelines.panderaenables users to:DataFrameor values in aSeries.panderaprovides a flexible and expressive API for performing data validation on tidy (long-form) and wide data to make data processing pipelines more readable and robust.Scope
* Please fill out a pre-submission inquiry before submitting a data visualization package. For more info, see this section of our guidebook.
Data munging: the package makes ETL, data analysis, and data processing pipelines more robust and reliable by providing users with tools to validate assumptions about the schema and statistical properties of datasets. This package supports validation on long (tidy) data and wide data.
Reproducibility: This package enables users to validate
DataFrameorSeriesobjects at runtime or as unit/integration tests, and can easily be integrated to existing pipelines using thecheck_inputandcheck_outputdecorators. It also supports collaboration and reproducible research by programmatically enforcing assertions made about the statistical properties of a dataset in addition to making it easier to review pandas code in production-critical contexts.The target audience of
panderaconsist of data scientists, data engineers, machine learning engineers, and machine learning scientists who usepandasin their data processing pipelines for various purposes e.g., transforming data for reporting, analytics, model training, and data visualization. This tool is built on top ofpandasandscipyto provide a user-friendly interface for explicitly specifying the set of properties that aDataFrameorSeriesmust fulfill in order to be considered valid. Sincepanderamakes no assumptions about the domain of study or contents of thesepandasdata structures, it could be used in a wide variety of quantitative fields that involve the analysis of tabular data.There are a few alternatives to pandera in the the Python ecosystem and here is how they compare:
EnforcerandColumnobjects are very similar to pandera, but it's a little difficult to followKey differentiators of pandera:
column data types, nullability, and uniqueness are first-class concepts.
check_inputandcheck_outputdecorators enable seamless integration with existing code.Checks provide flexibility and performance by providing access topandasAPI by design.Hypothesisclass provides a tidy-first interface for statistical hypothesis testing.Checks andHypothesisobjects support both tidy and wide data validation.Comprehensive documentation on key functionality.
If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or
@tagthe editor you contacted:https://pyopensci.discourse.group/t/candidate-package-pandera-a-flexible-pandas-data-structure-validation-package/92
Technical checks
For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:
Publication options
JOSS Checks
- [ ] The package has an **obvious research application** according to JOSS's definition in their [submission requirements](https://joss.readthedocs.io/en/latest/submitting.html#submission-requirements). Be aware that completing the pyOpenSci review process **does not** guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS. - [ ] The package is not a "minor utility" as defined by JOSS's [submission requirements](https://joss.readthedocs.io/en/latest/submitting.html#submission-requirements): "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria. - [ ] The package contains a `paper.md` matching [JOSS's requirements](https://joss.readthedocs.io/en/latest/submitting.html#what-should-my-paper-contain) with a high-level description in the package root or in `inst/`. - [ ] The package is deposited in a long-term repository with the DOI: *Note: Do not submit your package separately to JOSS*Are you OK with Reviewers Submitting Issues to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
Code of conduct
P.S. Have feedback/comments about our review process? Leave a comment here
Editor and Review Templates
Editor and review templates can be found here
Previous Repo: https://github.com/cosmicBboy/pandera