meerschaum
Meerschaum Python API
Welcome to the Meerschaum Python API technical documentation! Here you can find information about the classes and functions provided by the meerschaum
package. Visit meerschaum.io for general usage documentation.
Root Module
For your convenience, the following classes and functions may be imported from the root meerschaum
namespace:
Classes
Examples
Build a Connector
Get existing connectors or build a new one in-memory with the meerschaum.get_connector()
factory function:
import meerschaum as mrsm
sql_conn = mrsm.get_connector(
'sql:temp',
flavor='sqlite',
database='/tmp/tmp.db',
)
df = sql_conn.read("SELECT 1 AS foo")
print(df)
# foo
# 0 1
sql_conn.to_sql(df, 'foo')
print(sql_conn.read('foo'))
# foo
# 0 1
Create a Custom Connector Class
Decorate your connector classes with meerschaum.make_connector()
to designate it as a custom connector:
from datetime import datetime, timezone
from random import randint
import meerschaum as mrsm
from meerschaum.utils.misc import round_time
@mrsm.make_connector
class FooConnector(mrsm.Connector):
REQUIRED_ATTRIBUTES = ['username', 'password']
def fetch(
self,
begin: datetime | None = None,
end: datetime | None = None,
):
now = begin or round_time(datetime.now(timezone.utc))
return [
{'ts': now, 'id': 1, 'vl': randint(1, 100)},
{'ts': now, 'id': 2, 'vl': randint(1, 100)},
{'ts': now, 'id': 3, 'vl': randint(1, 100)},
]
foo_conn = mrsm.get_connector(
'foo:bar',
username='foo',
password='bar',
)
docs = foo_conn.fetch()
Build a Pipe
Build a meerschaum.Pipe
in-memory:
from datetime import datetime
import meerschaum as mrsm
pipe = mrsm.Pipe(
foo_conn, 'demo',
instance=sql_conn,
columns={'datetime': 'ts', 'id': 'id'},
tags=['production'],
)
pipe.sync(begin=datetime(2024, 1, 1))
df = pipe.get_data()
print(df)
# ts id vl
# 0 2024-01-01 1 97
# 1 2024-01-01 2 18
# 2 2024-01-01 3 96
Add temporary=True
to skip registering the pipe in the pipes table.
Get Registered Pipes
The meerschaum.get_pipes()
function returns a dictionary hierarchy of pipes by connector, metric, and location:
import meerschaum as mrsm
pipes = mrsm.get_pipes(instance='sql:temp')
pipe = pipes['foo:bar']['demo'][None]
Add as_list=True
to flatten the hierarchy:
import meerschaum as mrsm
pipes = mrsm.get_pipes(
tags=['production'],
instance=sql_conn,
as_list=True,
)
print(pipes)
# [Pipe('foo:bar', 'demo', instance='sql:temp')]
Import Plugins
You can import a plugin's module through meerschaum.Plugin.module
:
import meerschaum as mrsm
plugin = mrsm.Plugin('noaa')
with mrsm.Venv(plugin):
noaa = plugin.module
If your plugin has submodules, use meerschaum.plugins.from_plugin_import
:
from meerschaum.plugins import from_plugin_import
get_defined_pipes = from_plugin_import('compose.utils.pipes', 'get_defined_pipes')
Import multiple plugins with meerschaum.plugins.import_plugins
:
from meerschaum.plugins import import_plugins
noaa, compose = import_plugins('noaa', 'compose')
Create a Job
Create a meerschaum.Job
with name
and sysargs
:
import meerschaum as mrsm
job = mrsm.Job('syncing-engine', 'sync pipes --loop')
success, msg = job.start()
Pass executor_keys
as the connectors keys of an API instance to create a remote job:
import meerschaum as mrsm
job = mrsm.Job(
'foo',
'sync pipes -s daily',
executor_keys='api:main',
)
Import from a Virtual Environment
Use the meerschaum.Venv
context manager to activate a virtual environment:
import meerschaum as mrsm
with mrsm.Venv('noaa'):
import requests
print(requests.__file__)
# /home/bmeares/.config/meerschaum/venvs/noaa/lib/python3.12/site-packages/requests/__init__.py
To import packages which may not be installed, use meerschaum.attempt_import()
:
import meerschaum as mrsm
requests = mrsm.attempt_import('requests', venv='noaa')
print(requests.__file__)
# /home/bmeares/.config/meerschaum/venvs/noaa/lib/python3.12/site-packages/requests/__init__.py
Run Actions
Run sysargs
with meerschaum.entry()
:
import meerschaum as mrsm
success, msg = mrsm.entry('show pipes + show version : x2')
Use meerschaum.actions.get_action()
to access an action function directly:
from meerschaum.actions import get_action
show_pipes = get_action(['show', 'pipes'])
success, msg = show_pipes(connector_keys=['plugin:noaa'])
Get a dictionary of available subactions with meerschaum.actions.get_subactions()
:
from meerschaum.actions import get_subactions
subactions = get_subactions('show')
success, msg = subactions['pipes']()
Create a Plugin
Run bootstrap plugin
to create a new plugin:
mrsm bootstrap plugin example
This will create example.py
in your plugins directory (default ~/.config/meerschaum/plugins/
, Windows: %APPDATA%\Meerschaum\plugins
). You may paste the example code from the "Create a Custom Action" example below.
Open your plugin with edit plugin
:
mrsm edit plugin example
Run edit plugin
and paste the example code below to try out the features.
See the writing plugins guide for more in-depth documentation.
Create a Custom Action
Decorate a function with meerschaum.actions.make_action
to designate it as an action. Subactions will be automatically detected if not decorated:
from meerschaum.actions import make_action
@make_action
def sing():
print('What would you like me to sing?')
return True, "Success"
def sing_tune():
return False, "I don't know that song!"
def sing_song():
print('Hello, World!')
return True, "Success"
Use meerschaum.plugins.add_plugin_argument()
to create new parameters for your action:
from meerschaum.plugins import make_action, add_plugin_argument
add_plugin_argument(
'--song', type=str, help='What song to sing.',
)
@make_action
def sing_melody(action=None, song=None):
to_sing = action[0] if action else song
if not to_sing:
return False, "Please tell me what to sing!"
return True, f'~I am singing {to_sing}~'
mrsm sing melody lalala
mrsm sing melody --song do-re-mi
Add a Page to the Web Dashboard
Use the decorators meerschaum.plugins.dash_plugin()
and meerschaum.plugins.web_page()
to add new pages to the web dashboard:
from meerschaum.plugins import dash_plugin, web_page
@dash_plugin
def init_dash(dash_app):
import dash.html as html
import dash_bootstrap_components as dbc
from dash import Input, Output, no_update
### Routes to '/dash/my-page'
@web_page('/my-page', login_required=False)
def my_page():
return dbc.Container([
html.H1("Hello, World!"),
dbc.Button("Click me", id='my-button'),
html.Div(id="my-output-div"),
])
@dash_app.callback(
Output('my-output-div', 'children'),
Input('my-button', 'n_clicks'),
)
def my_button_click(n_clicks):
if not n_clicks:
return no_update
return html.P(f'You clicked {n_clicks} times!')
Submodules
meerschaum.actions
Access functions for actions and subactions.
meerschaum.actions.actions
meerschaum.actions.get_action()
meerschaum.actions.get_completer()
meerschaum.actions.get_main_action_name()
meerschaum.actions.get_subactions()
meerschaum.config
Read and write the Meerschaum configuration registry.
meerschaum.config.get_config()
meerschaum.config.get_plugin_config()
meerschaum.config.write_config()
meerschaum.config.write_plugin_config()
meerschaum.connectors
Build connectors to interact with databases and fetch data.
meerschaum.connectors.get_connector()
meerschaum.connectors.make_connector()
meerschaum.connectors.is_connected()
meerschaum.connectors.poll.retry_connect()
meerschaum.connectors.Connector
meerschaum.connectors.sql.SQLConnector
meerschaum.connectors.api.APIConnector
meerschaum.connectors.valkey.ValkeyConnector
meerschaum.jobs
Start background jobs.
meerschaum.jobs.Job
meerschaum.jobs.Executor
meerschaum.jobs.systemd.SystemdExecutor
meerschaum.jobs.get_jobs()
meerschaum.jobs.get_filtered_jobs()
meerschaum.jobs.get_running_jobs()
meerschaum.jobs.get_stopped_jobs()
meerschaum.jobs.get_paused_jobs()
meerschaum.jobs.get_restart_jobs()
meerschaum.jobs.make_executor()
meerschaum.jobs.check_restart_jobs()
meerschaum.jobs.start_check_jobs_thread()
meerschaum.jobs.stop_check_jobs_thread()
meerschaum.plugins
Access plugin modules and other API utilties.
meerschaum.plugins.Plugin
meerschaum.plugins.api_plugin()
meerschaum.plugins.dash_plugin()
meerschaum.plugins.import_plugins()
meerschaum.plugins.reload_plugins()
meerschaum.plugins.get_plugins()
meerschaum.plugins.get_data_plugins()
meerschaum.plugins.add_plugin_argument()
meerschaum.plugins.pre_sync_hook()
meerschaum.plugins.post_sync_hook()
meerschaum.utils
Utility functions are available in several submodules:
meerschaum.utils.daemon.daemon_entry()
meerschaum.utils.daemon.daemon_action()
meerschaum.utils.daemon.get_daemons()
meerschaum.utils.daemon.get_daemon_ids()
meerschaum.utils.daemon.get_running_daemons()
meerschaum.utils.daemon.get_paused_daemons()
meerschaum.utils.daemon.get_stopped_daemons()
meerschaum.utils.daemon.get_filtered_daemons()
meerschaum.utils.daemon.run_daemon()
meerschaum.utils.daemon.Daemon
meerschaum.utils.daemon.FileDescriptorInterceptor
meerschaum.utils.daemon.RotatingFile
meerschaum.utils.daemon
Manage background jobs.
meerschaum.utils.dataframe.add_missing_cols_to_df()
meerschaum.utils.dataframe.df_is_chunk_generator()
meerschaum.utils.dataframe.enforce_dtypes()
meerschaum.utils.dataframe.filter_unseen_df()
meerschaum.utils.dataframe.get_datetime_bound_from_df()
meerschaum.utils.dataframe.get_first_valid_dask_partition()
meerschaum.utils.dataframe.get_json_cols()
meerschaum.utils.dataframe.get_numeric_cols()
meerschaum.utils.dataframe.get_unhashable_cols()
meerschaum.utils.dataframe.parse_df_datetimes()
meerschaum.utils.dataframe.query_df()
meerschaum.utils.dataframe.to_json()
meerschaum.utils.dataframe
Manipulate dataframes.
meerschaum.utils.dtypes.are_dtypes_equal()
meerschaum.utils.dtypes.attempt_cast_to_numeric()
meerschaum.utils.dtypes.is_dtype_numeric()
meerschaum.utils.dtypes.none_if_null()
meerschaum.utils.dtypes.quantize_decimal()
meerschaum.utils.dtypes.to_pandas_dtype()
meerschaum.utils.dtypes.value_is_null()
meerschaum.utils.dtypes.sql.get_pd_type_from_db_type()
meerschaum.utils.dtypes.sql.get_db_type_from_pd_type()
meerschaum.utils.dtypes
Work with data types.
meerschaum.utils.formatting.colored()
meerschaum.utils.formatting.extract_stats_from_message()
meerschaum.utils.formatting.fill_ansi()
meerschaum.utils.formatting.get_console()
meerschaum.utils.formatting.highlight_pipes()
meerschaum.utils.formatting.make_header()
meerschaum.utils.formatting.pipe_repr()
meerschaum.utils.formatting.pprint()
meerschaum.utils.formatting.pprint_pipes()
meerschaum.utils.formatting.print_options()
meerschaum.utils.formatting.print_pipes_results()
meerschaum.utils.formatting.print_tuple()
meerschaum.utils.formatting.translate_rich_to_termcolor()
meerschaum.utils.formatting
Format output text.
meerschaum.utils.misc.items_str()
meerschaum.utils.misc.round_time()
meerschaum.utils.misc.is_int()
meerschaum.utils.misc.interval_str()
meerschaum.utils.misc.filter_keywords()
meerschaum.utils.misc.generate_password()
meerschaum.utils.misc.string_to_dict()
meerschaum.utils.misc.iterate_chunks()
meerschaum.utils.misc.timed_input()
meerschaum.utils.misc.replace_pipes_in_dict()
meerschaum.utils.misc.is_valid_email()
meerschaum.utils.misc.string_width()
meerschaum.utils.misc.replace_password()
meerschaum.utils.misc.parse_config_substitution()
meerschaum.utils.misc.edit_file()
meerschaum.utils.misc.get_in_ex_params()
meerschaum.utils.misc.separate_negation_values()
meerschaum.utils.misc.flatten_list()
meerschaum.utils.misc.make_symlink()
meerschaum.utils.misc.is_symlink()
meerschaum.utils.misc.wget()
meerschaum.utils.misc.add_method_to_class()
meerschaum.utils.misc.is_pipe_registered()
meerschaum.utils.misc.get_cols_lines()
meerschaum.utils.misc.sorted_dict()
meerschaum.utils.misc.flatten_pipes_dict()
meerschaum.utils.misc.dict_from_od()
meerschaum.utils.misc.remove_ansi()
meerschaum.utils.misc.get_connector_labels()
meerschaum.utils.misc.json_serialize_datetime()
meerschaum.utils.misc.async_wrap()
meerschaum.utils.misc.is_docker_available()
meerschaum.utils.misc.is_android()
meerschaum.utils.misc.is_bcp_available()
meerschaum.utils.misc.truncate_string_sections()
meerschaum.utils.misc.safely_extract_tar()
meerschaum.utils.misc
Miscellaneous utility functions.
meerschaum.utils.packages.attempt_import()
meerschaum.utils.packages.get_module_path()
meerschaum.utils.packages.manually_import_module()
meerschaum.utils.packages.get_install_no_version()
meerschaum.utils.packages.determine_version()
meerschaum.utils.packages.need_update()
meerschaum.utils.packages.get_pip()
meerschaum.utils.packages.pip_install()
meerschaum.utils.packages.pip_uninstall()
meerschaum.utils.packages.completely_uninstall_package()
meerschaum.utils.packages.run_python_package()
meerschaum.utils.packages.lazy_import()
meerschaum.utils.packages.pandas_name()
meerschaum.utils.packages.import_pandas()
meerschaum.utils.packages.import_rich()
meerschaum.utils.packages.import_dcc()
meerschaum.utils.packages.import_html()
meerschaum.utils.packages.get_modules_from_package()
meerschaum.utils.packages.import_children()
meerschaum.utils.packages.reload_package()
meerschaum.utils.packages.reload_meerschaum()
meerschaum.utils.packages.is_installed()
meerschaum.utils.packages.venv_contains_package()
meerschaum.utils.packages.package_venv()
meerschaum.utils.packages.ensure_readline()
meerschaum.utils.packages.get_prerelease_dependencies()
meerschaum.utils.packages
Manage Python packages.
meerschaum.utils.sql.build_where()
meerschaum.utils.sql.clean()
meerschaum.utils.sql.dateadd_str()
meerschaum.utils.sql.test_connection()
meerschaum.utils.sql.get_distinct_col_count()
meerschaum.utils.sql.sql_item_name()
meerschaum.utils.sql.pg_capital()
meerschaum.utils.sql.oracle_capital()
meerschaum.utils.sql.truncate_item_name()
meerschaum.utils.sql.table_exists()
meerschaum.utils.sql.get_table_cols_types()
meerschaum.utils.sql.get_update_queries()
meerschaum.utils.sql.get_null_replacement()
meerschaum.utils.sql.get_db_version()
meerschaum.utils.sql.get_rename_table_queries()
meerschaum.utils.sql.get_create_table_query()
meerschaum.utils.sql.wrap_query_with_cte()
meerschaum.utils.sql.format_cte_subquery()
meerschaum.utils.sql.session_execute()
meerschaum.utils.sql
Build SQL queries.
meerschaum.utils.venv.Venv
meerschaum.utils.venv.activate_venv()
meerschaum.utils.venv.deactivate_venv()
meerschaum.utils.venv.get_module_venv()
meerschaum.utils.venv.get_venvs()
meerschaum.utils.venv.init_venv()
meerschaum.utils.venv.inside_venv()
meerschaum.utils.venv.is_venv_active()
meerschaum.utils.venv.venv_exec()
meerschaum.utils.venv.venv_executable()
meerschaum.utils.venv.venv_exists()
meerschaum.utils.venv.venv_target_path()
meerschaum.utils.venv.verify_venv()
meerschaum.utils.venv
Manage virtual environments.
meerschaum.utils.warnings
Print warnings, errors, info, and debug messages.
1#! /usr/bin/env python 2# -*- coding: utf-8 -*- 3# vim:fenc=utf-8 4 5""" 6Copyright 2023 Bennett Meares 7 8Licensed under the Apache License, Version 2.0 (the "License"); 9you may not use this file except in compliance with the License. 10You may obtain a copy of the License at 11 12 http://www.apache.org/licenses/LICENSE-2.0 13 14Unless required by applicable law or agreed to in writing, software 15distributed under the License is distributed on an "AS IS" BASIS, 16WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 17See the License for the specific language governing permissions and 18limitations under the License. 19""" 20 21import atexit 22from meerschaum.utils.typing import SuccessTuple 23from meerschaum.utils.packages import attempt_import 24from meerschaum.core.Pipe import Pipe 25from meerschaum.plugins import Plugin 26from meerschaum.utils.venv import Venv 27from meerschaum.jobs import Job, make_executor 28from meerschaum.connectors import get_connector, Connector, make_connector 29from meerschaum.utils import get_pipes 30from meerschaum.utils.formatting import pprint 31from meerschaum._internal.docs import index as __doc__ 32from meerschaum.config import __version__, get_config 33from meerschaum._internal.entry import entry 34from meerschaum.__main__ import _close_pools 35 36atexit.register(_close_pools) 37 38__pdoc__ = {'gui': False, 'api': False, 'core': False, '_internal': False} 39__all__ = ( 40 "get_pipes", 41 "get_connector", 42 "get_config", 43 "Pipe", 44 "Plugin", 45 "Venv", 46 "Plugin", 47 "Job", 48 "pprint", 49 "attempt_import", 50 "actions", 51 "config", 52 "connectors", 53 "jobs", 54 "plugins", 55 "utils", 56 "SuccessTuple", 57 "Connector", 58 "make_connector", 59 "entry", 60)
19def get_pipes( 20 connector_keys: Union[str, List[str], None] = None, 21 metric_keys: Union[str, List[str], None] = None, 22 location_keys: Union[str, List[str], None] = None, 23 tags: Optional[List[str]] = None, 24 params: Optional[Dict[str, Any]] = None, 25 mrsm_instance: Union[str, InstanceConnector, None] = None, 26 instance: Union[str, InstanceConnector, None] = None, 27 as_list: bool = False, 28 method: str = 'registered', 29 debug: bool = False, 30 **kw: Any 31) -> Union[PipesDict, List[mrsm.Pipe]]: 32 """ 33 Return a dictionary or list of `meerschaum.Pipe` objects. 34 35 Parameters 36 ---------- 37 connector_keys: Union[str, List[str], None], default None 38 String or list of connector keys. 39 If omitted or is `'*'`, fetch all possible keys. 40 If a string begins with `'_'`, select keys that do NOT match the string. 41 42 metric_keys: Union[str, List[str], None], default None 43 String or list of metric keys. See `connector_keys` for formatting. 44 45 location_keys: Union[str, List[str], None], default None 46 String or list of location keys. See `connector_keys` for formatting. 47 48 tags: Optional[List[str]], default None 49 If provided, only include pipes with these tags. 50 51 params: Optional[Dict[str, Any]], default None 52 Dictionary of additional parameters to search by. 53 Params are parsed into a SQL WHERE clause. 54 E.g. `{'a': 1, 'b': 2}` equates to `'WHERE a = 1 AND b = 2'` 55 56 mrsm_instance: Union[str, InstanceConnector, None], default None 57 Connector keys for the Meerschaum instance of the pipes. 58 Must be a `meerschaum.connectors.sql.SQLConnector.SQLConnector` or 59 `meerschaum.connectors.api.APIConnector.APIConnector`. 60 61 as_list: bool, default False 62 If `True`, return pipes in a list instead of a hierarchical dictionary. 63 `False` : `{connector_keys: {metric_key: {location_key: Pipe}}}` 64 `True` : `[Pipe]` 65 66 method: str, default 'registered' 67 Available options: `['registered', 'explicit', 'all']` 68 If `'registered'` (default), create pipes based on registered keys in the connector's pipes table 69 (API or SQL connector, depends on mrsm_instance). 70 If `'explicit'`, create pipes from provided connector_keys, metric_keys, and location_keys 71 instead of consulting the pipes table. Useful for creating non-existent pipes. 72 If `'all'`, create pipes from predefined metrics and locations. Required `connector_keys`. 73 **NOTE:** Method `'all'` is not implemented! 74 75 **kw: Any: 76 Keyword arguments to pass to the `meerschaum.Pipe` constructor. 77 78 79 Returns 80 ------- 81 A dictionary of dictionaries and `meerschaum.Pipe` objects 82 in the connector, metric, location hierarchy. 83 If `as_list` is `True`, return a list of `meerschaum.Pipe` objects. 84 85 Examples 86 -------- 87 ``` 88 >>> ### Manual definition: 89 >>> pipes = { 90 ... <connector_keys>: { 91 ... <metric_key>: { 92 ... <location_key>: Pipe( 93 ... <connector_keys>, 94 ... <metric_key>, 95 ... <location_key>, 96 ... ), 97 ... }, 98 ... }, 99 ... }, 100 >>> ### Accessing a single pipe: 101 >>> pipes['sql:main']['weather'][None] 102 >>> ### Return a list instead: 103 >>> get_pipes(as_list=True) 104 [sql_main_weather] 105 >>> 106 ``` 107 """ 108 109 from meerschaum.config import get_config 110 from meerschaum.utils.warnings import error 111 from meerschaum.utils.misc import filter_keywords 112 113 if connector_keys is None: 114 connector_keys = [] 115 if metric_keys is None: 116 metric_keys = [] 117 if location_keys is None: 118 location_keys = [] 119 if params is None: 120 params = {} 121 if tags is None: 122 tags = [] 123 124 if isinstance(connector_keys, str): 125 connector_keys = [connector_keys] 126 if isinstance(metric_keys, str): 127 metric_keys = [metric_keys] 128 if isinstance(location_keys, str): 129 location_keys = [location_keys] 130 131 ### Get SQL or API connector (keys come from `connector.fetch_pipes_keys()`). 132 if mrsm_instance is None: 133 mrsm_instance = instance 134 if mrsm_instance is None: 135 mrsm_instance = get_config('meerschaum', 'instance', patch=True) 136 if isinstance(mrsm_instance, str): 137 from meerschaum.connectors.parse import parse_instance_keys 138 connector = parse_instance_keys(keys=mrsm_instance, debug=debug) 139 else: 140 from meerschaum.connectors import instance_types 141 valid_connector = False 142 if hasattr(mrsm_instance, 'type'): 143 if mrsm_instance.type in instance_types: 144 valid_connector = True 145 if not valid_connector: 146 error(f"Invalid instance connector: {mrsm_instance}") 147 connector = mrsm_instance 148 if debug: 149 from meerschaum.utils.debug import dprint 150 dprint(f"Using instance connector: {connector}") 151 if not connector: 152 error(f"Could not create connector from keys: '{mrsm_instance}'") 153 154 ### Get a list of tuples for the keys needed to build pipes. 155 result = fetch_pipes_keys( 156 method, 157 connector, 158 connector_keys = connector_keys, 159 metric_keys = metric_keys, 160 location_keys = location_keys, 161 tags = tags, 162 params = params, 163 debug = debug 164 ) 165 if result is None: 166 error(f"Unable to build pipes!") 167 168 ### Populate the `pipes` dictionary with Pipes based on the keys 169 ### obtained from the chosen `method`. 170 from meerschaum import Pipe 171 pipes = {} 172 for ck, mk, lk in result: 173 if ck not in pipes: 174 pipes[ck] = {} 175 176 if mk not in pipes[ck]: 177 pipes[ck][mk] = {} 178 179 pipes[ck][mk][lk] = Pipe( 180 ck, mk, lk, 181 mrsm_instance = connector, 182 debug = debug, 183 **filter_keywords(Pipe, **kw) 184 ) 185 186 if not as_list: 187 return pipes 188 from meerschaum.utils.misc import flatten_pipes_dict 189 return flatten_pipes_dict(pipes)
Return a dictionary or list of meerschaum.Pipe
objects.
Parameters
- connector_keys (Union[str, List[str], None], default None):
String or list of connector keys.
If omitted or is
'*'
, fetch all possible keys. If a string begins with'_'
, select keys that do NOT match the string. - metric_keys (Union[str, List[str], None], default None):
String or list of metric keys. See
connector_keys
for formatting. - location_keys (Union[str, List[str], None], default None):
String or list of location keys. See
connector_keys
for formatting. - tags (Optional[List[str]], default None): If provided, only include pipes with these tags.
- params (Optional[Dict[str, Any]], default None):
Dictionary of additional parameters to search by.
Params are parsed into a SQL WHERE clause.
E.g.
{'a': 1, 'b': 2}
equates to'WHERE a = 1 AND b = 2'
- mrsm_instance (Union[str, InstanceConnector, None], default None):
Connector keys for the Meerschaum instance of the pipes.
Must be a
meerschaum.connectors.sql.SQLConnector.SQLConnector
ormeerschaum.connectors.api.APIConnector.APIConnector
. - as_list (bool, default False):
If
True
, return pipes in a list instead of a hierarchical dictionary.False
:{connector_keys: {metric_key: {location_key: Pipe}}}
True
:[Pipe]
- method (str, default 'registered'):
Available options:
['registered', 'explicit', 'all']
If'registered'
(default), create pipes based on registered keys in the connector's pipes table (API or SQL connector, depends on mrsm_instance). If'explicit'
, create pipes from provided connector_keys, metric_keys, and location_keys instead of consulting the pipes table. Useful for creating non-existent pipes. If'all'
, create pipes from predefined metrics and locations. Requiredconnector_keys
. NOTE: Method'all'
is not implemented! - **kw (Any:):
Keyword arguments to pass to the
meerschaum.Pipe
constructor.
Returns
- A dictionary of dictionaries and
meerschaum.Pipe
objects - in the connector, metric, location hierarchy.
- If
as_list
isTrue
, return a list ofmeerschaum.Pipe
objects.
Examples
>>> ### Manual definition:
>>> pipes = {
... <connector_keys>: {
... <metric_key>: {
... <location_key>: Pipe(
... <connector_keys>,
... <metric_key>,
... <location_key>,
... ),
... },
... },
... },
>>> ### Accessing a single pipe:
>>> pipes['sql:main']['weather'][None]
>>> ### Return a list instead:
>>> get_pipes(as_list=True)
[sql_main_weather]
>>>
80def get_connector( 81 type: str = None, 82 label: str = None, 83 refresh: bool = False, 84 debug: bool = False, 85 **kw: Any 86) -> Connector: 87 """ 88 Return existing connector or create new connection and store for reuse. 89 90 You can create new connectors if enough parameters are provided for the given type and flavor. 91 92 93 Parameters 94 ---------- 95 type: Optional[str], default None 96 Connector type (sql, api, etc.). 97 Defaults to the type of the configured `instance_connector`. 98 99 label: Optional[str], default None 100 Connector label (e.g. main). Defaults to `'main'`. 101 102 refresh: bool, default False 103 Refresh the Connector instance / construct new object. Defaults to `False`. 104 105 kw: Any 106 Other arguments to pass to the Connector constructor. 107 If the Connector has already been constructed and new arguments are provided, 108 `refresh` is set to `True` and the old Connector is replaced. 109 110 Returns 111 ------- 112 A new Meerschaum connector (e.g. `meerschaum.connectors.api.APIConnector`, 113 `meerschaum.connectors.sql.SQLConnector`). 114 115 Examples 116 -------- 117 The following parameters would create a new 118 `meerschaum.connectors.sql.SQLConnector` that isn't in the configuration file. 119 120 ``` 121 >>> conn = get_connector( 122 ... type = 'sql', 123 ... label = 'newlabel', 124 ... flavor = 'sqlite', 125 ... database = '/file/path/to/database.db' 126 ... ) 127 >>> 128 ``` 129 130 """ 131 from meerschaum.connectors.parse import parse_instance_keys 132 from meerschaum.config import get_config 133 from meerschaum.config.static import STATIC_CONFIG 134 from meerschaum.utils.warnings import warn 135 global _loaded_plugin_connectors 136 if isinstance(type, str) and not label and ':' in type: 137 type, label = type.split(':', maxsplit=1) 138 139 with _locks['_loaded_plugin_connectors']: 140 if not _loaded_plugin_connectors: 141 load_plugin_connectors() 142 _load_builtin_custom_connectors() 143 _loaded_plugin_connectors = True 144 145 if type is None and label is None: 146 default_instance_keys = get_config('meerschaum', 'instance', patch=True) 147 ### recursive call to get_connector 148 return parse_instance_keys(default_instance_keys) 149 150 ### NOTE: the default instance connector may not be main. 151 ### Only fall back to 'main' if the type is provided by the label is omitted. 152 label = label if label is not None else STATIC_CONFIG['connectors']['default_label'] 153 154 ### type might actually be a label. Check if so and raise a warning. 155 if type not in connectors: 156 possibilities, poss_msg = [], "" 157 for _type in get_config('meerschaum', 'connectors'): 158 if type in get_config('meerschaum', 'connectors', _type): 159 possibilities.append(f"{_type}:{type}") 160 if len(possibilities) > 0: 161 poss_msg = " Did you mean" 162 for poss in possibilities[:-1]: 163 poss_msg += f" '{poss}'," 164 if poss_msg.endswith(','): 165 poss_msg = poss_msg[:-1] 166 if len(possibilities) > 1: 167 poss_msg += " or" 168 poss_msg += f" '{possibilities[-1]}'?" 169 170 warn(f"Cannot create Connector of type '{type}'." + poss_msg, stack=False) 171 return None 172 173 if 'sql' not in types: 174 from meerschaum.connectors.plugin import PluginConnector 175 from meerschaum.connectors.valkey import ValkeyConnector 176 with _locks['types']: 177 types.update({ 178 'api': APIConnector, 179 'sql': SQLConnector, 180 'plugin': PluginConnector, 181 'valkey': ValkeyConnector, 182 }) 183 184 ### determine if we need to call the constructor 185 if not refresh: 186 ### see if any user-supplied arguments differ from the existing instance 187 if label in connectors[type]: 188 warning_message = None 189 for attribute, value in kw.items(): 190 if attribute not in connectors[type][label].meta: 191 import inspect 192 cls = connectors[type][label].__class__ 193 cls_init_signature = inspect.signature(cls) 194 cls_init_params = cls_init_signature.parameters 195 if attribute not in cls_init_params: 196 warning_message = ( 197 f"Received new attribute '{attribute}' not present in connector " + 198 f"{connectors[type][label]}.\n" 199 ) 200 elif connectors[type][label].__dict__[attribute] != value: 201 warning_message = ( 202 f"Mismatched values for attribute '{attribute}' in connector " 203 + f"'{connectors[type][label]}'.\n" + 204 f" - Keyword value: '{value}'\n" + 205 f" - Existing value: '{connectors[type][label].__dict__[attribute]}'\n" 206 ) 207 if warning_message is not None: 208 warning_message += ( 209 "\nSetting `refresh` to True and recreating connector with type:" 210 + f" '{type}' and label '{label}'." 211 ) 212 refresh = True 213 warn(warning_message) 214 else: ### connector doesn't yet exist 215 refresh = True 216 217 ### only create an object if refresh is True 218 ### (can be manually specified, otherwise determined above) 219 if refresh: 220 with _locks['connectors']: 221 try: 222 ### will raise an error if configuration is incorrect / missing 223 conn = types[type](label=label, **kw) 224 connectors[type][label] = conn 225 except InvalidAttributesError as ie: 226 warn( 227 f"Incorrect attributes for connector '{type}:{label}'.\n" 228 + str(ie), 229 stack = False, 230 ) 231 conn = None 232 except Exception as e: 233 from meerschaum.utils.formatting import get_console 234 console = get_console() 235 if console: 236 console.print_exception() 237 warn( 238 f"Exception when creating connector '{type}:{label}'.\n" + str(e), 239 stack = False, 240 ) 241 conn = None 242 if conn is None: 243 return None 244 245 return connectors[type][label]
Return existing connector or create new connection and store for reuse.
You can create new connectors if enough parameters are provided for the given type and flavor.
Parameters
- type (Optional[str], default None):
Connector type (sql, api, etc.).
Defaults to the type of the configured
instance_connector
. - label (Optional[str], default None):
Connector label (e.g. main). Defaults to
'main'
. - refresh (bool, default False):
Refresh the Connector instance / construct new object. Defaults to
False
. - kw (Any):
Other arguments to pass to the Connector constructor.
If the Connector has already been constructed and new arguments are provided,
refresh
is set toTrue
and the old Connector is replaced.
Returns
- A new Meerschaum connector (e.g.
meerschaum.connectors.api.APIConnector
, meerschaum.connectors.sql.SQLConnector
).
Examples
The following parameters would create a new
meerschaum.connectors.sql.SQLConnector
that isn't in the configuration file.
>>> conn = get_connector(
... type = 'sql',
... label = 'newlabel',
... flavor = 'sqlite',
... database = '/file/path/to/database.db'
... )
>>>
82def get_config( 83 *keys: str, 84 patch: bool = True, 85 substitute: bool = True, 86 sync_files: bool = True, 87 write_missing: bool = True, 88 as_tuple: bool = False, 89 warn: bool = True, 90 debug: bool = False 91) -> Any: 92 """ 93 Return the Meerschaum configuration dictionary. 94 If positional arguments are provided, index by the keys. 95 Raises a warning if invalid keys are provided. 96 97 Parameters 98 ---------- 99 keys: str: 100 List of strings to index. 101 102 patch: bool, default True 103 If `True`, patch missing default keys into the config directory. 104 Defaults to `True`. 105 106 sync_files: bool, default True 107 If `True`, sync files if needed. 108 Defaults to `True`. 109 110 write_missing: bool, default True 111 If `True`, write default values when the main config files are missing. 112 Defaults to `True`. 113 114 substitute: bool, default True 115 If `True`, subsitute 'MRSM{}' values. 116 Defaults to `True`. 117 118 as_tuple: bool, default False 119 If `True`, return a tuple of type (success, value). 120 Defaults to `False`. 121 122 Returns 123 ------- 124 The value in the configuration directory, indexed by the provided keys. 125 126 Examples 127 -------- 128 >>> get_config('meerschaum', 'instance') 129 'sql:main' 130 >>> get_config('does', 'not', 'exist') 131 UserWarning: Invalid keys in config: ('does', 'not', 'exist') 132 """ 133 import json 134 135 symlinks_key = STATIC_CONFIG['config']['symlinks_key'] 136 if debug: 137 from meerschaum.utils.debug import dprint 138 dprint(f"Indexing keys: {keys}", color=False) 139 140 if len(keys) == 0: 141 _rc = _config(substitute=substitute, sync_files=sync_files, write_missing=write_missing) 142 if as_tuple: 143 return True, _rc 144 return _rc 145 146 ### Weird threading issues, only import if substitute is True. 147 if substitute: 148 from meerschaum.config._read_config import search_and_substitute_config 149 ### Invalidate the cache if it was read before with substitute=False 150 ### but there still exist substitutions. 151 if ( 152 config is not None and substitute and keys[0] != symlinks_key 153 and 'MRSM{' in json.dumps(config.get(keys[0])) 154 ): 155 try: 156 _subbed = search_and_substitute_config({keys[0]: config[keys[0]]}) 157 except Exception as e: 158 import traceback 159 traceback.print_exc() 160 config[keys[0]] = _subbed[keys[0]] 161 if symlinks_key in _subbed: 162 if symlinks_key not in config: 163 config[symlinks_key] = {} 164 if keys[0] not in config[symlinks_key]: 165 config[symlinks_key][keys[0]] = {} 166 config[symlinks_key][keys[0]] = apply_patch_to_config( 167 _subbed, 168 config[symlinks_key][keys[0]] 169 ) 170 171 from meerschaum.config._sync import sync_files as _sync_files 172 if config is None: 173 _config(*keys, sync_files=sync_files) 174 175 invalid_keys = False 176 if keys[0] not in config and keys[0] != symlinks_key: 177 single_key_config = read_config( 178 keys=[keys[0]], substitute=substitute, write_missing=write_missing 179 ) 180 if keys[0] not in single_key_config: 181 invalid_keys = True 182 else: 183 config[keys[0]] = single_key_config.get(keys[0], None) 184 if symlinks_key in single_key_config and keys[0] in single_key_config[symlinks_key]: 185 if symlinks_key not in config: 186 config[symlinks_key] = {} 187 config[symlinks_key][keys[0]] = single_key_config[symlinks_key][keys[0]] 188 189 if sync_files: 190 _sync_files(keys=[keys[0]]) 191 192 c = config 193 if len(keys) > 0: 194 for k in keys: 195 try: 196 c = c[k] 197 except Exception as e: 198 invalid_keys = True 199 break 200 if invalid_keys: 201 ### Check if the keys are in the default configuration. 202 from meerschaum.config._default import default_config 203 in_default = True 204 patched_default_config = ( 205 search_and_substitute_config(default_config) 206 if substitute else copy.deepcopy(default_config) 207 ) 208 _c = patched_default_config 209 for k in keys: 210 try: 211 _c = _c[k] 212 except Exception as e: 213 in_default = False 214 if in_default: 215 c = _c 216 invalid_keys = False 217 warning_msg = f"Invalid keys in config: {keys}" 218 if not in_default: 219 try: 220 if warn: 221 from meerschaum.utils.warnings import warn as _warn 222 _warn(warning_msg, stacklevel=3, color=False) 223 except Exception as e: 224 if warn: 225 print(warning_msg) 226 if as_tuple: 227 return False, None 228 return None 229 230 ### Don't write keys that we haven't yet loaded into memory. 231 not_loaded_keys = [k for k in patched_default_config if k not in config] 232 for k in not_loaded_keys: 233 patched_default_config.pop(k, None) 234 235 set_config( 236 apply_patch_to_config( 237 patched_default_config, 238 config, 239 ) 240 ) 241 if patch and keys[0] != symlinks_key: 242 if write_missing: 243 write_config(config, debug=debug) 244 245 if as_tuple: 246 return (not invalid_keys), c 247 return c
Return the Meerschaum configuration dictionary. If positional arguments are provided, index by the keys. Raises a warning if invalid keys are provided.
Parameters
- keys (str:): List of strings to index.
- patch (bool, default True):
If
True
, patch missing default keys into the config directory. Defaults toTrue
. - sync_files (bool, default True):
If
True
, sync files if needed. Defaults toTrue
. - write_missing (bool, default True):
If
True
, write default values when the main config files are missing. Defaults toTrue
. - substitute (bool, default True):
If
True
, subsitute 'MRSM{}' values. Defaults toTrue
. - as_tuple (bool, default False):
If
True
, return a tuple of type (success, value). Defaults toFalse
.
Returns
- The value in the configuration directory, indexed by the provided keys.
Examples
>>> get_config('meerschaum', 'instance')
'sql:main'
>>> get_config('does', 'not', 'exist')
UserWarning: Invalid keys in config: ('does', 'not', 'exist')
60class Pipe: 61 """ 62 Access Meerschaum pipes via Pipe objects. 63 64 Pipes are identified by the following: 65 66 1. Connector keys (e.g. `'sql:main'`) 67 2. Metric key (e.g. `'weather'`) 68 3. Location (optional; e.g. `None`) 69 70 A pipe's connector keys correspond to a data source, and when the pipe is synced, 71 its `fetch` definition is evaluated and executed to produce new data. 72 73 Alternatively, new data may be directly synced via `pipe.sync()`: 74 75 ``` 76 >>> from meerschaum import Pipe 77 >>> pipe = Pipe('csv', 'weather') 78 >>> 79 >>> import pandas as pd 80 >>> df = pd.read_csv('weather.csv') 81 >>> pipe.sync(df) 82 ``` 83 """ 84 85 from ._fetch import ( 86 fetch, 87 get_backtrack_interval, 88 ) 89 from ._data import ( 90 get_data, 91 get_backtrack_data, 92 get_rowcount, 93 _get_data_as_iterator, 94 get_chunk_interval, 95 get_chunk_bounds, 96 ) 97 from ._register import register 98 from ._attributes import ( 99 attributes, 100 parameters, 101 columns, 102 indices, 103 indexes, 104 dtypes, 105 get_columns, 106 get_columns_types, 107 get_indices, 108 tags, 109 get_id, 110 id, 111 get_val_column, 112 parents, 113 children, 114 target, 115 _target_legacy, 116 guess_datetime, 117 ) 118 from ._show import show 119 from ._edit import edit, edit_definition, update 120 from ._sync import ( 121 sync, 122 get_sync_time, 123 exists, 124 filter_existing, 125 _get_chunk_label, 126 get_num_workers, 127 _persist_new_json_columns, 128 _persist_new_numeric_columns, 129 _persist_new_uuid_columns, 130 ) 131 from ._verify import ( 132 verify, 133 get_bound_interval, 134 get_bound_time, 135 ) 136 from ._delete import delete 137 from ._drop import drop 138 from ._clear import clear 139 from ._deduplicate import deduplicate 140 from ._bootstrap import bootstrap 141 from ._dtypes import enforce_dtypes, infer_dtypes 142 from ._copy import copy_to 143 144 def __init__( 145 self, 146 connector: str = '', 147 metric: str = '', 148 location: Optional[str] = None, 149 parameters: Optional[Dict[str, Any]] = None, 150 columns: Union[Dict[str, str], List[str], None] = None, 151 indices: Optional[Dict[str, Union[str, List[str]]]] = None, 152 tags: Optional[List[str]] = None, 153 target: Optional[str] = None, 154 dtypes: Optional[Dict[str, str]] = None, 155 instance: Optional[Union[str, InstanceConnector]] = None, 156 temporary: bool = False, 157 mrsm_instance: Optional[Union[str, InstanceConnector]] = None, 158 cache: bool = False, 159 debug: bool = False, 160 connector_keys: Optional[str] = None, 161 metric_key: Optional[str] = None, 162 location_key: Optional[str] = None, 163 indexes: Union[Dict[str, str], List[str], None] = None, 164 ): 165 """ 166 Parameters 167 ---------- 168 connector: str 169 Keys for the pipe's source connector, e.g. `'sql:main'`. 170 171 metric: str 172 Label for the pipe's contents, e.g. `'weather'`. 173 174 location: str, default None 175 Label for the pipe's location. Defaults to `None`. 176 177 parameters: Optional[Dict[str, Any]], default None 178 Optionally set a pipe's parameters from the constructor, 179 e.g. columns and other attributes. 180 You can edit these parameters with `edit pipes`. 181 182 columns: Union[Dict[str, str], List[str], None], default None 183 Set the `columns` dictionary of `parameters`. 184 If `parameters` is also provided, this dictionary is added under the `'columns'` key. 185 186 indices: Optional[Dict[str, Union[str, List[str]]]], default None 187 Set the `indices` dictionary of `parameters`. 188 If `parameters` is also provided, this dictionary is added under the `'indices'` key. 189 190 tags: Optional[List[str]], default None 191 A list of strings to be added under the `'tags'` key of `parameters`. 192 You can select pipes with certain tags using `--tags`. 193 194 dtypes: Optional[Dict[str, str]], default None 195 Set the `dtypes` dictionary of `parameters`. 196 If `parameters` is also provided, this dictionary is added under the `'dtypes'` key. 197 198 mrsm_instance: Optional[Union[str, InstanceConnector]], default None 199 Connector for the Meerschaum instance where the pipe resides. 200 Defaults to the preconfigured default instance (`'sql:main'`). 201 202 instance: Optional[Union[str, InstanceConnector]], default None 203 Alias for `mrsm_instance`. If `mrsm_instance` is supplied, this value is ignored. 204 205 temporary: bool, default False 206 If `True`, prevent instance tables (pipes, users, plugins) from being created. 207 208 cache: bool, default False 209 If `True`, cache fetched data into a local database file. 210 Defaults to `False`. 211 """ 212 from meerschaum.utils.warnings import error, warn 213 if (not connector and not connector_keys) or (not metric and not metric_key): 214 error( 215 "Please provide strings for the connector and metric\n " 216 + "(first two positional arguments)." 217 ) 218 219 ### Fall back to legacy `location_key` just in case. 220 if not location: 221 location = location_key 222 223 if not connector: 224 connector = connector_keys 225 226 if not metric: 227 metric = metric_key 228 229 if location in ('[None]', 'None'): 230 location = None 231 232 from meerschaum.config.static import STATIC_CONFIG 233 negation_prefix = STATIC_CONFIG['system']['fetch_pipes_keys']['negation_prefix'] 234 for k in (connector, metric, location, *(tags or [])): 235 if str(k).startswith(negation_prefix): 236 error(f"A pipe's keys and tags cannot start with the prefix '{negation_prefix}'.") 237 238 self.connector_keys = str(connector) 239 self.connector_key = self.connector_keys ### Alias 240 self.metric_key = metric 241 self.location_key = location 242 self.temporary = temporary 243 244 self._attributes = { 245 'connector_keys': self.connector_keys, 246 'metric_key': self.metric_key, 247 'location_key': self.location_key, 248 'parameters': {}, 249 } 250 251 ### only set parameters if values are provided 252 if isinstance(parameters, dict): 253 self._attributes['parameters'] = parameters 254 else: 255 if parameters is not None: 256 warn(f"The provided parameters are of invalid type '{type(parameters)}'.") 257 self._attributes['parameters'] = {} 258 259 columns = columns or self._attributes.get('parameters', {}).get('columns', {}) 260 if isinstance(columns, list): 261 columns = {str(col): str(col) for col in columns} 262 if isinstance(columns, dict): 263 self._attributes['parameters']['columns'] = columns 264 elif columns is not None: 265 warn(f"The provided columns are of invalid type '{type(columns)}'.") 266 267 indices = ( 268 indices 269 or indexes 270 or self._attributes.get('parameters', {}).get('indices', None) 271 or self._attributes.get('parameters', {}).get('indexes', None) 272 ) or columns 273 if isinstance(indices, dict): 274 indices_key = ( 275 'indexes' 276 if 'indexes' in self._attributes['parameters'] 277 else 'indices' 278 ) 279 self._attributes['parameters'][indices_key] = indices 280 281 if isinstance(tags, (list, tuple)): 282 self._attributes['parameters']['tags'] = tags 283 elif tags is not None: 284 warn(f"The provided tags are of invalid type '{type(tags)}'.") 285 286 if isinstance(target, str): 287 self._attributes['parameters']['target'] = target 288 elif target is not None: 289 warn(f"The provided target is of invalid type '{type(target)}'.") 290 291 if isinstance(dtypes, dict): 292 self._attributes['parameters']['dtypes'] = dtypes 293 elif dtypes is not None: 294 warn(f"The provided dtypes are of invalid type '{type(dtypes)}'.") 295 296 ### NOTE: The parameters dictionary is {} by default. 297 ### A Pipe may be registered without parameters, then edited, 298 ### or a Pipe may be registered with parameters set in-memory first. 299 # from meerschaum.config import get_config 300 _mrsm_instance = mrsm_instance if mrsm_instance is not None else instance 301 if _mrsm_instance is None: 302 _mrsm_instance = get_config('meerschaum', 'instance', patch=True) 303 304 if not isinstance(_mrsm_instance, str): 305 self._instance_connector = _mrsm_instance 306 self.instance_keys = str(_mrsm_instance) 307 else: ### NOTE: must be SQL or API Connector for this work 308 self.instance_keys = _mrsm_instance 309 310 self._cache = cache and get_config('system', 'experimental', 'cache') 311 312 313 @property 314 def meta(self): 315 """ 316 Return the four keys needed to reconstruct this pipe. 317 """ 318 return { 319 'connector': self.connector_keys, 320 'metric': self.metric_key, 321 'location': self.location_key, 322 'instance': self.instance_keys, 323 } 324 325 326 def keys(self) -> List[str]: 327 """ 328 Return the ordered keys for this pipe. 329 """ 330 return { 331 key: val 332 for key, val in self.meta.items() 333 if key != 'instance' 334 } 335 336 337 @property 338 def instance_connector(self) -> Union[InstanceConnector, None]: 339 """ 340 The connector to where this pipe resides. 341 May either be of type `meerschaum.connectors.sql.SQLConnector` or 342 `meerschaum.connectors.api.APIConnector`. 343 """ 344 if '_instance_connector' not in self.__dict__: 345 from meerschaum.connectors.parse import parse_instance_keys 346 conn = parse_instance_keys(self.instance_keys) 347 if conn: 348 self._instance_connector = conn 349 else: 350 return None 351 return self._instance_connector 352 353 @property 354 def connector(self) -> Union[meerschaum.connectors.Connector, None]: 355 """ 356 The connector to the data source. 357 """ 358 if '_connector' not in self.__dict__: 359 from meerschaum.connectors.parse import parse_instance_keys 360 import warnings 361 with warnings.catch_warnings(): 362 warnings.simplefilter('ignore') 363 try: 364 conn = parse_instance_keys(self.connector_keys) 365 except Exception as e: 366 conn = None 367 if conn: 368 self._connector = conn 369 else: 370 return None 371 return self._connector 372 373 374 @property 375 def cache_connector(self) -> Union[meerschaum.connectors.sql.SQLConnector, None]: 376 """ 377 If the pipe was created with `cache=True`, return the connector to the pipe's 378 SQLite database for caching. 379 """ 380 if not self._cache: 381 return None 382 383 if '_cache_connector' not in self.__dict__: 384 from meerschaum.connectors import get_connector 385 from meerschaum.config._paths import DUCKDB_RESOURCES_PATH, SQLITE_RESOURCES_PATH 386 _resources_path = SQLITE_RESOURCES_PATH 387 self._cache_connector = get_connector( 388 'sql', '_cache_' + str(self), 389 flavor='sqlite', 390 database=str(_resources_path / ('_cache_' + str(self) + '.db')), 391 ) 392 393 return self._cache_connector 394 395 396 @property 397 def cache_pipe(self) -> Union['meerschaum.Pipe', None]: 398 """ 399 If the pipe was created with `cache=True`, return another `meerschaum.Pipe` used to 400 manage the local data. 401 """ 402 if self.cache_connector is None: 403 return None 404 if '_cache_pipe' not in self.__dict__: 405 from meerschaum.config._patch import apply_patch_to_config 406 from meerschaum.utils.sql import sql_item_name 407 _parameters = copy.deepcopy(self.parameters) 408 _fetch_patch = { 409 'fetch': ({ 410 'definition': ( 411 f"SELECT * FROM " 412 + sql_item_name( 413 str(self.target), 414 self.instance_connector.flavor, 415 self.instance_connector.get_pipe_schema(self), 416 ) 417 ), 418 }) if self.instance_connector.type == 'sql' else ({ 419 'connector_keys': self.connector_keys, 420 'metric_key': self.metric_key, 421 'location_key': self.location_key, 422 }) 423 } 424 _parameters = apply_patch_to_config(_parameters, _fetch_patch) 425 self._cache_pipe = Pipe( 426 self.instance_keys, 427 (self.connector_keys + '_' + self.metric_key + '_cache'), 428 self.location_key, 429 mrsm_instance = self.cache_connector, 430 parameters = _parameters, 431 cache = False, 432 temporary = True, 433 ) 434 435 return self._cache_pipe 436 437 438 def __str__(self, ansi: bool=False): 439 return pipe_repr(self, ansi=ansi) 440 441 442 def __eq__(self, other): 443 try: 444 return ( 445 isinstance(self, type(other)) 446 and self.connector_keys == other.connector_keys 447 and self.metric_key == other.metric_key 448 and self.location_key == other.location_key 449 and self.instance_keys == other.instance_keys 450 ) 451 except Exception as e: 452 return False 453 454 def __hash__(self): 455 ### Using an esoteric separator to avoid collisions. 456 sep = "[\"']" 457 return hash( 458 str(self.connector_keys) + sep 459 + str(self.metric_key) + sep 460 + str(self.location_key) + sep 461 + str(self.instance_keys) + sep 462 ) 463 464 def __repr__(self, ansi: bool=True, **kw) -> str: 465 if not hasattr(sys, 'ps1'): 466 ansi = False 467 468 return pipe_repr(self, ansi=ansi, **kw) 469 470 def __pt_repr__(self): 471 from meerschaum.utils.packages import attempt_import 472 prompt_toolkit_formatted_text = attempt_import('prompt_toolkit.formatted_text', lazy=False) 473 return prompt_toolkit_formatted_text.ANSI(pipe_repr(self, ansi=True)) 474 475 def __getstate__(self) -> Dict[str, Any]: 476 """ 477 Define the state dictionary (pickling). 478 """ 479 return { 480 'connector': self.connector_keys, 481 'metric': self.metric_key, 482 'location': self.location_key, 483 'parameters': self.parameters, 484 'instance': self.instance_keys, 485 } 486 487 def __setstate__(self, _state: Dict[str, Any]): 488 """ 489 Read the state (unpickling). 490 """ 491 self.__init__(**_state) 492 493 494 def __getitem__(self, key: str) -> Any: 495 """ 496 Index the pipe's attributes. 497 If the `key` cannot be found`, return `None`. 498 """ 499 if key in self.attributes: 500 return self.attributes.get(key, None) 501 502 aliases = { 503 'connector': 'connector_keys', 504 'connector_key': 'connector_keys', 505 'metric': 'metric_key', 506 'location': 'location_key', 507 } 508 aliased_key = aliases.get(key, None) 509 if aliased_key is not None: 510 return self.attributes.get(aliased_key, None) 511 512 property_aliases = { 513 'instance': 'instance_keys', 514 'instance_key': 'instance_keys', 515 } 516 aliased_key = property_aliases.get(key, None) 517 if aliased_key is not None: 518 key = aliased_key 519 return getattr(self, key, None)
Access Meerschaum pipes via Pipe objects.
Pipes are identified by the following:
- Connector keys (e.g.
'sql:main'
) - Metric key (e.g.
'weather'
) - Location (optional; e.g.
None
)
A pipe's connector keys correspond to a data source, and when the pipe is synced,
its fetch
definition is evaluated and executed to produce new data.
Alternatively, new data may be directly synced via pipe.sync()
:
>>> from meerschaum import Pipe
>>> pipe = Pipe('csv', 'weather')
>>>
>>> import pandas as pd
>>> df = pd.read_csv('weather.csv')
>>> pipe.sync(df)
144 def __init__( 145 self, 146 connector: str = '', 147 metric: str = '', 148 location: Optional[str] = None, 149 parameters: Optional[Dict[str, Any]] = None, 150 columns: Union[Dict[str, str], List[str], None] = None, 151 indices: Optional[Dict[str, Union[str, List[str]]]] = None, 152 tags: Optional[List[str]] = None, 153 target: Optional[str] = None, 154 dtypes: Optional[Dict[str, str]] = None, 155 instance: Optional[Union[str, InstanceConnector]] = None, 156 temporary: bool = False, 157 mrsm_instance: Optional[Union[str, InstanceConnector]] = None, 158 cache: bool = False, 159 debug: bool = False, 160 connector_keys: Optional[str] = None, 161 metric_key: Optional[str] = None, 162 location_key: Optional[str] = None, 163 indexes: Union[Dict[str, str], List[str], None] = None, 164 ): 165 """ 166 Parameters 167 ---------- 168 connector: str 169 Keys for the pipe's source connector, e.g. `'sql:main'`. 170 171 metric: str 172 Label for the pipe's contents, e.g. `'weather'`. 173 174 location: str, default None 175 Label for the pipe's location. Defaults to `None`. 176 177 parameters: Optional[Dict[str, Any]], default None 178 Optionally set a pipe's parameters from the constructor, 179 e.g. columns and other attributes. 180 You can edit these parameters with `edit pipes`. 181 182 columns: Union[Dict[str, str], List[str], None], default None 183 Set the `columns` dictionary of `parameters`. 184 If `parameters` is also provided, this dictionary is added under the `'columns'` key. 185 186 indices: Optional[Dict[str, Union[str, List[str]]]], default None 187 Set the `indices` dictionary of `parameters`. 188 If `parameters` is also provided, this dictionary is added under the `'indices'` key. 189 190 tags: Optional[List[str]], default None 191 A list of strings to be added under the `'tags'` key of `parameters`. 192 You can select pipes with certain tags using `--tags`. 193 194 dtypes: Optional[Dict[str, str]], default None 195 Set the `dtypes` dictionary of `parameters`. 196 If `parameters` is also provided, this dictionary is added under the `'dtypes'` key. 197 198 mrsm_instance: Optional[Union[str, InstanceConnector]], default None 199 Connector for the Meerschaum instance where the pipe resides. 200 Defaults to the preconfigured default instance (`'sql:main'`). 201 202 instance: Optional[Union[str, InstanceConnector]], default None 203 Alias for `mrsm_instance`. If `mrsm_instance` is supplied, this value is ignored. 204 205 temporary: bool, default False 206 If `True`, prevent instance tables (pipes, users, plugins) from being created. 207 208 cache: bool, default False 209 If `True`, cache fetched data into a local database file. 210 Defaults to `False`. 211 """ 212 from meerschaum.utils.warnings import error, warn 213 if (not connector and not connector_keys) or (not metric and not metric_key): 214 error( 215 "Please provide strings for the connector and metric\n " 216 + "(first two positional arguments)." 217 ) 218 219 ### Fall back to legacy `location_key` just in case. 220 if not location: 221 location = location_key 222 223 if not connector: 224 connector = connector_keys 225 226 if not metric: 227 metric = metric_key 228 229 if location in ('[None]', 'None'): 230 location = None 231 232 from meerschaum.config.static import STATIC_CONFIG 233 negation_prefix = STATIC_CONFIG['system']['fetch_pipes_keys']['negation_prefix'] 234 for k in (connector, metric, location, *(tags or [])): 235 if str(k).startswith(negation_prefix): 236 error(f"A pipe's keys and tags cannot start with the prefix '{negation_prefix}'.") 237 238 self.connector_keys = str(connector) 239 self.connector_key = self.connector_keys ### Alias 240 self.metric_key = metric 241 self.location_key = location 242 self.temporary = temporary 243 244 self._attributes = { 245 'connector_keys': self.connector_keys, 246 'metric_key': self.metric_key, 247 'location_key': self.location_key, 248 'parameters': {}, 249 } 250 251 ### only set parameters if values are provided 252 if isinstance(parameters, dict): 253 self._attributes['parameters'] = parameters 254 else: 255 if parameters is not None: 256 warn(f"The provided parameters are of invalid type '{type(parameters)}'.") 257 self._attributes['parameters'] = {} 258 259 columns = columns or self._attributes.get('parameters', {}).get('columns', {}) 260 if isinstance(columns, list): 261 columns = {str(col): str(col) for col in columns} 262 if isinstance(columns, dict): 263 self._attributes['parameters']['columns'] = columns 264 elif columns is not None: 265 warn(f"The provided columns are of invalid type '{type(columns)}'.") 266 267 indices = ( 268 indices 269 or indexes 270 or self._attributes.get('parameters', {}).get('indices', None) 271 or self._attributes.get('parameters', {}).get('indexes', None) 272 ) or columns 273 if isinstance(indices, dict): 274 indices_key = ( 275 'indexes' 276 if 'indexes' in self._attributes['parameters'] 277 else 'indices' 278 ) 279 self._attributes['parameters'][indices_key] = indices 280 281 if isinstance(tags, (list, tuple)): 282 self._attributes['parameters']['tags'] = tags 283 elif tags is not None: 284 warn(f"The provided tags are of invalid type '{type(tags)}'.") 285 286 if isinstance(target, str): 287 self._attributes['parameters']['target'] = target 288 elif target is not None: 289 warn(f"The provided target is of invalid type '{type(target)}'.") 290 291 if isinstance(dtypes, dict): 292 self._attributes['parameters']['dtypes'] = dtypes 293 elif dtypes is not None: 294 warn(f"The provided dtypes are of invalid type '{type(dtypes)}'.") 295 296 ### NOTE: The parameters dictionary is {} by default. 297 ### A Pipe may be registered without parameters, then edited, 298 ### or a Pipe may be registered with parameters set in-memory first. 299 # from meerschaum.config import get_config 300 _mrsm_instance = mrsm_instance if mrsm_instance is not None else instance 301 if _mrsm_instance is None: 302 _mrsm_instance = get_config('meerschaum', 'instance', patch=True) 303 304 if not isinstance(_mrsm_instance, str): 305 self._instance_connector = _mrsm_instance 306 self.instance_keys = str(_mrsm_instance) 307 else: ### NOTE: must be SQL or API Connector for this work 308 self.instance_keys = _mrsm_instance 309 310 self._cache = cache and get_config('system', 'experimental', 'cache')
Parameters
- connector (str):
Keys for the pipe's source connector, e.g.
'sql:main'
. - metric (str):
Label for the pipe's contents, e.g.
'weather'
. - location (str, default None):
Label for the pipe's location. Defaults to
None
. - parameters (Optional[Dict[str, Any]], default None):
Optionally set a pipe's parameters from the constructor,
e.g. columns and other attributes.
You can edit these parameters with
edit pipes
. - columns (Union[Dict[str, str], List[str], None], default None):
Set the
columns
dictionary ofparameters
. Ifparameters
is also provided, this dictionary is added under the'columns'
key. - indices (Optional[Dict[str, Union[str, List[str]]]], default None):
Set the
indices
dictionary ofparameters
. Ifparameters
is also provided, this dictionary is added under the'indices'
key. - tags (Optional[List[str]], default None):
A list of strings to be added under the
'tags'
key ofparameters
. You can select pipes with certain tags using--tags
. - dtypes (Optional[Dict[str, str]], default None):
Set the
dtypes
dictionary ofparameters
. Ifparameters
is also provided, this dictionary is added under the'dtypes'
key. - mrsm_instance (Optional[Union[str, InstanceConnector]], default None):
Connector for the Meerschaum instance where the pipe resides.
Defaults to the preconfigured default instance (
'sql:main'
). - instance (Optional[Union[str, InstanceConnector]], default None):
Alias for
mrsm_instance
. Ifmrsm_instance
is supplied, this value is ignored. - temporary (bool, default False):
If
True
, prevent instance tables (pipes, users, plugins) from being created. - cache (bool, default False):
If
True
, cache fetched data into a local database file. Defaults toFalse
.
313 @property 314 def meta(self): 315 """ 316 Return the four keys needed to reconstruct this pipe. 317 """ 318 return { 319 'connector': self.connector_keys, 320 'metric': self.metric_key, 321 'location': self.location_key, 322 'instance': self.instance_keys, 323 }
Return the four keys needed to reconstruct this pipe.
326 def keys(self) -> List[str]: 327 """ 328 Return the ordered keys for this pipe. 329 """ 330 return { 331 key: val 332 for key, val in self.meta.items() 333 if key != 'instance' 334 }
Return the ordered keys for this pipe.
337 @property 338 def instance_connector(self) -> Union[InstanceConnector, None]: 339 """ 340 The connector to where this pipe resides. 341 May either be of type `meerschaum.connectors.sql.SQLConnector` or 342 `meerschaum.connectors.api.APIConnector`. 343 """ 344 if '_instance_connector' not in self.__dict__: 345 from meerschaum.connectors.parse import parse_instance_keys 346 conn = parse_instance_keys(self.instance_keys) 347 if conn: 348 self._instance_connector = conn 349 else: 350 return None 351 return self._instance_connector
The connector to where this pipe resides.
May either be of type meerschaum.connectors.sql.SQLConnector
or
meerschaum.connectors.api.APIConnector
.
353 @property 354 def connector(self) -> Union[meerschaum.connectors.Connector, None]: 355 """ 356 The connector to the data source. 357 """ 358 if '_connector' not in self.__dict__: 359 from meerschaum.connectors.parse import parse_instance_keys 360 import warnings 361 with warnings.catch_warnings(): 362 warnings.simplefilter('ignore') 363 try: 364 conn = parse_instance_keys(self.connector_keys) 365 except Exception as e: 366 conn = None 367 if conn: 368 self._connector = conn 369 else: 370 return None 371 return self._connector
The connector to the data source.
374 @property 375 def cache_connector(self) -> Union[meerschaum.connectors.sql.SQLConnector, None]: 376 """ 377 If the pipe was created with `cache=True`, return the connector to the pipe's 378 SQLite database for caching. 379 """ 380 if not self._cache: 381 return None 382 383 if '_cache_connector' not in self.__dict__: 384 from meerschaum.connectors import get_connector 385 from meerschaum.config._paths import DUCKDB_RESOURCES_PATH, SQLITE_RESOURCES_PATH 386 _resources_path = SQLITE_RESOURCES_PATH 387 self._cache_connector = get_connector( 388 'sql', '_cache_' + str(self), 389 flavor='sqlite', 390 database=str(_resources_path / ('_cache_' + str(self) + '.db')), 391 ) 392 393 return self._cache_connector
If the pipe was created with cache=True
, return the connector to the pipe's
SQLite database for caching.
396 @property 397 def cache_pipe(self) -> Union['meerschaum.Pipe', None]: 398 """ 399 If the pipe was created with `cache=True`, return another `meerschaum.Pipe` used to 400 manage the local data. 401 """ 402 if self.cache_connector is None: 403 return None 404 if '_cache_pipe' not in self.__dict__: 405 from meerschaum.config._patch import apply_patch_to_config 406 from meerschaum.utils.sql import sql_item_name 407 _parameters = copy.deepcopy(self.parameters) 408 _fetch_patch = { 409 'fetch': ({ 410 'definition': ( 411 f"SELECT * FROM " 412 + sql_item_name( 413 str(self.target), 414 self.instance_connector.flavor, 415 self.instance_connector.get_pipe_schema(self), 416 ) 417 ), 418 }) if self.instance_connector.type == 'sql' else ({ 419 'connector_keys': self.connector_keys, 420 'metric_key': self.metric_key, 421 'location_key': self.location_key, 422 }) 423 } 424 _parameters = apply_patch_to_config(_parameters, _fetch_patch) 425 self._cache_pipe = Pipe( 426 self.instance_keys, 427 (self.connector_keys + '_' + self.metric_key + '_cache'), 428 self.location_key, 429 mrsm_instance = self.cache_connector, 430 parameters = _parameters, 431 cache = False, 432 temporary = True, 433 ) 434 435 return self._cache_pipe
If the pipe was created with cache=True
, return another meerschaum.Pipe
used to
manage the local data.
21def fetch( 22 self, 23 begin: Union[datetime, str, None] = '', 24 end: Optional[datetime] = None, 25 check_existing: bool = True, 26 sync_chunks: bool = False, 27 debug: bool = False, 28 **kw: Any 29 ) -> Union['pd.DataFrame', Iterator['pd.DataFrame'], None]: 30 """ 31 Fetch a Pipe's latest data from its connector. 32 33 Parameters 34 ---------- 35 begin: Union[datetime, str, None], default '': 36 If provided, only fetch data newer than or equal to `begin`. 37 38 end: Optional[datetime], default None: 39 If provided, only fetch data older than or equal to `end`. 40 41 check_existing: bool, default True 42 If `False`, do not apply the backtrack interval. 43 44 sync_chunks: bool, default False 45 If `True` and the pipe's connector is of type `'sql'`, begin syncing chunks while fetching 46 loads chunks into memory. 47 48 debug: bool, default False 49 Verbosity toggle. 50 51 Returns 52 ------- 53 A `pd.DataFrame` of the newest unseen data. 54 55 """ 56 if 'fetch' not in dir(self.connector): 57 warn(f"No `fetch()` function defined for connector '{self.connector}'") 58 return None 59 60 from meerschaum.connectors import custom_types, get_connector_plugin 61 from meerschaum.utils.debug import dprint, _checkpoint 62 from meerschaum.utils.misc import filter_arguments 63 64 _chunk_hook = kw.pop('chunk_hook', None) 65 kw['workers'] = self.get_num_workers(kw.get('workers', None)) 66 if sync_chunks and _chunk_hook is None: 67 68 def _chunk_hook(chunk, **_kw) -> SuccessTuple: 69 """ 70 Wrap `Pipe.sync()` with a custom chunk label prepended to the message. 71 """ 72 from meerschaum.config._patch import apply_patch_to_config 73 kwargs = apply_patch_to_config(kw, _kw) 74 chunk_success, chunk_message = self.sync(chunk, **kwargs) 75 chunk_label = self._get_chunk_label(chunk, self.columns.get('datetime', None)) 76 if chunk_label: 77 chunk_message = '\n' + chunk_label + '\n' + chunk_message 78 return chunk_success, chunk_message 79 80 with mrsm.Venv(get_connector_plugin(self.connector)): 81 _args, _kwargs = filter_arguments( 82 self.connector.fetch, 83 self, 84 begin=_determine_begin( 85 self, 86 begin, 87 check_existing=check_existing, 88 debug=debug, 89 ), 90 end=end, 91 chunk_hook=_chunk_hook, 92 debug=debug, 93 **kw 94 ) 95 df = self.connector.fetch(*_args, **_kwargs) 96 return df
Fetch a Pipe's latest data from its connector.
Parameters
- begin (Union[datetime, str, None], default '':):
If provided, only fetch data newer than or equal to
begin
. - end (Optional[datetime], default None:):
If provided, only fetch data older than or equal to
end
. - check_existing (bool, default True):
If
False
, do not apply the backtrack interval. - sync_chunks (bool, default False):
If
True
and the pipe's connector is of type'sql'
, begin syncing chunks while fetching loads chunks into memory. - debug (bool, default False): Verbosity toggle.
Returns
- A
pd.DataFrame
of the newest unseen data.
99def get_backtrack_interval( 100 self, 101 check_existing: bool = True, 102 debug: bool = False, 103) -> Union[timedelta, int]: 104 """ 105 Get the chunk interval to use for this pipe. 106 107 Parameters 108 ---------- 109 check_existing: bool, default True 110 If `False`, return a backtrack_interval of 0 minutes. 111 112 Returns 113 ------- 114 The backtrack interval (`timedelta` or `int`) to use with this pipe's `datetime` axis. 115 """ 116 default_backtrack_minutes = get_config('pipes', 'parameters', 'fetch', 'backtrack_minutes') 117 configured_backtrack_minutes = self.parameters.get('fetch', {}).get('backtrack_minutes', None) 118 backtrack_minutes = ( 119 configured_backtrack_minutes 120 if configured_backtrack_minutes is not None 121 else default_backtrack_minutes 122 ) if check_existing else 0 123 124 backtrack_interval = timedelta(minutes=backtrack_minutes) 125 dt_col = self.columns.get('datetime', None) 126 if dt_col is None: 127 return backtrack_interval 128 129 dt_dtype = self.dtypes.get(dt_col, 'datetime64[ns]') 130 if 'int' in dt_dtype.lower(): 131 return backtrack_minutes 132 133 return backtrack_interval
Get the chunk interval to use for this pipe.
Parameters
- check_existing (bool, default True):
If
False
, return a backtrack_interval of 0 minutes.
Returns
- The backtrack interval (
timedelta
orint
) to use with this pipe'sdatetime
axis.
23def get_data( 24 self, 25 select_columns: Optional[List[str]] = None, 26 omit_columns: Optional[List[str]] = None, 27 begin: Union[datetime, int, None] = None, 28 end: Union[datetime, int, None] = None, 29 params: Optional[Dict[str, Any]] = None, 30 as_iterator: bool = False, 31 as_chunks: bool = False, 32 as_dask: bool = False, 33 chunk_interval: Union[timedelta, int, None] = None, 34 order: Optional[str] = 'asc', 35 limit: Optional[int] = None, 36 fresh: bool = False, 37 debug: bool = False, 38 **kw: Any 39) -> Union['pd.DataFrame', Iterator['pd.DataFrame'], None]: 40 """ 41 Get a pipe's data from the instance connector. 42 43 Parameters 44 ---------- 45 select_columns: Optional[List[str]], default None 46 If provided, only select these given columns. 47 Otherwise select all available columns (i.e. `SELECT *`). 48 49 omit_columns: Optional[List[str]], default None 50 If provided, remove these columns from the selection. 51 52 begin: Union[datetime, int, None], default None 53 Lower bound datetime to begin searching for data (inclusive). 54 Translates to a `WHERE` clause like `WHERE datetime >= begin`. 55 Defaults to `None`. 56 57 end: Union[datetime, int, None], default None 58 Upper bound datetime to stop searching for data (inclusive). 59 Translates to a `WHERE` clause like `WHERE datetime < end`. 60 Defaults to `None`. 61 62 params: Optional[Dict[str, Any]], default None 63 Filter the retrieved data by a dictionary of parameters. 64 See `meerschaum.utils.sql.build_where` for more details. 65 66 as_iterator: bool, default False 67 If `True`, return a generator of chunks of pipe data. 68 69 as_chunks: bool, default False 70 Alias for `as_iterator`. 71 72 as_dask: bool, default False 73 If `True`, return a `dask.DataFrame` 74 (which may be loaded into a Pandas DataFrame with `df.compute()`). 75 76 chunk_interval: Union[timedelta, int, None], default None 77 If `as_iterator`, then return chunks with `begin` and `end` separated by this interval. 78 This may be set under `pipe.parameters['chunk_minutes']`. 79 By default, use a timedelta of 1440 minutes (1 day). 80 If `chunk_interval` is an integer and the `datetime` axis a timestamp, 81 the use a timedelta with the number of minutes configured to this value. 82 If the `datetime` axis is an integer, default to the configured chunksize. 83 If `chunk_interval` is a `timedelta` and the `datetime` axis an integer, 84 use the number of minutes in the `timedelta`. 85 86 order: Optional[str], default 'asc' 87 If `order` is not `None`, sort the resulting dataframe by indices. 88 89 limit: Optional[int], default None 90 If provided, cap the dataframe to this many rows. 91 92 fresh: bool, default True 93 If `True`, skip local cache and directly query the instance connector. 94 Defaults to `True`. 95 96 debug: bool, default False 97 Verbosity toggle. 98 Defaults to `False`. 99 100 Returns 101 ------- 102 A `pd.DataFrame` for the pipe's data corresponding to the provided parameters. 103 104 """ 105 from meerschaum.utils.warnings import warn 106 from meerschaum.utils.venv import Venv 107 from meerschaum.connectors import get_connector_plugin 108 from meerschaum.utils.misc import iterate_chunks, items_str 109 from meerschaum.utils.dtypes import to_pandas_dtype 110 from meerschaum.utils.dataframe import add_missing_cols_to_df, df_is_chunk_generator 111 from meerschaum.utils.packages import attempt_import 112 dd = attempt_import('dask.dataframe') if as_dask else None 113 dask = attempt_import('dask') if as_dask else None 114 115 if select_columns == '*': 116 select_columns = None 117 elif isinstance(select_columns, str): 118 select_columns = [select_columns] 119 120 if isinstance(omit_columns, str): 121 omit_columns = [omit_columns] 122 123 as_iterator = as_iterator or as_chunks 124 125 def _sort_df(_df): 126 if df_is_chunk_generator(_df): 127 return _df 128 dt_col = self.columns.get('datetime', None) 129 indices = [] if dt_col not in _df.columns else [dt_col] 130 non_dt_cols = [ 131 col 132 for col_ix, col in self.columns.items() 133 if col_ix != 'datetime' and col in _df.columns 134 ] 135 indices.extend(non_dt_cols) 136 if 'dask' not in _df.__module__: 137 _df.sort_values( 138 by=indices, 139 inplace=True, 140 ascending=(str(order).lower() == 'asc'), 141 ) 142 _df.reset_index(drop=True, inplace=True) 143 else: 144 _df = _df.sort_values( 145 by=indices, 146 ascending=(str(order).lower() == 'asc'), 147 ) 148 _df = _df.reset_index(drop=True) 149 if limit is not None and len(_df) > limit: 150 return _df.head(limit) 151 return _df 152 153 if as_iterator or as_chunks: 154 df = self._get_data_as_iterator( 155 select_columns=select_columns, 156 omit_columns=omit_columns, 157 begin=begin, 158 end=end, 159 params=params, 160 chunk_interval=chunk_interval, 161 limit=limit, 162 order=order, 163 fresh=fresh, 164 debug=debug, 165 ) 166 return _sort_df(df) 167 168 if as_dask: 169 from multiprocessing.pool import ThreadPool 170 dask_pool = ThreadPool(self.get_num_workers()) 171 dask.config.set(pool=dask_pool) 172 chunk_interval = self.get_chunk_interval(chunk_interval, debug=debug) 173 bounds = self.get_chunk_bounds( 174 begin=begin, 175 end=end, 176 bounded=False, 177 chunk_interval=chunk_interval, 178 debug=debug, 179 ) 180 dask_chunks = [ 181 dask.delayed(self.get_data)( 182 select_columns=select_columns, 183 omit_columns=omit_columns, 184 begin=chunk_begin, 185 end=chunk_end, 186 params=params, 187 chunk_interval=chunk_interval, 188 order=order, 189 limit=limit, 190 fresh=fresh, 191 debug=debug, 192 ) 193 for (chunk_begin, chunk_end) in bounds 194 ] 195 dask_meta = { 196 col: to_pandas_dtype(typ) 197 for col, typ in self.dtypes.items() 198 } 199 return _sort_df(dd.from_delayed(dask_chunks, meta=dask_meta)) 200 201 if not self.exists(debug=debug): 202 return None 203 204 if self.cache_pipe is not None: 205 if not fresh: 206 _sync_cache_tuple = self.cache_pipe.sync( 207 begin=begin, 208 end=end, 209 params=params, 210 debug=debug, 211 **kw 212 ) 213 if not _sync_cache_tuple[0]: 214 warn(f"Failed to sync cache for {self}:\n" + _sync_cache_tuple[1]) 215 fresh = True 216 else: ### Successfully synced cache. 217 return self.enforce_dtypes( 218 self.cache_pipe.get_data( 219 select_columns=select_columns, 220 omit_columns=omit_columns, 221 begin=begin, 222 end=end, 223 params=params, 224 order=order, 225 limit=limit, 226 debug=debug, 227 fresh=True, 228 **kw 229 ), 230 debug=debug, 231 ) 232 233 with Venv(get_connector_plugin(self.instance_connector)): 234 df = self.instance_connector.get_pipe_data( 235 pipe=self, 236 select_columns=select_columns, 237 omit_columns=omit_columns, 238 begin=begin, 239 end=end, 240 params=params, 241 limit=limit, 242 order=order, 243 debug=debug, 244 **kw 245 ) 246 if df is None: 247 return df 248 249 if not select_columns: 250 select_columns = [col for col in df.columns] 251 252 cols_to_omit = [ 253 col 254 for col in df.columns 255 if ( 256 col in (omit_columns or []) 257 or 258 col not in (select_columns or []) 259 ) 260 ] 261 cols_to_add = [ 262 col 263 for col in select_columns 264 if col not in df.columns 265 ] 266 if cols_to_omit: 267 warn( 268 ( 269 f"Received {len(cols_to_omit)} omitted column" 270 + ('s' if len(cols_to_omit) != 1 else '') 271 + f" for {self}. " 272 + "Consider adding `select_columns` and `omit_columns` support to " 273 + f"'{self.instance_connector.type}' connectors to improve performance." 274 ), 275 stack=False, 276 ) 277 _cols_to_select = [col for col in df.columns if col not in cols_to_omit] 278 df = df[_cols_to_select] 279 280 if cols_to_add: 281 warn( 282 ( 283 f"Specified columns {items_str(cols_to_add)} were not found on {self}. " 284 + "Adding these to the DataFrame as null columns." 285 ), 286 stack=False, 287 ) 288 df = add_missing_cols_to_df(df, {col: 'string' for col in cols_to_add}) 289 290 enforced_df = self.enforce_dtypes(df, debug=debug) 291 292 if order: 293 return _sort_df(enforced_df) 294 return enforced_df
Get a pipe's data from the instance connector.
Parameters
- select_columns (Optional[List[str]], default None):
If provided, only select these given columns.
Otherwise select all available columns (i.e.
SELECT *
). - omit_columns (Optional[List[str]], default None): If provided, remove these columns from the selection.
- begin (Union[datetime, int, None], default None):
Lower bound datetime to begin searching for data (inclusive).
Translates to a
WHERE
clause likeWHERE datetime >= begin
. Defaults toNone
. - end (Union[datetime, int, None], default None):
Upper bound datetime to stop searching for data (inclusive).
Translates to a
WHERE
clause likeWHERE datetime < end
. Defaults toNone
. - params (Optional[Dict[str, Any]], default None):
Filter the retrieved data by a dictionary of parameters.
See
meerschaum.utils.sql.build_where
for more details. - as_iterator (bool, default False):
If
True
, return a generator of chunks of pipe data. - as_chunks (bool, default False):
Alias for
as_iterator
. - as_dask (bool, default False):
If
True
, return adask.DataFrame
(which may be loaded into a Pandas DataFrame withdf.compute()
). - chunk_interval (Union[timedelta, int, None], default None):
If
as_iterator
, then return chunks withbegin
andend
separated by this interval. This may be set underpipe.parameters['chunk_minutes']
. By default, use a timedelta of 1440 minutes (1 day). Ifchunk_interval
is an integer and thedatetime
axis a timestamp, the use a timedelta with the number of minutes configured to this value. If thedatetime
axis is an integer, default to the configured chunksize. Ifchunk_interval
is atimedelta
and thedatetime
axis an integer, use the number of minutes in thetimedelta
. - order (Optional[str], default 'asc'):
If
order
is notNone
, sort the resulting dataframe by indices. - limit (Optional[int], default None): If provided, cap the dataframe to this many rows.
- fresh (bool, default True):
If
True
, skip local cache and directly query the instance connector. Defaults toTrue
. - debug (bool, default False):
Verbosity toggle.
Defaults to
False
.
Returns
- A
pd.DataFrame
for the pipe's data corresponding to the provided parameters.
395def get_backtrack_data( 396 self, 397 backtrack_minutes: Optional[int] = None, 398 begin: Union[datetime, int, None] = None, 399 params: Optional[Dict[str, Any]] = None, 400 limit: Optional[int] = None, 401 fresh: bool = False, 402 debug: bool = False, 403 **kw: Any 404) -> Optional['pd.DataFrame']: 405 """ 406 Get the most recent data from the instance connector as a Pandas DataFrame. 407 408 Parameters 409 ---------- 410 backtrack_minutes: Optional[int], default None 411 How many minutes from `begin` to select from. 412 If `None`, use `pipe.parameters['fetch']['backtrack_minutes']`. 413 414 begin: Optional[datetime], default None 415 The starting point to search for data. 416 If begin is `None` (default), use the most recent observed datetime 417 (AKA sync_time). 418 419 ``` 420 E.g. begin = 02:00 421 422 Search this region. Ignore this, even if there's data. 423 / / / / / / / / / | 424 -----|----------|----------|----------|----------|----------| 425 00:00 01:00 02:00 03:00 04:00 05:00 426 427 ``` 428 429 params: Optional[Dict[str, Any]], default None 430 The standard Meerschaum `params` query dictionary. 431 432 limit: Optional[int], default None 433 If provided, cap the number of rows to be returned. 434 435 fresh: bool, default False 436 If `True`, Ignore local cache and pull directly from the instance connector. 437 Only comes into effect if a pipe was created with `cache=True`. 438 439 debug: bool default False 440 Verbosity toggle. 441 442 Returns 443 ------- 444 A `pd.DataFrame` for the pipe's data corresponding to the provided parameters. Backtrack data 445 is a convenient way to get a pipe's data "backtracked" from the most recent datetime. 446 """ 447 from meerschaum.utils.warnings import warn 448 from meerschaum.utils.venv import Venv 449 from meerschaum.connectors import get_connector_plugin 450 451 if not self.exists(debug=debug): 452 return None 453 454 backtrack_interval = self.get_backtrack_interval(debug=debug) 455 if backtrack_minutes is None: 456 backtrack_minutes = ( 457 (backtrack_interval.total_seconds() / 60) 458 if isinstance(backtrack_interval, timedelta) 459 else backtrack_interval 460 ) 461 462 if self.cache_pipe is not None: 463 if not fresh: 464 _sync_cache_tuple = self.cache_pipe.sync(begin=begin, params=params, debug=debug, **kw) 465 if not _sync_cache_tuple[0]: 466 warn(f"Failed to sync cache for {self}:\n" + _sync_cache_tuple[1]) 467 fresh = True 468 else: ### Successfully synced cache. 469 return self.enforce_dtypes( 470 self.cache_pipe.get_backtrack_data( 471 fresh=True, 472 begin=begin, 473 backtrack_minutes=backtrack_minutes, 474 params=params, 475 limit=limit, 476 order=kw.get('order', 'desc'), 477 debug=debug, 478 **kw 479 ), 480 debug=debug, 481 ) 482 483 if hasattr(self.instance_connector, 'get_backtrack_data'): 484 with Venv(get_connector_plugin(self.instance_connector)): 485 return self.enforce_dtypes( 486 self.instance_connector.get_backtrack_data( 487 pipe=self, 488 begin=begin, 489 backtrack_minutes=backtrack_minutes, 490 params=params, 491 limit=limit, 492 debug=debug, 493 **kw 494 ), 495 debug=debug, 496 ) 497 498 if begin is None: 499 begin = self.get_sync_time(params=params, debug=debug) 500 501 backtrack_interval = ( 502 timedelta(minutes=backtrack_minutes) 503 if isinstance(begin, datetime) 504 else backtrack_minutes 505 ) 506 if begin is not None: 507 begin = begin - backtrack_interval 508 509 return self.get_data( 510 begin=begin, 511 params=params, 512 debug=debug, 513 limit=limit, 514 order=kw.get('order', 'desc'), 515 **kw 516 )
Get the most recent data from the instance connector as a Pandas DataFrame.
Parameters
- backtrack_minutes (Optional[int], default None):
How many minutes from
begin
to select from. IfNone
, usepipe.parameters['fetch']['backtrack_minutes']
. begin (Optional[datetime], default None): The starting point to search for data. If begin is
None
(default), use the most recent observed datetime (AKA sync_time).E.g. begin = 02:00 Search this region. Ignore this, even if there's data. / / / / / / / / / | -----|----------|----------|----------|----------|----------| 00:00 01:00 02:00 03:00 04:00 05:00
params (Optional[Dict[str, Any]], default None): The standard Meerschaum
params
query dictionary.- limit (Optional[int], default None): If provided, cap the number of rows to be returned.
- fresh (bool, default False):
If
True
, Ignore local cache and pull directly from the instance connector. Only comes into effect if a pipe was created withcache=True
. - debug (bool default False): Verbosity toggle.
Returns
- A
pd.DataFrame
for the pipe's data corresponding to the provided parameters. Backtrack data - is a convenient way to get a pipe's data "backtracked" from the most recent datetime.
519def get_rowcount( 520 self, 521 begin: Union[datetime, int, None] = None, 522 end: Union[datetime, int, None] = None, 523 params: Optional[Dict[str, Any]] = None, 524 remote: bool = False, 525 debug: bool = False 526) -> int: 527 """ 528 Get a Pipe's instance or remote rowcount. 529 530 Parameters 531 ---------- 532 begin: Optional[datetime], default None 533 Count rows where datetime > begin. 534 535 end: Optional[datetime], default None 536 Count rows where datetime < end. 537 538 remote: bool, default False 539 Count rows from a pipe's remote source. 540 **NOTE**: This is experimental! 541 542 debug: bool, default False 543 Verbosity toggle. 544 545 Returns 546 ------- 547 An `int` of the number of rows in the pipe corresponding to the provided parameters. 548 Returned 0 if the pipe does not exist. 549 """ 550 from meerschaum.utils.warnings import warn 551 from meerschaum.utils.venv import Venv 552 from meerschaum.connectors import get_connector_plugin 553 554 connector = self.instance_connector if not remote else self.connector 555 try: 556 with Venv(get_connector_plugin(connector)): 557 rowcount = connector.get_pipe_rowcount( 558 self, 559 begin=begin, 560 end=end, 561 params=params, 562 remote=remote, 563 debug=debug, 564 ) 565 if rowcount is None: 566 return 0 567 return rowcount 568 except AttributeError as e: 569 warn(e) 570 if remote: 571 return 0 572 warn(f"Failed to get a rowcount for {self}.") 573 return 0
Get a Pipe's instance or remote rowcount.
Parameters
- begin (Optional[datetime], default None): Count rows where datetime > begin.
- end (Optional[datetime], default None): Count rows where datetime < end.
- remote (bool, default False): Count rows from a pipe's remote source. NOTE: This is experimental!
- debug (bool, default False): Verbosity toggle.
Returns
- An
int
of the number of rows in the pipe corresponding to the provided parameters. - Returned 0 if the pipe does not exist.
576def get_chunk_interval( 577 self, 578 chunk_interval: Union[timedelta, int, None] = None, 579 debug: bool = False, 580) -> Union[timedelta, int]: 581 """ 582 Get the chunk interval to use for this pipe. 583 584 Parameters 585 ---------- 586 chunk_interval: Union[timedelta, int, None], default None 587 If provided, coerce this value into the correct type. 588 For example, if the datetime axis is an integer, then 589 return the number of minutes. 590 591 Returns 592 ------- 593 The chunk interval (`timedelta` or `int`) to use with this pipe's `datetime` axis. 594 """ 595 default_chunk_minutes = get_config('pipes', 'parameters', 'verify', 'chunk_minutes') 596 configured_chunk_minutes = self.parameters.get('verify', {}).get('chunk_minutes', None) 597 chunk_minutes = ( 598 (configured_chunk_minutes or default_chunk_minutes) 599 if chunk_interval is None 600 else ( 601 chunk_interval 602 if isinstance(chunk_interval, int) 603 else int(chunk_interval.total_seconds() / 60) 604 ) 605 ) 606 607 dt_col = self.columns.get('datetime', None) 608 if dt_col is None: 609 return timedelta(minutes=chunk_minutes) 610 611 dt_dtype = self.dtypes.get(dt_col, 'datetime64[ns]') 612 if 'int' in dt_dtype.lower(): 613 return chunk_minutes 614 return timedelta(minutes=chunk_minutes)
Get the chunk interval to use for this pipe.
Parameters
- chunk_interval (Union[timedelta, int, None], default None): If provided, coerce this value into the correct type. For example, if the datetime axis is an integer, then return the number of minutes.
Returns
- The chunk interval (
timedelta
orint
) to use with this pipe'sdatetime
axis.
617def get_chunk_bounds( 618 self, 619 begin: Union[datetime, int, None] = None, 620 end: Union[datetime, int, None] = None, 621 bounded: bool = False, 622 chunk_interval: Union[timedelta, int, None] = None, 623 debug: bool = False, 624) -> List[ 625 Tuple[ 626 Union[datetime, int, None], 627 Union[datetime, int, None], 628 ] 629]: 630 """ 631 Return a list of datetime bounds for iterating over the pipe's `datetime` axis. 632 633 Parameters 634 ---------- 635 begin: Union[datetime, int, None], default None 636 If provided, do not select less than this value. 637 Otherwise the first chunk will be unbounded. 638 639 end: Union[datetime, int, None], default None 640 If provided, do not select greater than or equal to this value. 641 Otherwise the last chunk will be unbounded. 642 643 bounded: bool, default False 644 If `True`, do not include `None` in the first chunk. 645 646 chunk_interval: Union[timedelta, int, None], default None 647 If provided, use this interval for the size of chunk boundaries. 648 The default value for this pipe may be set 649 under `pipe.parameters['verify']['chunk_minutes']`. 650 651 debug: bool, default False 652 Verbosity toggle. 653 654 Returns 655 ------- 656 A list of chunk bounds (datetimes or integers). 657 If unbounded, the first and last chunks will include `None`. 658 """ 659 include_less_than_begin = not bounded and begin is None 660 include_greater_than_end = not bounded and end is None 661 if begin is None: 662 begin = self.get_sync_time(newest=False, debug=debug) 663 if end is None: 664 end = self.get_sync_time(newest=True, debug=debug) 665 if begin is None and end is None: 666 return [(None, None)] 667 668 ### Set the chunk interval under `pipe.parameters['verify']['chunk_minutes']`. 669 chunk_interval = self.get_chunk_interval(chunk_interval, debug=debug) 670 671 ### Build a list of tuples containing the chunk boundaries 672 ### so that we can sync multiple chunks in parallel. 673 ### Run `verify pipes --workers 1` to sync chunks in series. 674 chunk_bounds = [] 675 begin_cursor = begin 676 while begin_cursor < end: 677 end_cursor = begin_cursor + chunk_interval 678 chunk_bounds.append((begin_cursor, end_cursor)) 679 begin_cursor = end_cursor 680 681 ### The chunk interval might be too large. 682 if not chunk_bounds and end >= begin: 683 chunk_bounds = [(begin, end)] 684 685 ### Truncate the last chunk to the end timestamp. 686 if chunk_bounds[-1][1] > end: 687 chunk_bounds[-1] = (chunk_bounds[-1][0], end) 688 689 ### Pop the last chunk if its bounds are equal. 690 if chunk_bounds[-1][0] == chunk_bounds[-1][1]: 691 chunk_bounds = chunk_bounds[:-1] 692 693 if include_less_than_begin: 694 chunk_bounds = [(None, begin)] + chunk_bounds 695 if include_greater_than_end: 696 chunk_bounds = chunk_bounds + [(end, None)] 697 698 return chunk_bounds
Return a list of datetime bounds for iterating over the pipe's datetime
axis.
Parameters
- begin (Union[datetime, int, None], default None): If provided, do not select less than this value. Otherwise the first chunk will be unbounded.
- end (Union[datetime, int, None], default None): If provided, do not select greater than or equal to this value. Otherwise the last chunk will be unbounded.
- bounded (bool, default False):
If
True
, do not includeNone
in the first chunk. - chunk_interval (Union[timedelta, int, None], default None):
If provided, use this interval for the size of chunk boundaries.
The default value for this pipe may be set
under
pipe.parameters['verify']['chunk_minutes']
. - debug (bool, default False): Verbosity toggle.
Returns
- A list of chunk bounds (datetimes or integers).
- If unbounded, the first and last chunks will include
None
.
12def register( 13 self, 14 debug: bool = False, 15 **kw: Any 16 ) -> SuccessTuple: 17 """ 18 Register a new Pipe along with its attributes. 19 20 Parameters 21 ---------- 22 debug: bool, default False 23 Verbosity toggle. 24 25 kw: Any 26 Keyword arguments to pass to `instance_connector.register_pipe()`. 27 28 Returns 29 ------- 30 A `SuccessTuple` of success, message. 31 """ 32 if self.temporary: 33 return False, "Cannot register pipes created with `temporary=True` (read-only)." 34 35 from meerschaum.utils.formatting import get_console 36 from meerschaum.utils.venv import Venv 37 from meerschaum.connectors import get_connector_plugin, custom_types 38 from meerschaum.config._patch import apply_patch_to_config 39 40 import warnings 41 with warnings.catch_warnings(): 42 warnings.simplefilter('ignore') 43 try: 44 _conn = self.connector 45 except Exception as e: 46 _conn = None 47 48 if ( 49 _conn is not None 50 and 51 (_conn.type == 'plugin' or _conn.type in custom_types) 52 and 53 getattr(_conn, 'register', None) is not None 54 ): 55 try: 56 with Venv(get_connector_plugin(_conn), debug=debug): 57 params = self.connector.register(self) 58 except Exception as e: 59 get_console().print_exception() 60 params = None 61 params = {} if params is None else params 62 if not isinstance(params, dict): 63 from meerschaum.utils.warnings import warn 64 warn( 65 f"Invalid parameters returned from `register()` in connector {self.connector}:\n" 66 + f"{params}" 67 ) 68 else: 69 self.parameters = apply_patch_to_config(params, self.parameters) 70 71 if not self.parameters: 72 cols = self.columns if self.columns else {'datetime': None, 'id': None} 73 self.parameters = { 74 'columns': cols, 75 } 76 77 with Venv(get_connector_plugin(self.instance_connector)): 78 return self.instance_connector.register_pipe(self, debug=debug, **kw)
Register a new Pipe along with its attributes.
Parameters
- debug (bool, default False): Verbosity toggle.
- kw (Any):
Keyword arguments to pass to
instance_connector.register_pipe()
.
Returns
- A
SuccessTuple
of success, message.
14@property 15def attributes(self) -> Dict[str, Any]: 16 """ 17 Return a dictionary of a pipe's keys and parameters. 18 These values are reflected directly from the pipes table of the instance. 19 """ 20 import time 21 from meerschaum.config import get_config 22 from meerschaum.config._patch import apply_patch_to_config 23 from meerschaum.utils.venv import Venv 24 from meerschaum.connectors import get_connector_plugin 25 26 timeout_seconds = get_config('pipes', 'attributes', 'local_cache_timeout_seconds') 27 28 if '_attributes' not in self.__dict__: 29 self._attributes = {} 30 31 now = time.perf_counter() 32 last_refresh = self.__dict__.get('_attributes_sync_time', None) 33 timed_out = ( 34 last_refresh is None 35 or 36 (timeout_seconds is not None and (now - last_refresh) >= timeout_seconds) 37 ) 38 if not self.temporary and timed_out: 39 self._attributes_sync_time = now 40 local_attributes = self.__dict__.get('_attributes', {}) 41 with Venv(get_connector_plugin(self.instance_connector)): 42 instance_attributes = self.instance_connector.get_pipe_attributes(self) 43 self._attributes = apply_patch_to_config(instance_attributes, local_attributes) 44 return self._attributes
Return a dictionary of a pipe's keys and parameters. These values are reflected directly from the pipes table of the instance.
47@property 48def parameters(self) -> Optional[Dict[str, Any]]: 49 """ 50 Return the parameters dictionary of the pipe. 51 """ 52 if 'parameters' not in self.attributes: 53 self.attributes['parameters'] = {} 54 return self.attributes['parameters']
Return the parameters dictionary of the pipe.
66@property 67def columns(self) -> Union[Dict[str, str], None]: 68 """ 69 Return the `columns` dictionary defined in `meerschaum.Pipe.parameters`. 70 """ 71 if 'columns' not in self.parameters: 72 self.parameters['columns'] = {} 73 cols = self.parameters['columns'] 74 if not isinstance(cols, dict): 75 cols = {} 76 self.parameters['columns'] = cols 77 return cols
Return the columns
dictionary defined in meerschaum.Pipe.parameters
.
94@property 95def indices(self) -> Union[Dict[str, Union[str, List[str]]], None]: 96 """ 97 Return the `indices` dictionary defined in `meerschaum.Pipe.parameters`. 98 """ 99 indices_key = ( 100 'indexes' 101 if 'indexes' in self.parameters 102 else 'indices' 103 ) 104 if indices_key not in self.parameters: 105 self.parameters[indices_key] = {} 106 _indices = self.parameters[indices_key] 107 if not isinstance(_indices, dict): 108 _indices = {} 109 self.parameters[indices_key] = _indices 110 return {**self.columns, **_indices}
Return the indices
dictionary defined in meerschaum.Pipe.parameters
.
113@property 114def indexes(self) -> Union[Dict[str, Union[str, List[str]]], None]: 115 """ 116 Alias for `meerschaum.Pipe.indices`. 117 """ 118 return self.indices
Alias for meerschaum.Pipe.indices
.
171@property 172def dtypes(self) -> Union[Dict[str, Any], None]: 173 """ 174 If defined, return the `dtypes` dictionary defined in `meerschaum.Pipe.parameters`. 175 """ 176 from meerschaum.config._patch import apply_patch_to_config 177 configured_dtypes = self.parameters.get('dtypes', {}) 178 remote_dtypes = self.infer_dtypes(persist=False) 179 patched_dtypes = apply_patch_to_config(remote_dtypes, configured_dtypes) 180 return patched_dtypes
If defined, return the dtypes
dictionary defined in meerschaum.Pipe.parameters
.
192def get_columns(self, *args: str, error: bool = False) -> Union[str, Tuple[str]]: 193 """ 194 Check if the requested columns are defined. 195 196 Parameters 197 ---------- 198 *args: str 199 The column names to be retrieved. 200 201 error: bool, default False 202 If `True`, raise an `Exception` if the specified column is not defined. 203 204 Returns 205 ------- 206 A tuple of the same size of `args` or a `str` if `args` is a single argument. 207 208 Examples 209 -------- 210 >>> pipe = mrsm.Pipe('test', 'test') 211 >>> pipe.columns = {'datetime': 'dt', 'id': 'id'} 212 >>> pipe.get_columns('datetime', 'id') 213 ('dt', 'id') 214 >>> pipe.get_columns('value', error=True) 215 Exception: 🛑 Missing 'value' column for Pipe('test', 'test'). 216 """ 217 from meerschaum.utils.warnings import error as _error, warn 218 if not args: 219 args = tuple(self.columns.keys()) 220 col_names = [] 221 for col in args: 222 col_name = None 223 try: 224 col_name = self.columns[col] 225 if col_name is None and error: 226 _error(f"Please define the name of the '{col}' column for {self}.") 227 except Exception as e: 228 col_name = None 229 if col_name is None and error: 230 _error(f"Missing '{col}'" + f" column for {self}.") 231 col_names.append(col_name) 232 if len(col_names) == 1: 233 return col_names[0] 234 return tuple(col_names)
Check if the requested columns are defined.
Parameters
- *args (str): The column names to be retrieved.
- error (bool, default False):
If
True
, raise anException
if the specified column is not defined.
Returns
- A tuple of the same size of
args
or astr
ifargs
is a single argument.
Examples
>>> pipe = mrsm.Pipe('test', 'test')
>>> pipe.columns = {'datetime': 'dt', 'id': 'id'}
>>> pipe.get_columns('datetime', 'id')
('dt', 'id')
>>> pipe.get_columns('value', error=True)
Exception: 🛑 Missing 'value' column for Pipe('test', 'test').
237def get_columns_types(self, debug: bool = False) -> Union[Dict[str, str], None]: 238 """ 239 Get a dictionary of a pipe's column names and their types. 240 241 Parameters 242 ---------- 243 debug: bool, default False: 244 Verbosity toggle. 245 246 Returns 247 ------- 248 A dictionary of column names (`str`) to column types (`str`). 249 250 Examples 251 -------- 252 >>> pipe.get_columns_types() 253 { 254 'dt': 'TIMESTAMP WITHOUT TIMEZONE', 255 'id': 'BIGINT', 256 'val': 'DOUBLE PRECISION', 257 } 258 >>> 259 """ 260 from meerschaum.utils.venv import Venv 261 from meerschaum.connectors import get_connector_plugin 262 263 with Venv(get_connector_plugin(self.instance_connector)): 264 return self.instance_connector.get_pipe_columns_types(self, debug=debug)
Get a dictionary of a pipe's column names and their types.
Parameters
- debug (bool, default False:): Verbosity toggle.
Returns
- A dictionary of column names (
str
) to column types (str
).
Examples
>>> pipe.get_columns_types()
{
'dt': 'TIMESTAMP WITHOUT TIMEZONE',
'id': 'BIGINT',
'val': 'DOUBLE PRECISION',
}
>>>
491def get_indices(self) -> Dict[str, str]: 492 """ 493 Return a dictionary mapping index keys to their names on the database. 494 495 Returns 496 ------- 497 A dictionary of index keys to column names. 498 """ 499 _parameters = self.parameters 500 _index_template = _parameters.get('index_template', "IX_{target}_{column_names}") 501 _indices = self.indices 502 _target = self.target 503 _column_names = { 504 ix: ( 505 '_'.join(cols) 506 if isinstance(cols, (list, tuple)) 507 else str(cols) 508 ) 509 for ix, cols in _indices.items() 510 if cols 511 } 512 _index_names = { 513 ix: ( 514 _index_template.format( 515 target=_target, 516 column_names=column_names, 517 connector_keys=self.connector_keys, 518 metric_key=self.connector_key, 519 location_key=self.location_key, 520 ) 521 ) 522 for ix, column_names in _column_names.items() 523 } 524 return _index_names
Return a dictionary mapping index keys to their names on the database.
Returns
- A dictionary of index keys to column names.
267def get_id(self, **kw: Any) -> Union[int, None]: 268 """ 269 Fetch a pipe's ID from its instance connector. 270 If the pipe does not exist, return `None`. 271 """ 272 if self.temporary: 273 return None 274 from meerschaum.utils.venv import Venv 275 from meerschaum.connectors import get_connector_plugin 276 277 with Venv(get_connector_plugin(self.instance_connector)): 278 return self.instance_connector.get_pipe_id(self, **kw)
Fetch a pipe's ID from its instance connector.
If the pipe does not exist, return None
.
281@property 282def id(self) -> Union[int, None]: 283 """ 284 Fetch and cache a pipe's ID. 285 """ 286 if not ('_id' in self.__dict__ and self._id): 287 self._id = self.get_id() 288 return self._id
Fetch and cache a pipe's ID.
291def get_val_column(self, debug: bool = False) -> Union[str, None]: 292 """ 293 Return the name of the value column if it's defined, otherwise make an educated guess. 294 If not set in the `columns` dictionary, return the first numeric column that is not 295 an ID or datetime column. 296 If none may be found, return `None`. 297 298 Parameters 299 ---------- 300 debug: bool, default False: 301 Verbosity toggle. 302 303 Returns 304 ------- 305 Either a string or `None`. 306 """ 307 from meerschaum.utils.debug import dprint 308 if debug: 309 dprint('Attempting to determine the value column...') 310 try: 311 val_name = self.get_columns('value') 312 except Exception as e: 313 val_name = None 314 if val_name is not None: 315 if debug: 316 dprint(f"Value column: {val_name}") 317 return val_name 318 319 cols = self.columns 320 if cols is None: 321 if debug: 322 dprint('No columns could be determined. Returning...') 323 return None 324 try: 325 dt_name = self.get_columns('datetime', error=False) 326 except Exception as e: 327 dt_name = None 328 try: 329 id_name = self.get_columns('id', errors=False) 330 except Exception as e: 331 id_name = None 332 333 if debug: 334 dprint(f"dt_name: {dt_name}") 335 dprint(f"id_name: {id_name}") 336 337 cols_types = self.get_columns_types(debug=debug) 338 if cols_types is None: 339 return None 340 if debug: 341 dprint(f"cols_types: {cols_types}") 342 if dt_name is not None: 343 cols_types.pop(dt_name, None) 344 if id_name is not None: 345 cols_types.pop(id_name, None) 346 347 candidates = [] 348 candidate_keywords = {'float', 'double', 'precision', 'int', 'numeric',} 349 for search_term in candidate_keywords: 350 for col, typ in cols_types.items(): 351 if search_term in typ.lower(): 352 candidates.append(col) 353 break 354 if not candidates: 355 if debug: 356 dprint("No value column could be determined.") 357 return None 358 359 return candidates[0]
Return the name of the value column if it's defined, otherwise make an educated guess.
If not set in the columns
dictionary, return the first numeric column that is not
an ID or datetime column.
If none may be found, return None
.
Parameters
- debug (bool, default False:): Verbosity toggle.
Returns
- Either a string or
None
.
362@property 363def parents(self) -> List[meerschaum.Pipe]: 364 """ 365 Return a list of `meerschaum.Pipe` objects to be designated as parents. 366 """ 367 if 'parents' not in self.parameters: 368 return [] 369 from meerschaum.utils.warnings import warn 370 _parents_keys = self.parameters['parents'] 371 if not isinstance(_parents_keys, list): 372 warn( 373 f"Please ensure the parents for {self} are defined as a list of keys.", 374 stacklevel = 4 375 ) 376 return [] 377 from meerschaum import Pipe 378 _parents = [] 379 for keys in _parents_keys: 380 try: 381 p = Pipe(**keys) 382 except Exception as e: 383 warn(f"Unable to build parent with keys '{keys}' for {self}:\n{e}") 384 continue 385 _parents.append(p) 386 return _parents
Return a list of meerschaum.Pipe
objects to be designated as parents.
389@property 390def children(self) -> List[meerschaum.Pipe]: 391 """ 392 Return a list of `meerschaum.Pipe` objects to be designated as children. 393 """ 394 if 'children' not in self.parameters: 395 return [] 396 from meerschaum.utils.warnings import warn 397 _children_keys = self.parameters['children'] 398 if not isinstance(_children_keys, list): 399 warn( 400 f"Please ensure the children for {self} are defined as a list of keys.", 401 stacklevel = 4 402 ) 403 return [] 404 from meerschaum import Pipe 405 _children = [] 406 for keys in _children_keys: 407 try: 408 p = Pipe(**keys) 409 except Exception as e: 410 warn(f"Unable to build parent with keys '{keys}' for {self}:\n{e}") 411 continue 412 _children.append(p) 413 return _children
Return a list of meerschaum.Pipe
objects to be designated as children.
416@property 417def target(self) -> str: 418 """ 419 The target table name. 420 You can set the target name under on of the following keys 421 (checked in this order): 422 - `target` 423 - `target_name` 424 - `target_table` 425 - `target_table_name` 426 """ 427 if 'target' not in self.parameters: 428 target = self._target_legacy() 429 potential_keys = ('target_name', 'target_table', 'target_table_name') 430 for k in potential_keys: 431 if k in self.parameters: 432 target = self.parameters[k] 433 break 434 435 if self.instance_connector.type == 'sql': 436 from meerschaum.utils.sql import truncate_item_name 437 truncated_target = truncate_item_name(target, self.instance_connector.flavor) 438 if truncated_target != target: 439 warn( 440 f"The target '{target}' is too long for '{self.instance_connector.flavor}', " 441 + f"will use {truncated_target} instead." 442 ) 443 target = truncated_target 444 445 self.target = target 446 return self.parameters['target']
The target table name. You can set the target name under on of the following keys (checked in this order):
target
target_name
target_table
target_table_name
469def guess_datetime(self) -> Union[str, None]: 470 """ 471 Try to determine a pipe's datetime column. 472 """ 473 _dtypes = self.dtypes 474 475 ### Abort if the user explictly disallows a datetime index. 476 if 'datetime' in _dtypes: 477 if _dtypes['datetime'] is None: 478 return None 479 480 from meerschaum.utils.dtypes import are_dtypes_equal 481 dt_cols = [ 482 col 483 for col, typ in _dtypes.items() 484 if are_dtypes_equal(typ, 'datetime') 485 ] 486 if not dt_cols: 487 return None 488 return dt_cols[0]
Try to determine a pipe's datetime column.
12def show( 13 self, 14 nopretty: bool = False, 15 debug: bool = False, 16 **kw 17 ) -> SuccessTuple: 18 """ 19 Show attributes of a Pipe. 20 21 Parameters 22 ---------- 23 nopretty: bool, default False 24 If `True`, simply print the JSON of the pipe's attributes. 25 26 debug: bool, default False 27 Verbosity toggle. 28 29 Returns 30 ------- 31 A `SuccessTuple` of success, message. 32 33 """ 34 import json 35 from meerschaum.utils.formatting import ( 36 pprint, make_header, ANSI, highlight_pipes, fill_ansi, get_console, 37 ) 38 from meerschaum.utils.packages import import_rich, attempt_import 39 from meerschaum.utils.warnings import info 40 attributes_json = json.dumps(self.attributes) 41 if not nopretty: 42 _to_print = f"Attributes for {self}:" 43 if ANSI: 44 _to_print = fill_ansi(highlight_pipes(make_header(_to_print)), 'magenta') 45 print(_to_print) 46 rich = import_rich() 47 rich_json = attempt_import('rich.json') 48 get_console().print(rich_json.JSON(attributes_json)) 49 else: 50 print(_to_print) 51 else: 52 print(attributes_json) 53 54 return True, "Success"
Show attributes of a Pipe.
Parameters
- nopretty (bool, default False):
If
True
, simply print the JSON of the pipe's attributes. - debug (bool, default False): Verbosity toggle.
Returns
- A
SuccessTuple
of success, message.
21def edit( 22 self, 23 patch: bool = False, 24 interactive: bool = False, 25 debug: bool = False, 26 **kw: Any 27) -> SuccessTuple: 28 """ 29 Edit a Pipe's configuration. 30 31 Parameters 32 ---------- 33 patch: bool, default False 34 If `patch` is True, update parameters by cascading rather than overwriting. 35 interactive: bool, default False 36 If `True`, open an editor for the user to make changes to the pipe's YAML file. 37 debug: bool, default False 38 Verbosity toggle. 39 40 Returns 41 ------- 42 A `SuccessTuple` of success, message. 43 44 """ 45 from meerschaum.utils.venv import Venv 46 from meerschaum.connectors import get_connector_plugin 47 48 if self.temporary: 49 return False, "Cannot edit pipes created with `temporary=True` (read-only)." 50 51 if not interactive: 52 with Venv(get_connector_plugin(self.instance_connector)): 53 return self.instance_connector.edit_pipe(self, patch=patch, debug=debug, **kw) 54 55 from meerschaum.config._paths import PIPES_CACHE_RESOURCES_PATH 56 from meerschaum.utils.misc import edit_file 57 parameters_filename = str(self) + '.yaml' 58 parameters_path = PIPES_CACHE_RESOURCES_PATH / parameters_filename 59 60 from meerschaum.utils.yaml import yaml 61 62 edit_text = f"Edit the parameters for {self}" 63 edit_top = '#' * (len(edit_text) + 4) 64 edit_header = edit_top + f'\n# {edit_text} #\n' + edit_top + '\n\n' 65 66 from meerschaum.config import get_config 67 parameters = dict(get_config('pipes', 'parameters', patch=True)) 68 from meerschaum.config._patch import apply_patch_to_config 69 parameters = apply_patch_to_config(parameters, self.parameters) 70 71 ### write parameters to yaml file 72 with open(parameters_path, 'w+') as f: 73 f.write(edit_header) 74 yaml.dump(parameters, stream=f, sort_keys=False) 75 76 ### only quit editing if yaml is valid 77 editing = True 78 while editing: 79 edit_file(parameters_path) 80 try: 81 with open(parameters_path, 'r') as f: 82 file_parameters = yaml.load(f.read()) 83 except Exception as e: 84 from meerschaum.utils.warnings import warn 85 warn(f"Invalid format defined for '{self}':\n\n{e}") 86 input(f"Press [Enter] to correct the configuration for '{self}': ") 87 else: 88 editing = False 89 90 self.parameters = file_parameters 91 92 if debug: 93 from meerschaum.utils.formatting import pprint 94 pprint(self.parameters) 95 96 with Venv(get_connector_plugin(self.instance_connector)): 97 return self.instance_connector.edit_pipe(self, patch=patch, debug=debug, **kw)
Edit a Pipe's configuration.
Parameters
- patch (bool, default False):
If
patch
is True, update parameters by cascading rather than overwriting. - interactive (bool, default False):
If
True
, open an editor for the user to make changes to the pipe's YAML file. - debug (bool, default False): Verbosity toggle.
Returns
- A
SuccessTuple
of success, message.
100def edit_definition( 101 self, 102 yes: bool = False, 103 noask: bool = False, 104 force: bool = False, 105 debug : bool = False, 106 **kw : Any 107) -> SuccessTuple: 108 """ 109 Edit a pipe's definition file and update its configuration. 110 **NOTE:** This function is interactive and should not be used in automated scripts! 111 112 Returns 113 ------- 114 A `SuccessTuple` of success, message. 115 116 """ 117 if self.temporary: 118 return False, "Cannot edit pipes created with `temporary=True` (read-only)." 119 120 from meerschaum.connectors import instance_types 121 if (self.connector is None) or self.connector.type not in instance_types: 122 return self.edit(interactive=True, debug=debug, **kw) 123 124 import json 125 from meerschaum.utils.warnings import info, warn 126 from meerschaum.utils.debug import dprint 127 from meerschaum.config._patch import apply_patch_to_config 128 from meerschaum.utils.misc import edit_file 129 130 _parameters = self.parameters 131 if 'fetch' not in _parameters: 132 _parameters['fetch'] = {} 133 134 def _edit_api(): 135 from meerschaum.utils.prompt import prompt, yes_no 136 info( 137 f"Please enter the keys of the source pipe from '{self.connector}'.\n" + 138 "Type 'None' for None, or empty when there is no default. Press [CTRL+C] to skip." 139 ) 140 141 _keys = { 'connector_keys' : None, 'metric_key' : None, 'location_key' : None } 142 for k in _keys: 143 _keys[k] = _parameters['fetch'].get(k, None) 144 145 for k, v in _keys.items(): 146 try: 147 _keys[k] = prompt(k.capitalize().replace('_', ' ') + ':', icon=True, default=v) 148 except KeyboardInterrupt: 149 continue 150 if _keys[k] in ('', 'None', '\'None\'', '[None]'): 151 _keys[k] = None 152 153 _parameters['fetch'] = apply_patch_to_config(_parameters['fetch'], _keys) 154 155 info("You may optionally specify additional filter parameters as JSON.") 156 print(" Parameters are translated into a 'WHERE x AND y' clause, and lists are IN clauses.") 157 print(" For example, the following JSON would correspond to 'WHERE x = 1 AND y IN (2, 3)':") 158 print(json.dumps({'x': 1, 'y': [2, 3]}, indent=2, separators=(',', ': '))) 159 if force or yes_no( 160 "Would you like to add additional filter parameters?", 161 yes=yes, noask=noask 162 ): 163 from meerschaum.config._paths import PIPES_CACHE_RESOURCES_PATH 164 definition_filename = str(self) + '.json' 165 definition_path = PIPES_CACHE_RESOURCES_PATH / definition_filename 166 try: 167 definition_path.touch() 168 with open(definition_path, 'w+') as f: 169 json.dump(_parameters.get('fetch', {}).get('params', {}), f, indent=2) 170 except Exception as e: 171 return False, f"Failed writing file '{definition_path}':\n" + str(e) 172 173 _params = None 174 while True: 175 edit_file(definition_path) 176 try: 177 with open(definition_path, 'r') as f: 178 _params = json.load(f) 179 except Exception as e: 180 warn(f'Failed to read parameters JSON:\n{e}', stack=False) 181 if force or yes_no( 182 "Would you like to try again?\n " 183 + "If not, the parameters JSON file will be ignored.", 184 noask=noask, yes=yes 185 ): 186 continue 187 _params = None 188 break 189 if _params is not None: 190 if 'fetch' not in _parameters: 191 _parameters['fetch'] = {} 192 _parameters['fetch']['params'] = _params 193 194 self.parameters = _parameters 195 return True, "Success" 196 197 def _edit_sql(): 198 import pathlib, os, textwrap 199 from meerschaum.config._paths import PIPES_CACHE_RESOURCES_PATH 200 from meerschaum.utils.misc import edit_file 201 definition_filename = str(self) + '.sql' 202 definition_path = PIPES_CACHE_RESOURCES_PATH / definition_filename 203 204 sql_definition = _parameters['fetch'].get('definition', None) 205 if sql_definition is None: 206 sql_definition = '' 207 sql_definition = textwrap.dedent(sql_definition).lstrip() 208 209 try: 210 definition_path.touch() 211 with open(definition_path, 'w+') as f: 212 f.write(sql_definition) 213 except Exception as e: 214 return False, f"Failed writing file '{definition_path}':\n" + str(e) 215 216 edit_file(definition_path) 217 try: 218 with open(definition_path, 'r') as f: 219 file_definition = f.read() 220 except Exception as e: 221 return False, f"Failed reading file '{definition_path}':\n" + str(e) 222 223 if sql_definition == file_definition: 224 return False, f"No changes made to definition for {self}." 225 226 if ' ' not in file_definition: 227 return False, f"Invalid SQL definition for {self}." 228 229 if debug: 230 dprint("Read SQL definition:\n\n" + file_definition) 231 _parameters['fetch']['definition'] = file_definition 232 self.parameters = _parameters 233 return True, "Success" 234 235 locals()['_edit_' + str(self.connector.type)]() 236 return self.edit(interactive=False, debug=debug, **kw)
Edit a pipe's definition file and update its configuration. NOTE: This function is interactive and should not be used in automated scripts!
Returns
- A
SuccessTuple
of success, message.
13def update(self, *args, **kw) -> SuccessTuple: 14 """ 15 Update a pipe's parameters in its instance. 16 """ 17 kw['interactive'] = False 18 return self.edit(*args, **kw)
Update a pipe's parameters in its instance.
40def sync( 41 self, 42 df: Union[ 43 pd.DataFrame, 44 Dict[str, List[Any]], 45 List[Dict[str, Any]], 46 InferFetch 47 ] = InferFetch, 48 begin: Union[datetime, int, str, None] = '', 49 end: Union[datetime, int, None] = None, 50 force: bool = False, 51 retries: int = 10, 52 min_seconds: int = 1, 53 check_existing: bool = True, 54 blocking: bool = True, 55 workers: Optional[int] = None, 56 callback: Optional[Callable[[Tuple[bool, str]], Any]] = None, 57 error_callback: Optional[Callable[[Exception], Any]] = None, 58 chunksize: Optional[int] = -1, 59 sync_chunks: bool = True, 60 debug: bool = False, 61 _inplace: bool = True, 62 **kw: Any 63) -> SuccessTuple: 64 """ 65 Fetch new data from the source and update the pipe's table with new data. 66 67 Get new remote data via fetch, get existing data in the same time period, 68 and merge the two, only keeping the unseen data. 69 70 Parameters 71 ---------- 72 df: Union[None, pd.DataFrame, Dict[str, List[Any]]], default None 73 An optional DataFrame to sync into the pipe. Defaults to `None`. 74 75 begin: Union[datetime, int, str, None], default '' 76 Optionally specify the earliest datetime to search for data. 77 78 end: Union[datetime, int, str, None], default None 79 Optionally specify the latest datetime to search for data. 80 81 force: bool, default False 82 If `True`, keep trying to sync untul `retries` attempts. 83 84 retries: int, default 10 85 If `force`, how many attempts to try syncing before declaring failure. 86 87 min_seconds: Union[int, float], default 1 88 If `force`, how many seconds to sleep between retries. Defaults to `1`. 89 90 check_existing: bool, default True 91 If `True`, pull and diff with existing data from the pipe. 92 93 blocking: bool, default True 94 If `True`, wait for sync to finish and return its result, otherwise 95 asyncronously sync (oxymoron?) and return success. Defaults to `True`. 96 Only intended for specific scenarios. 97 98 workers: Optional[int], default None 99 If provided and the instance connector is thread-safe 100 (`pipe.instance_connector.IS_THREAD_SAFE is True`), 101 limit concurrent sync to this many threads. 102 103 callback: Optional[Callable[[Tuple[bool, str]], Any]], default None 104 Callback function which expects a SuccessTuple as input. 105 Only applies when `blocking=False`. 106 107 error_callback: Optional[Callable[[Exception], Any]], default None 108 Callback function which expects an Exception as input. 109 Only applies when `blocking=False`. 110 111 chunksize: int, default -1 112 Specify the number of rows to sync per chunk. 113 If `-1`, resort to system configuration (default is `900`). 114 A `chunksize` of `None` will sync all rows in one transaction. 115 116 sync_chunks: bool, default True 117 If possible, sync chunks while fetching them into memory. 118 119 debug: bool, default False 120 Verbosity toggle. Defaults to False. 121 122 Returns 123 ------- 124 A `SuccessTuple` of success (`bool`) and message (`str`). 125 """ 126 from meerschaum.utils.debug import dprint, _checkpoint 127 from meerschaum.connectors import custom_types 128 from meerschaum.plugins import Plugin 129 from meerschaum.utils.formatting import get_console 130 from meerschaum.utils.venv import Venv 131 from meerschaum.connectors import get_connector_plugin 132 from meerschaum.utils.misc import df_is_chunk_generator, filter_keywords, filter_arguments 133 from meerschaum.utils.pool import get_pool 134 from meerschaum.config import get_config 135 136 if (callback is not None or error_callback is not None) and blocking: 137 warn("Callback functions are only executed when blocking = False. Ignoring...") 138 139 _checkpoint(_total=2, **kw) 140 141 if chunksize == 0: 142 chunksize = None 143 sync_chunks = False 144 145 kw.update({ 146 'begin': begin, 147 'end': end, 148 'force': force, 149 'retries': retries, 150 'min_seconds': min_seconds, 151 'check_existing': check_existing, 152 'blocking': blocking, 153 'workers': workers, 154 'callback': callback, 155 'error_callback': error_callback, 156 'sync_chunks': sync_chunks, 157 'chunksize': chunksize, 158 }) 159 160 ### NOTE: Invalidate `_exists` cache before and after syncing. 161 self._exists = None 162 163 def _sync( 164 p: 'meerschaum.Pipe', 165 df: Union[ 166 'pd.DataFrame', 167 Dict[str, List[Any]], 168 List[Dict[str, Any]], 169 InferFetch 170 ] = InferFetch, 171 ) -> SuccessTuple: 172 if df is None: 173 p._exists = None 174 return ( 175 False, 176 f"You passed `None` instead of data into `sync()` for {p}.\n" 177 + "Omit the DataFrame to infer fetching.", 178 ) 179 ### Ensure that Pipe is registered. 180 if not p.temporary and p.get_id(debug=debug) is None: 181 ### NOTE: This may trigger an interactive session for plugins! 182 register_success, register_msg = p.register(debug=debug) 183 if not register_success: 184 if 'already' not in register_msg: 185 p._exists = None 186 return register_success, register_msg 187 188 ### If connector is a plugin with a `sync()` method, return that instead. 189 ### If the plugin does not have a `sync()` method but does have a `fetch()` method, 190 ### use that instead. 191 ### NOTE: The DataFrame must be omitted for the plugin sync method to apply. 192 ### If a DataFrame is provided, continue as expected. 193 if hasattr(df, 'MRSM_INFER_FETCH'): 194 try: 195 if p.connector is None: 196 if ':' not in p.connector_keys: 197 return True, f"{p} does not support fetching; nothing to do." 198 199 msg = f"{p} does not have a valid connector." 200 if p.connector_keys.startswith('plugin:'): 201 msg += f"\n Perhaps {p.connector_keys} has a syntax error?" 202 p._exists = None 203 return False, msg 204 except Exception: 205 p._exists = None 206 return False, f"Unable to create the connector for {p}." 207 208 ### Sync in place if this is a SQL pipe. 209 if ( 210 str(self.connector) == str(self.instance_connector) 211 and 212 hasattr(self.instance_connector, 'sync_pipe_inplace') 213 and 214 _inplace 215 and 216 get_config('system', 'experimental', 'inplace_sync') 217 ): 218 with Venv(get_connector_plugin(self.instance_connector)): 219 p._exists = None 220 _args, _kwargs = filter_arguments( 221 p.instance_connector.sync_pipe_inplace, 222 p, 223 debug=debug, 224 **kw 225 ) 226 return self.instance_connector.sync_pipe_inplace( 227 *_args, 228 **_kwargs 229 ) 230 231 ### Activate and invoke `sync(pipe)` for plugin connectors with `sync` methods. 232 try: 233 if getattr(p.connector, 'sync', None) is not None: 234 with Venv(get_connector_plugin(p.connector), debug=debug): 235 _args, _kwargs = filter_arguments( 236 p.connector.sync, 237 p, 238 debug=debug, 239 **kw 240 ) 241 return_tuple = p.connector.sync(*_args, **_kwargs) 242 p._exists = None 243 if not isinstance(return_tuple, tuple): 244 return_tuple = ( 245 False, 246 f"Plugin '{p.connector.label}' returned non-tuple value: {return_tuple}" 247 ) 248 return return_tuple 249 250 except Exception as e: 251 get_console().print_exception() 252 msg = f"Failed to sync {p} with exception: '" + str(e) + "'" 253 if debug: 254 error(msg, silent=False) 255 p._exists = None 256 return False, msg 257 258 ### Fetch the dataframe from the connector's `fetch()` method. 259 try: 260 with Venv(get_connector_plugin(p.connector), debug=debug): 261 df = p.fetch( 262 **filter_keywords( 263 p.fetch, 264 debug=debug, 265 **kw 266 ) 267 ) 268 except Exception as e: 269 get_console().print_exception( 270 suppress=[ 271 'meerschaum/core/Pipe/_sync.py', 272 'meerschaum/core/Pipe/_fetch.py', 273 ] 274 ) 275 msg = f"Failed to fetch data from {p.connector}:\n {e}" 276 df = None 277 278 if df is None: 279 p._exists = None 280 return False, f"No data were fetched for {p}." 281 282 if isinstance(df, list): 283 if len(df) == 0: 284 return True, f"No new rows were returned for {p}." 285 286 ### May be a chunk hook results list. 287 if isinstance(df[0], tuple): 288 success = all([_success for _success, _ in df]) 289 message = '\n'.join([_message for _, _message in df]) 290 return success, message 291 292 ### TODO: Depreciate async? 293 if df is True: 294 p._exists = None 295 return True, f"{p} is being synced in parallel." 296 297 ### CHECKPOINT: Retrieved the DataFrame. 298 _checkpoint(**kw) 299 300 ### Allow for dataframe generators or iterables. 301 if df_is_chunk_generator(df): 302 kw['workers'] = p.get_num_workers(kw.get('workers', None)) 303 dt_col = p.columns.get('datetime', None) 304 pool = get_pool(workers=kw.get('workers', 1)) 305 if debug: 306 dprint(f"Received {type(df)}. Attempting to sync first chunk...") 307 308 try: 309 chunk = next(df) 310 except StopIteration: 311 return True, "Received an empty generator; nothing to do." 312 313 chunk_success, chunk_msg = _sync(p, chunk) 314 chunk_msg = '\n' + self._get_chunk_label(chunk, dt_col) + '\n' + chunk_msg 315 if not chunk_success: 316 return chunk_success, f"Unable to sync initial chunk for {p}:\n{chunk_msg}" 317 if debug: 318 dprint("Successfully synced the first chunk, attemping the rest...") 319 320 failed_chunks = [] 321 def _process_chunk(_chunk): 322 try: 323 _chunk_success, _chunk_msg = _sync(p, _chunk) 324 except Exception as e: 325 _chunk_success, _chunk_msg = False, str(e) 326 if not _chunk_success: 327 failed_chunks.append(_chunk) 328 return ( 329 _chunk_success, 330 ( 331 '\n' 332 + self._get_chunk_label(_chunk, dt_col) 333 + '\n' 334 + _chunk_msg 335 ) 336 ) 337 338 results = sorted( 339 [(chunk_success, chunk_msg)] + ( 340 list(pool.imap(_process_chunk, df)) 341 if not df_is_chunk_generator(chunk) 342 else [ 343 _process_chunk(_child_chunks) 344 for _child_chunks in df 345 ] 346 ) 347 ) 348 chunk_messages = [chunk_msg for _, chunk_msg in results] 349 success_bools = [chunk_success for chunk_success, _ in results] 350 success = all(success_bools) 351 msg = '\n'.join(chunk_messages) 352 353 ### If some chunks succeeded, retry the failures. 354 retry_success = True 355 if not success and any(success_bools): 356 if debug: 357 dprint("Retrying failed chunks...") 358 chunks_to_retry = [c for c in failed_chunks] 359 failed_chunks = [] 360 for chunk in chunks_to_retry: 361 chunk_success, chunk_msg = _process_chunk(chunk) 362 msg += f"\n\nRetried chunk:\n{chunk_msg}\n" 363 retry_success = retry_success and chunk_success 364 365 success = success and retry_success 366 return success, msg 367 368 ### Cast to a dataframe and ensure datatypes are what we expect. 369 df = self.enforce_dtypes(df, chunksize=chunksize, debug=debug) 370 371 ### Capture `numeric`, `uuid`, and `json` columns. 372 self._persist_new_json_columns(df, debug=debug) 373 self._persist_new_numeric_columns(df, debug=debug) 374 self._persist_new_uuid_columns(df, debug=debug) 375 376 if debug: 377 dprint( 378 "DataFrame to sync:\n" 379 + ( 380 str(df)[:255] 381 + '...' 382 if len(str(df)) >= 256 383 else str(df) 384 ), 385 **kw 386 ) 387 388 ### if force, continue to sync until success 389 return_tuple = False, f"Did not sync {p}." 390 run = True 391 _retries = 1 392 while run: 393 with Venv(get_connector_plugin(self.instance_connector)): 394 return_tuple = p.instance_connector.sync_pipe( 395 pipe=p, 396 df=df, 397 debug=debug, 398 **kw 399 ) 400 _retries += 1 401 run = (not return_tuple[0]) and force and _retries <= retries 402 if run and debug: 403 dprint(f"Syncing failed for {p}. Attempt ( {_retries} / {retries} )", **kw) 404 dprint(f"Sleeping for {min_seconds} seconds...", **kw) 405 time.sleep(min_seconds) 406 if _retries > retries: 407 warn( 408 f"Unable to sync {p} within {retries} attempt" + 409 ("s" if retries != 1 else "") + "!" 410 ) 411 412 ### CHECKPOINT: Finished syncing. Handle caching. 413 _checkpoint(**kw) 414 if self.cache_pipe is not None: 415 if debug: 416 dprint("Caching retrieved dataframe.", **kw) 417 _sync_cache_tuple = self.cache_pipe.sync(df, debug=debug, **kw) 418 if not _sync_cache_tuple[0]: 419 warn(f"Failed to sync local cache for {self}.") 420 421 self._exists = None 422 return return_tuple 423 424 if blocking: 425 self._exists = None 426 return _sync(self, df = df) 427 428 from meerschaum.utils.threading import Thread 429 def default_callback(result_tuple: SuccessTuple): 430 dprint(f"Asynchronous result from {self}: {result_tuple}", **kw) 431 432 def default_error_callback(x: Exception): 433 dprint(f"Error received for {self}: {x}", **kw) 434 435 if callback is None and debug: 436 callback = default_callback 437 if error_callback is None and debug: 438 error_callback = default_error_callback 439 try: 440 thread = Thread( 441 target=_sync, 442 args=(self,), 443 kwargs={'df': df}, 444 daemon=False, 445 callback=callback, 446 error_callback=error_callback, 447 ) 448 thread.start() 449 except Exception as e: 450 self._exists = None 451 return False, str(e) 452 453 self._exists = None 454 return True, f"Spawned asyncronous sync for {self}."
Fetch new data from the source and update the pipe's table with new data.
Get new remote data via fetch, get existing data in the same time period, and merge the two, only keeping the unseen data.
Parameters
- df (Union[None, pd.DataFrame, Dict[str, List[Any]]], default None):
An optional DataFrame to sync into the pipe. Defaults to
None
. - begin (Union[datetime, int, str, None], default ''): Optionally specify the earliest datetime to search for data.
- end (Union[datetime, int, str, None], default None): Optionally specify the latest datetime to search for data.
- force (bool, default False):
If
True
, keep trying to sync untulretries
attempts. - retries (int, default 10):
If
force
, how many attempts to try syncing before declaring failure. - min_seconds (Union[int, float], default 1):
If
force
, how many seconds to sleep between retries. Defaults to1
. - check_existing (bool, default True):
If
True
, pull and diff with existing data from the pipe. - blocking (bool, default True):
If
True
, wait for sync to finish and return its result, otherwise asyncronously sync (oxymoron?) and return success. Defaults toTrue
. Only intended for specific scenarios. - workers (Optional[int], default None):
If provided and the instance connector is thread-safe
(
pipe.instance_connector.IS_THREAD_SAFE is True
), limit concurrent sync to this many threads. - callback (Optional[Callable[[Tuple[bool, str]], Any]], default None):
Callback function which expects a SuccessTuple as input.
Only applies when
blocking=False
. - error_callback (Optional[Callable[[Exception], Any]], default None):
Callback function which expects an Exception as input.
Only applies when
blocking=False
. - chunksize (int, default -1):
Specify the number of rows to sync per chunk.
If
-1
, resort to system configuration (default is900
). Achunksize
ofNone
will sync all rows in one transaction. - sync_chunks (bool, default True): If possible, sync chunks while fetching them into memory.
- debug (bool, default False): Verbosity toggle. Defaults to False.
Returns
- A
SuccessTuple
of success (bool
) and message (str
).
457def get_sync_time( 458 self, 459 params: Optional[Dict[str, Any]] = None, 460 newest: bool = True, 461 apply_backtrack_interval: bool = False, 462 round_down: bool = False, 463 debug: bool = False 464) -> Union['datetime', None]: 465 """ 466 Get the most recent datetime value for a Pipe. 467 468 Parameters 469 ---------- 470 params: Optional[Dict[str, Any]], default None 471 Dictionary to build a WHERE clause for a specific column. 472 See `meerschaum.utils.sql.build_where`. 473 474 newest: bool, default True 475 If `True`, get the most recent datetime (honoring `params`). 476 If `False`, get the oldest datetime (`ASC` instead of `DESC`). 477 478 apply_backtrack_interval: bool, default False 479 If `True`, subtract the backtrack interval from the sync time. 480 481 round_down: bool, default False 482 If `True`, round down the datetime value to the nearest minute. 483 484 debug: bool, default False 485 Verbosity toggle. 486 487 Returns 488 ------- 489 A `datetime` object if the pipe exists, otherwise `None`. 490 491 """ 492 from meerschaum.utils.venv import Venv 493 from meerschaum.connectors import get_connector_plugin 494 from meerschaum.utils.misc import round_time 495 496 with Venv(get_connector_plugin(self.instance_connector)): 497 sync_time = self.instance_connector.get_sync_time( 498 self, 499 params=params, 500 newest=newest, 501 debug=debug, 502 ) 503 504 if round_down and isinstance(sync_time, datetime): 505 sync_time = round_time(sync_time, timedelta(minutes=1)) 506 507 if apply_backtrack_interval and sync_time is not None: 508 backtrack_interval = self.get_backtrack_interval(debug=debug) 509 try: 510 sync_time -= backtrack_interval 511 except Exception as e: 512 warn(f"Failed to apply backtrack interval:\n{e}") 513 514 return sync_time
Get the most recent datetime value for a Pipe.
Parameters
- params (Optional[Dict[str, Any]], default None):
Dictionary to build a WHERE clause for a specific column.
See
meerschaum.utils.sql.build_where
. - newest (bool, default True):
If
True
, get the most recent datetime (honoringparams
). IfFalse
, get the oldest datetime (ASC
instead ofDESC
). - apply_backtrack_interval (bool, default False):
If
True
, subtract the backtrack interval from the sync time. - round_down (bool, default False):
If
True
, round down the datetime value to the nearest minute. - debug (bool, default False): Verbosity toggle.
Returns
- A
datetime
object if the pipe exists, otherwiseNone
.
517def exists( 518 self, 519 debug : bool = False 520 ) -> bool: 521 """ 522 See if a Pipe's table exists. 523 524 Parameters 525 ---------- 526 debug: bool, default False 527 Verbosity toggle. 528 529 Returns 530 ------- 531 A `bool` corresponding to whether a pipe's underlying table exists. 532 533 """ 534 import time 535 from meerschaum.utils.venv import Venv 536 from meerschaum.connectors import get_connector_plugin 537 from meerschaum.config import STATIC_CONFIG 538 from meerschaum.utils.debug import dprint 539 now = time.perf_counter() 540 exists_timeout_seconds = STATIC_CONFIG['pipes']['exists_timeout_seconds'] 541 542 _exists = self.__dict__.get('_exists', None) 543 if _exists: 544 exists_timestamp = self.__dict__.get('_exists_timestamp', None) 545 if exists_timestamp is not None: 546 delta = now - exists_timestamp 547 if delta < exists_timeout_seconds: 548 if debug: 549 dprint(f"Returning cached `exists` for {self} ({round(delta, 2)} seconds old).") 550 return _exists 551 552 with Venv(get_connector_plugin(self.instance_connector)): 553 _exists = self.instance_connector.pipe_exists(pipe=self, debug=debug) 554 555 self.__dict__['_exists'] = _exists 556 self.__dict__['_exists_timestamp'] = now 557 return _exists
See if a Pipe's table exists.
Parameters
- debug (bool, default False): Verbosity toggle.
Returns
- A
bool
corresponding to whether a pipe's underlying table exists.
560def filter_existing( 561 self, 562 df: 'pd.DataFrame', 563 safe_copy: bool = True, 564 date_bound_only: bool = False, 565 include_unchanged_columns: bool = False, 566 chunksize: Optional[int] = -1, 567 debug: bool = False, 568 **kw 569) -> Tuple['pd.DataFrame', 'pd.DataFrame', 'pd.DataFrame']: 570 """ 571 Inspect a dataframe and filter out rows which already exist in the pipe. 572 573 Parameters 574 ---------- 575 df: 'pd.DataFrame' 576 The dataframe to inspect and filter. 577 578 safe_copy: bool, default True 579 If `True`, create a copy before comparing and modifying the dataframes. 580 Setting to `False` may mutate the DataFrames. 581 See `meerschaum.utils.dataframe.filter_unseen_df`. 582 583 date_bound_only: bool, default False 584 If `True`, only use the datetime index to fetch the sample dataframe. 585 586 include_unchanged_columns: bool, default False 587 If `True`, include the backtrack columns which haven't changed in the update dataframe. 588 This is useful if you can't update individual keys. 589 590 chunksize: Optional[int], default -1 591 The `chunksize` used when fetching existing data. 592 593 debug: bool, default False 594 Verbosity toggle. 595 596 Returns 597 ------- 598 A tuple of three pandas DataFrames: unseen, update, and delta. 599 """ 600 from meerschaum.utils.warnings import warn 601 from meerschaum.utils.debug import dprint 602 from meerschaum.utils.packages import attempt_import, import_pandas 603 from meerschaum.utils.misc import round_time 604 from meerschaum.utils.dataframe import ( 605 filter_unseen_df, 606 add_missing_cols_to_df, 607 get_unhashable_cols, 608 get_numeric_cols, 609 ) 610 from meerschaum.utils.dtypes import ( 611 to_pandas_dtype, 612 none_if_null, 613 ) 614 from meerschaum.config import get_config 615 pd = import_pandas() 616 pandas = attempt_import('pandas') 617 if 'dataframe' not in str(type(df)).lower(): 618 df = self.enforce_dtypes(df, chunksize=chunksize, debug=debug) 619 is_dask = 'dask' in df.__module__ 620 if is_dask: 621 dd = attempt_import('dask.dataframe') 622 merge = dd.merge 623 NA = pandas.NA 624 else: 625 merge = pd.merge 626 NA = pd.NA 627 628 def get_empty_df(): 629 empty_df = pd.DataFrame([]) 630 dtypes = dict(df.dtypes) if df is not None else {} 631 dtypes.update(self.dtypes) 632 pd_dtypes = { 633 col: to_pandas_dtype(str(typ)) 634 for col, typ in dtypes.items() 635 } 636 return add_missing_cols_to_df(empty_df, pd_dtypes) 637 638 if df is None: 639 empty_df = get_empty_df() 640 return empty_df, empty_df, empty_df 641 642 if (df.empty if not is_dask else len(df) == 0): 643 return df, df, df 644 645 ### begin is the oldest data in the new dataframe 646 begin, end = None, None 647 dt_col = self.columns.get('datetime', None) 648 dt_type = self.dtypes.get(dt_col, 'datetime64[ns]') if dt_col else None 649 try: 650 min_dt_val = df[dt_col].min(skipna=True) if dt_col else None 651 if is_dask and min_dt_val is not None: 652 min_dt_val = min_dt_val.compute() 653 min_dt = ( 654 pandas.to_datetime(min_dt_val).to_pydatetime() 655 if min_dt_val is not None and 'datetime' in str(dt_type) 656 else min_dt_val 657 ) 658 except Exception: 659 min_dt = None 660 if not ('datetime' in str(type(min_dt))) or str(min_dt) == 'NaT': 661 if 'int' not in str(type(min_dt)).lower(): 662 min_dt = None 663 664 if isinstance(min_dt, datetime): 665 begin = ( 666 round_time( 667 min_dt, 668 to='down' 669 ) - timedelta(minutes=1) 670 ) 671 elif dt_type and 'int' in dt_type.lower(): 672 begin = min_dt 673 elif dt_col is None: 674 begin = None 675 676 ### end is the newest data in the new dataframe 677 try: 678 max_dt_val = df[dt_col].max(skipna=True) if dt_col else None 679 if is_dask and max_dt_val is not None: 680 max_dt_val = max_dt_val.compute() 681 max_dt = ( 682 pandas.to_datetime(max_dt_val).to_pydatetime() 683 if max_dt_val is not None and 'datetime' in str(dt_type) 684 else max_dt_val 685 ) 686 except Exception: 687 import traceback 688 traceback.print_exc() 689 max_dt = None 690 691 if ('datetime' not in str(type(max_dt))) or str(min_dt) == 'NaT': 692 if 'int' not in str(type(max_dt)).lower(): 693 max_dt = None 694 695 if isinstance(max_dt, datetime): 696 end = ( 697 round_time( 698 max_dt, 699 to='down' 700 ) + timedelta(minutes=1) 701 ) 702 elif dt_type and 'int' in dt_type.lower(): 703 end = max_dt + 1 704 705 if max_dt is not None and min_dt is not None and min_dt > max_dt: 706 warn("Detected minimum datetime greater than maximum datetime.") 707 708 if begin is not None and end is not None and begin > end: 709 if isinstance(begin, datetime): 710 begin = end - timedelta(minutes=1) 711 ### We might be using integers for the datetime axis. 712 else: 713 begin = end - 1 714 715 unique_index_vals = { 716 col: df[col].unique() 717 for col in self.columns 718 if col in df.columns and col != dt_col 719 } if not date_bound_only else {} 720 filter_params_index_limit = get_config('pipes', 'sync', 'filter_params_index_limit') 721 _ = kw.pop('params', None) 722 params = { 723 col: [ 724 none_if_null(val) 725 for val in unique_vals 726 ] 727 for col, unique_vals in unique_index_vals.items() 728 if len(unique_vals) <= filter_params_index_limit 729 } if not date_bound_only else {} 730 731 if debug: 732 dprint(f"Looking at data between '{begin}' and '{end}':", **kw) 733 734 backtrack_df = self.get_data( 735 begin=begin, 736 end=end, 737 chunksize=chunksize, 738 params=params, 739 debug=debug, 740 **kw 741 ) 742 if backtrack_df is None: 743 if debug: 744 dprint(f"No backtrack data was found for {self}.") 745 return df, get_empty_df(), df 746 747 if debug: 748 dprint(f"Existing data for {self}:\n" + str(backtrack_df), **kw) 749 dprint(f"Existing dtypes for {self}:\n" + str(backtrack_df.dtypes)) 750 751 ### Separate new rows from changed ones. 752 on_cols = [ 753 col for col_key, col in self.columns.items() 754 if ( 755 col 756 and 757 col_key != 'value' 758 and col in backtrack_df.columns 759 ) 760 ] 761 self_dtypes = self.dtypes 762 on_cols_dtypes = { 763 col: to_pandas_dtype(typ) 764 for col, typ in self_dtypes.items() 765 if col in on_cols 766 } 767 768 ### Detect changes between the old target and new source dataframes. 769 delta_df = add_missing_cols_to_df( 770 filter_unseen_df( 771 backtrack_df, 772 df, 773 dtypes={ 774 col: to_pandas_dtype(typ) 775 for col, typ in self_dtypes.items() 776 }, 777 safe_copy=safe_copy, 778 debug=debug 779 ), 780 on_cols_dtypes, 781 ) 782 783 ### Cast dicts or lists to strings so we can merge. 784 serializer = functools.partial(json.dumps, sort_keys=True, separators=(',', ':'), default=str) 785 786 def deserializer(x): 787 return json.loads(x) if isinstance(x, str) else x 788 789 unhashable_delta_cols = get_unhashable_cols(delta_df) 790 unhashable_backtrack_cols = get_unhashable_cols(backtrack_df) 791 for col in unhashable_delta_cols: 792 delta_df[col] = delta_df[col].apply(serializer) 793 for col in unhashable_backtrack_cols: 794 backtrack_df[col] = backtrack_df[col].apply(serializer) 795 casted_cols = set(unhashable_delta_cols + unhashable_backtrack_cols) 796 797 joined_df = merge( 798 delta_df.infer_objects(copy=False).fillna(NA), 799 backtrack_df.infer_objects(copy=False).fillna(NA), 800 how='left', 801 on=on_cols, 802 indicator=True, 803 suffixes=('', '_old'), 804 ) if on_cols else delta_df 805 for col in casted_cols: 806 if col in joined_df.columns: 807 joined_df[col] = joined_df[col].apply(deserializer) 808 if col in delta_df.columns: 809 delta_df[col] = delta_df[col].apply(deserializer) 810 811 ### Determine which rows are completely new. 812 new_rows_mask = (joined_df['_merge'] == 'left_only') if on_cols else None 813 cols = list(delta_df.columns) 814 815 unseen_df = ( 816 joined_df 817 .where(new_rows_mask) 818 .dropna(how='all')[cols] 819 .reset_index(drop=True) 820 ) if on_cols else delta_df 821 822 ### Rows that have already been inserted but values have changed. 823 update_df = ( 824 joined_df 825 .where(~new_rows_mask) 826 .dropna(how='all')[cols] 827 .reset_index(drop=True) 828 ) if on_cols else get_empty_df() 829 830 if include_unchanged_columns and on_cols: 831 unchanged_backtrack_cols = [ 832 col 833 for col in backtrack_df.columns 834 if col in on_cols or col not in update_df.columns 835 ] 836 update_df = merge( 837 backtrack_df[unchanged_backtrack_cols], 838 update_df, 839 how='inner', 840 on=on_cols, 841 ) 842 843 return unseen_df, update_df, delta_df
Inspect a dataframe and filter out rows which already exist in the pipe.
Parameters
- df ('pd.DataFrame'): The dataframe to inspect and filter.
- safe_copy (bool, default True):
If
True
, create a copy before comparing and modifying the dataframes. Setting toFalse
may mutate the DataFrames. Seemeerschaum.utils.dataframe.filter_unseen_df
. - date_bound_only (bool, default False):
If
True
, only use the datetime index to fetch the sample dataframe. - include_unchanged_columns (bool, default False):
If
True
, include the backtrack columns which haven't changed in the update dataframe. This is useful if you can't update individual keys. - chunksize (Optional[int], default -1):
The
chunksize
used when fetching existing data. - debug (bool, default False): Verbosity toggle.
Returns
- A tuple of three pandas DataFrames (unseen, update, and delta.):
868def get_num_workers(self, workers: Optional[int] = None) -> int: 869 """ 870 Get the number of workers to use for concurrent syncs. 871 872 Parameters 873 ---------- 874 The number of workers passed via `--workers`. 875 876 Returns 877 ------- 878 The number of workers, capped for safety. 879 """ 880 is_thread_safe = getattr(self.instance_connector, 'IS_THREAD_SAFE', False) 881 if not is_thread_safe: 882 return 1 883 884 engine_pool_size = ( 885 self.instance_connector.engine.pool.size() 886 if self.instance_connector.type == 'sql' 887 else None 888 ) 889 current_num_threads = threading.active_count() 890 current_num_connections = ( 891 self.instance_connector.engine.pool.checkedout() 892 if engine_pool_size is not None 893 else current_num_threads 894 ) 895 desired_workers = ( 896 min(workers or engine_pool_size, engine_pool_size) 897 if engine_pool_size is not None 898 else workers 899 ) 900 if desired_workers is None: 901 desired_workers = (multiprocessing.cpu_count() if is_thread_safe else 1) 902 903 return max( 904 (desired_workers - current_num_connections), 905 1, 906 )
Get the number of workers to use for concurrent syncs.
Parameters
- The number of workers passed via
--workers
.
Returns
- The number of workers, capped for safety.
15def verify( 16 self, 17 begin: Union[datetime, int, None] = None, 18 end: Union[datetime, int, None] = None, 19 params: Optional[Dict[str, Any]] = None, 20 chunk_interval: Union[timedelta, int, None] = None, 21 bounded: Optional[bool] = None, 22 deduplicate: bool = False, 23 workers: Optional[int] = None, 24 debug: bool = False, 25 **kwargs: Any 26) -> SuccessTuple: 27 """ 28 Verify the contents of the pipe by resyncing its interval. 29 30 Parameters 31 ---------- 32 begin: Union[datetime, int, None], default None 33 If specified, only verify rows greater than or equal to this value. 34 35 end: Union[datetime, int, None], default None 36 If specified, only verify rows less than this value. 37 38 chunk_interval: Union[timedelta, int, None], default None 39 If provided, use this as the size of the chunk boundaries. 40 Default to the value set in `pipe.parameters['chunk_minutes']` (1440). 41 42 bounded: Optional[bool], default None 43 If `True`, do not verify older than the oldest sync time or newer than the newest. 44 If `False`, verify unbounded syncs outside of the new and old sync times. 45 The default behavior (`None`) is to bound only if a bound interval is set 46 (e.g. `pipe.parameters['verify']['bound_days']`). 47 48 deduplicate: bool, default False 49 If `True`, deduplicate the pipe's table after the verification syncs. 50 51 workers: Optional[int], default None 52 If provided, limit the verification to this many threads. 53 Use a value of `1` to sync chunks in series. 54