mirror of
https://github.com/gristlabs/grist-core.git
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9fffb491f9
Summary: Adds a Python function `REQUEST` which makes an HTTP GET request. Behind the scenes it: - Raises a special exception to stop trying to evaluate the current cell and just keep the existing value. - Notes the request arguments which will be returned by `apply_user_actions`. - Makes the actual request in NodeJS, which sends back the raw response data in a new action `RespondToRequests` which reevaluates the cell(s) that made the request. - Wraps the response data in a class which mimics the `Response` class of the `requests` library. In certain cases, this asynchronous flow doesn't work and the sandbox will instead synchronously call an exported JS method: - When reevaluating a single cell to get a formula error, the request is made synchronously. - When a formula makes multiple requests, the earlier responses are retrieved synchronously from files which store responses as long as needed to complete evaluating formulas. See https://grist.slack.com/archives/CL1LQ8AT0/p1653399747810139 Test Plan: Added Python and nbrowser tests. Reviewers: georgegevoian Reviewed By: georgegevoian Subscribers: paulfitz, dsagal Differential Revision: https://phab.getgrist.com/D3429
145 lines
4.4 KiB
Python
145 lines
4.4 KiB
Python
"""
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This module defines what sandbox functions are made available to the Node controller,
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and starts the grist sandbox. See engine.py for the API documentation.
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"""
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import os
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import sys
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sys.path.append('thirdparty')
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# pylint: disable=wrong-import-position
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import logging
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import marshal
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import functools
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import six
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import actions
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import engine
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import migrations
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import schema
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import useractions
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import objtypes
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from acl_formula import parse_acl_formula
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from sandbox import get_default_sandbox
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from imports.register import register_import_parsers
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import logger
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log = logger.Logger(__name__, logger.INFO)
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# Configure logging module to behave similarly to logger. (It may be OK to get rid of logger.)
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logging.basicConfig(format="[%(levelname)s] [%(name)s] %(message)s")
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def table_data_from_db(table_name, table_data_repr):
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if table_data_repr is None:
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return actions.TableData(table_name, [], {})
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table_data_parsed = marshal.loads(table_data_repr)
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table_data_parsed = {key.decode("utf8"): value for key, value in table_data_parsed.items()}
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id_col = table_data_parsed.pop("id")
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return actions.TableData(table_name, id_col,
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actions.decode_bulk_values(table_data_parsed, _decode_db_value))
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def _decode_db_value(value):
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# Decode database values received from SQLite's allMarshal() call. These are encoded by
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# marshalling certain types and storing as BLOBs (received in Python as binary strings, as
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# opposed to text which is received as unicode). See also encodeValue() in DocStorage.js
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t = type(value)
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if t == six.binary_type:
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return objtypes.decode_object(marshal.loads(value))
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else:
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return value
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def run(sandbox):
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eng = engine.Engine()
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def export(method):
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# Wrap each method so that it logs a message that it's being called.
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@functools.wraps(method)
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def wrapper(*args, **kwargs):
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log.debug("calling %s" % method.__name__)
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return method(*args, **kwargs)
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sandbox.register(method.__name__, wrapper)
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def load_and_record_table_data(table_name, table_data_repr):
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result = table_data_from_db(table_name, table_data_repr)
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eng.record_table_stats(result, table_data_repr)
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return result
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@export
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def apply_user_actions(action_reprs, user=None):
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action_group = eng.apply_user_actions([useractions.from_repr(u) for u in action_reprs], user)
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result = dict(
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rowCount=eng.count_rows(),
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**eng.acl_split(action_group).to_json_obj()
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)
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if action_group.requests:
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result["requests"] = action_group.requests
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return result
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@export
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def fetch_table(table_id, formulas=True, query=None):
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return actions.get_action_repr(eng.fetch_table(table_id, formulas=formulas, query=query))
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@export
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def fetch_table_schema():
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return eng.fetch_table_schema()
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@export
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def autocomplete(txt, table_id, column_id, user):
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return eng.autocomplete(txt, table_id, column_id, user)
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@export
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def find_col_from_values(values, n, opt_table_id):
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return eng.find_col_from_values(values, n, opt_table_id)
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@export
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def fetch_meta_tables(formulas=True):
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return {table_id: actions.get_action_repr(table_data)
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for (table_id, table_data) in six.iteritems(eng.fetch_meta_tables(formulas))}
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@export
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def load_meta_tables(meta_tables, meta_columns):
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return eng.load_meta_tables(load_and_record_table_data("_grist_Tables", meta_tables),
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load_and_record_table_data("_grist_Tables_column", meta_columns))
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@export
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def load_table(table_name, table_data):
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return eng.load_table(load_and_record_table_data(table_name, table_data))
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@export
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def get_table_stats():
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return eng.get_table_stats()
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@export
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def create_migrations(all_tables, metadata_only=False):
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doc_actions = migrations.create_migrations(
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{t: table_data_from_db(t, data) for t, data in six.iteritems(all_tables)}, metadata_only)
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return [actions.get_action_repr(action) for action in doc_actions]
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@export
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def get_version():
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return schema.SCHEMA_VERSION
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@export
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def set_doc_url(doc_url):
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os.environ['DOC_URL'] = doc_url
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@export
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def get_formula_error(table_id, col_id, row_id):
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return objtypes.encode_object(eng.get_formula_error(table_id, col_id, row_id))
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export(parse_acl_formula)
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export(eng.load_empty)
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export(eng.load_done)
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register_import_parsers(sandbox)
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log.info("Ready") # This log message is significant for checkpointing.
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sandbox.run()
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def main():
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run(get_default_sandbox())
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if __name__ == "__main__":
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main()
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