datastore | Bloat free and flexible interface | Database library
kandi X-RAY | datastore Summary
kandi X-RAY | datastore Summary
:hamster: Bloat free and flexible interface for data store and database access.
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Top functions reviewed by kandi - BETA
- Mixin emitter properties .
- Register listener .
- Emitter constructor .
- creates datastore object
- Find a module .
- Emit event
datastore Key Features
datastore Examples and Code Snippets
License : Strong Copyleft (CC BY-SA 4.0)
Copy$ amplify update api
? Please select from one of the below mentioned services: GraphQL
? Select from the options below: Disable DataStore for entire API
.task{
await networkController.configureAmplify()
}
init(){
Task(priority: .medium){
await networkController.configureAmplify()
}
}
@main
struct YourApp: App {
@Stat(async () => {})()
const getDbClient = async () => {
try {
await mongoose.connect(mongoDbUrl, mongoDbOptions);
debug(`Connected to ${chalk.green('MongoDB')}`);
const db = mongoose.connection;
const express = require('express');
const app = express();
const Datastore = require('nedb');
app.listen(3000, () => console.log('listening at 3000'));
app.use(express.json({
limit: '1mb'
}));
const database = new Datastore('public/// Imports the Google Cloud client library
const {Datastore} = require('@google-cloud/datastore');
// Creates a client
const datastore = new Datastore();
async function quickstart() {
// The kind for the new entvar date = "2002-09-13";
var limit = "10";
exports.checkRecords = async (req, res) => {
const { Datastore } = require("@google-cloud/datastore");
const datastore = new Datastore();
const taskKey = datastore.key(["Dog", "Frega.FileList textFileList = await drive.files.list(q: "'root' in parents");
ga.Media response = await drive.files.get(filedId, downloadOptions: ga.DownloadOptions.FullMedia);
List dataStore from flask import Flask, render_template, redirect, request
from google.cloud import datastore
from markupsafe import escape
# Starting Datastore Client.
client = datastore.Client()
# Home page will do a redirect to the specified URL.
@a/opt/ripple/bin/rippled --net --silent --conf /etc/opt/ripple/rippled.cfg
[server]
port_rpc_admin_local
port_peer
port_ws_admin_local
#port_ws_public
#ssl_key = /etc/ssl/private/server.key
#ssl_cert = /etc/ssl/certconst appData = (() => {
const dataStore = {};
const fetchJSON = async (url) => {
try {
let response = await fetch(url);
return await response.json();
} catch (error) {
console.log(errCommunity Discussions
Trending Discussions on datastore
QUESTION
We are installing Anthos on VMWare platform and now we have an error in the Admin Cluster deployment procedure of the Seesaw Loadbalancer in HA.
The Deploy of two Seesaw VMs has been created with success, but when checking the health check we get the following error 403:
...ANSWER
Answered 2021-Jul-29 at 12:43Solved after the recreation of the admin workstation with the following parameter.
QUESTION
when I run android application in real device I am getting following gradle errors
...ANSWER
Answered 2021-Aug-21 at 12:15I fixed it my problem by updating current kotlin version to latest version and moshi version to 1.12.0
QUESTION
I'm writing a jetpack compose android app, I need to store some settings permanently.
I decided to use androidx.datastore:datastore-preferences:1.0.0 library, I have added this to my classpath.
According to the https://developer.android.com/topic/libraries/architecture/datastore descripton I have added this line of code to my kotline file at the top level:
val Context.prefsDataStore: DataStore by preferencesDataStore(name = "settings")
But I get a compile error:
...ANSWER
Answered 2022-Jan-13 at 09:20I got this error because of an incorrect import:
QUESTION
With the upgrade to Google Cloud SDK 360.0.0-0 i started seeing the following error when running the dev_appserver.py command for my Python 2.7 App Engine project.
ANSWER
Answered 2022-Feb-08 at 08:52This issue seems to have been resolved with Google Cloud SDK version 371
On my debian based system i fixed it by downgrading the app-engine-python component to the previous version
QUESTION
I have a dataframe of price data that looks like the following: (with more than 10,000 columns)
Unamed: 0 01973JAC3 corp Unamed: 2 019754AA8 corp Unamed: 4 01265RTJ7 corp Unamed: 6 01988PAD0 corp Unamed: 8 019736AB3 corp 1 2004-04-13 101.1 2008-06-16 99.1 2010-06-14 110.0 2008-06-18 102.1 NaT NaN 2 2004-04-14 101.2 2008-06-17 100.4 2010-07-05 110.3 2008-06-19 102.6 NaT NaN 3 2004-04-15 101.6 2008-06-18 100.4 2010-07-12 109.6 2008-06-20 102.5 NaT NaN 4 2004-04-16 102.8 2008-06-19 100.9 2010-07-19 110.1 2008-06-21 102.6 NaT NaN 5 2004-04-19 103.0 2008-06-20 101.3 2010-08-16 110.3 2008-06-22 102.8 NaT NaN ... ... ... ... ... ... ... ... ... NaT NaN 3431 NaT NaN 2021-12-30 119.2 NaT NaN NaT NaN NaT NaN 3432 NaT NaN 2021-12-31 119.4 NaT NaN NaT NaN NaT NaN(Those are 9-digit CUSIPs in the header. So every two columns represent date and closed price for a security.) I would like to
- find and get rid of empty pairs of date and price like "Unamed: 8" and"019736AB3 corp"
- then rearrange the dateframe to a panel of monthly close price as following:
Edit: I wanna clarify my question.
So my dataframe has more than 10,000 columns, which makes it impossible to just drop by column names or change their names one by one. The pairs of date and price start and end at different time and are of different length (, and of different frequency). I m looking for an efficient way to arrange therm into a less messy form. Thanks.
Here is a sample of 30 columns. https://github.com/txd2x/datastore file name: sample-question2022-01.xlsx
I figured out: stacking and then reshaping.Thx for the help.
...ANSWER
Answered 2022-Jan-03 at 10:33if you want to get rid of unusful columns then perform the following code:
df.drop("name_of_column", axis=1, inplace=True)
if you want to drop empty rows use:
df.drop(df.index[row_number], inplace=True)
if you want to rearrange the data using 'timestamp and date' you need to convert it to a datetime object and then make it as index:
QUESTION
**I am using AWS Appsync, AWS datastore, Aws Cognito, Aws API. When I am trying to save data on AWS Datastore it gives me this error "DataStoreError: The operation couldn’t be completed. (SQLite.Result error 0.)."
...ANSWER
Answered 2021-Dec-30 at 11:16After spending 8 - 9 days found this. Target < Project Name < Build Settings < Reflection Metadata level. Make sure you select "All" in this.
This setting controls the level of reflection metadata the Swift compiler emits.
All: Type information about stored properties of Swift structs and classes, Swift enum cases, and their names, are emitted into the binary for reflection and analysis in the Memory Graph Debugger.
Without Names: Only type information about stored properties and cases are emitted into the binary, with their names omitted. -disable-reflection-names
None: No reflection metadata is emitted into the binary. Accuracy of detecting memory issues involving Swift types in the Memory Graph Debugger will be degraded and reflection in Swift code may not be able to discover children of types, such as properties and enum cases. -disable-reflection-metadata.
In my case that was in None. Please make sure you select "All".
QUESTION
I am producing from VMware datastores collection a list of volumes and their associated tags
I formated them in a JSON type output to be able to feed another system later. The output is working but for the tags section I would like to keep only the name and category_name not the other properties.
This is my playbook :
...ANSWER
Answered 2021-Dec-14 at 18:03Select the attributes from the tag lists, e.g.
QUESTION
I'm writing some code for a class project that sends jobs to a dataproc cluster in GCP. I recently ran into an odd error and I'm having trouble wrapping my head around it. The error is as follows:
...ANSWER
Answered 2021-Dec-01 at 19:46Using mvn dependency:tree you can discover there's a mix of grpc-java 1.41.0 and 1.42.1 versions in your dependency tree. google-cloud-datastore:2.2.0 brings in grpc-api:1.42.1 but the other dependencies bring in grpc version 1.40.1.
grpc-java recommends always using requireUpperBoundDeps from maven-enforcer to catch Maven silently downgrading dependencies.
QUESTION
I am trying to create a dataproc cluster that will connect dataproc to pubsub. I need to add multiple jars on cluster creation in the spark.jars flag
...ANSWER
Answered 2021-Nov-27 at 22:40The answer you linked is the correct way to do it: How can I include additional jars when starting a Google DataProc cluster to use with Jupyter notebooks?
If you also post the command you tried with the escaping syntax and the resulting error message then others could more easily verify what you did wrong. It looks like you're specifying an additional spark property in addition to your list of jars spark:spark.driver.memory=3000m, and tried to just space-separate that from your jars flag, which isn't allowed.
Per the linked result, you'd need to use the newly assigned separator character to separate the second spark property:
QUESTION
I have spent the whole weekend trying to debug this piece of code. I have a Spring RestController :
...ANSWER
Answered 2021-Nov-01 at 10:57If you look at your last screenshot you see a message indicating that there is an id field that has no value.
In your entity you have the following declaration of your id field:
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