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Implement NCMEC Upvote/Downvote in reference API #1624
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UPDATE_FEEDBACK_RESULT_XML = """ | ||
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> | ||
<submissionResult xmlns="https://hashsharing.ncmec.org/hashsharing/v2"> | ||
<!-- What this returns is not documented --> |
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Looks like a good start. Once the CI is passing, let me know and I'll test it with some real credentials to confirm it works as expected.
from threatexchange.exchanges.clients.utils.common import TimeoutHTTPAdapter | ||
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_DATE_FORMAT_STR = "%Y-%m-%dT%H:%M:%SZ" | ||
_DEFAULT_ELE = ET.Element("") | ||
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T = t.TypeVar("T") | ||
FEEDBACK = t.List[t.Dict[str, str]] |
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blocking: ALL_CAPS usually denotes a constant. In this case, your type is simple enough that you should just inline it.
@@ -131,6 +132,7 @@ class NCMECEntryUpdate: | |||
deleted: bool | |||
classification: t.Optional[str] | |||
fingerprints: t.Dict[str, str] | |||
feedback: t.Optional[FEEDBACK] |
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blocking: We should not use optional here, because empty dictionary expresses the same thing
@@ -148,6 +150,18 @@ def from_xml(cls, xml: _XMLWrapper) -> "NCMECEntryUpdate": | |||
fingerprints={ | |||
x.tag: x.text for x in xml.maybe("fingerprints") if x.has_text | |||
}, | |||
feedback=[ |
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blocking; Your type says dict, your code says list!
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type is t.List[t.Dict[str, str]]
@@ -401,6 +432,14 @@ def get_entries_iter( | |||
has_more = bool(next_) | |||
yield result | |||
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# TODO: split into 2, submit upvote and downvote | |||
def submit_feedback(self, entry_id: str, is_good: bool) -> GetEntriesResponse: |
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unsure: This API also needs the ESP ID, no?
@@ -401,6 +432,14 @@ def get_entries_iter( | |||
has_more = bool(next_) | |||
yield result | |||
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# TODO: split into 2, submit upvote and downvote |
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blocking; Yup
send_upvote(...):
send_downvote(...):
python-threatexchange/threatexchange/exchanges/clients/ncmec/tests/data.py
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NEXT_UNESCAPED2 = ( | ||
"/v2/entries?from=2017-10-20T00%3A00%3A00.000Z" | ||
"&to=2017-10-30T00%3A00%3A00.000Z&start=3001&size=1000&max=4000" | ||
from threatexchange.exchanges.clients.ncmec.tests.data import ( |
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ignorable: Consider importing by module when you are importing many functions.
), | ||
"reasons": x.maybe( | ||
"reasons" | ||
), # "reason" with "guid", "name", "type" | "members" |
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working on expanding members
and reasons
here
@Dcallies this should be testable against the NCMEC API now |
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Thanks for all the hard work @aryzle ! We'll take it from here and test it against the real API and finish it off! You can consider this one done!
@@ -261,15 +343,19 @@ def __init__( | |||
username: str, | |||
password: str, | |||
environment: NCMECEnvironment, | |||
member_id: t.Optional[str] = None, | |||
reasons_map: t.Dict[str, t.List[t.Dict[str, str]]] = {}, |
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blocking: We won't know this at client construction time, and can poll it afterwards.
) -> None: | ||
assert is_valid_user_pass(username, password) | ||
self.username = username | ||
self.password = password | ||
self._base_url = environment.value | ||
self.member_id = member_id | ||
self.reasons_map = reasons_map or {} |
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Hmm this or {}
is fairly subtle. I'm assuming we are doing it because the default is {}
which is a shared instance across any object, and the or {}
will replace it with a new instance per call, but having it be optional and default to None
is more easy to prove doesn't have a bug.
if not affirmative and not reason_id: | ||
raise ValueError("Negative feedback must have a reason_id") |
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(note to self): If reason map only has one item in it, choose that item. Also test NCMEC API to make sure it won't accept empty reason, which should be our pref otherwise.
@@ -123,6 +123,19 @@ class NCMECEntryType(Enum): | |||
video = "video" | |||
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@unique | |||
class NCMECFeedbackType(Enum): |
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(note to self): Add note that these are also the entry types
@@ -131,6 +144,7 @@ class NCMECEntryUpdate: | |||
deleted: bool | |||
classification: t.Optional[str] | |||
fingerprints: t.Dict[str, str] | |||
feedback: t.List[t.Dict[str, t.Any]] |
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(note to self): Consider whether it makes sense to use the enum here, or whether to leave as string in all cases
"members": [ | ||
{"id": m.str("id"), "name": m.text} | ||
for m in x.maybe("members") | ||
if m.has_text | ||
], |
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(note to self): Should this be dict instead of synthesizing a a dict? What about a dedicated class?
{ | ||
"guid": reason.str("guid"), | ||
"name": reason.str("name"), | ||
"type": reason.str("type"), | ||
} |
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(note to self): Use a dedicated class here instead of dict
entry_id: str, | ||
feedback_type: NCMECFeedbackType, | ||
affirmative: bool, | ||
reason_id: t.Optional[str] = None, |
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(note to self): Is a reason string better to use here than the guid?
Continuing in #1648 - there's probably a way to have re-used this number, but I don't know it :/ |
Summary
Implement NCMEC Upvote/Downvote in reference API
docs: https://report.cybertip.org/hashsharing/v2/documentation/#working-with-feedback
fixes #1614
Test Plan