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param ( | |
[string]$file = $(throw "-file is required"), | |
[string]$ftphostpath = $(throw "-ftphostpath is required"), | |
[string]$username = $(throw "-username is required"), | |
[string]$password = $(throw "-password is required") | |
) | |
$f = dir $file | |
$req = [System.Net.FtpWebRequest]::Create("ftp://$ftphostpath/" + $f.Name); | |
$req.Credentials = New-Object System.Net.NetworkCredential($username, $password); |
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[Reflection.Assembly]::LoadWithPartialName('System.IO.Compression.FileSystem'); | |
[System.IO.Compression.ZipFile]::CreateFromDirectory($directoryTozip, "$output.zip"); |
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package com.fearlesstg.dataflow.pipelines; | |
import java.util.*; | |
import com.fasterxml.jackson.databind.ObjectMapper; | |
import com.fasterxml.jackson.databind.SerializationFeature; | |
import com.google.api.services.bigquery.model.TableRow; | |
import org.apache.beam.sdk.coders.StringUtf8Coder; | |
import org.apache.beam.sdk.io.Compression; | |
import org.apache.beam.sdk.io.FileIO; |
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package com.fearlesstg; | |
import com.google.api.client.googleapis.auth.oauth2.GoogleCredential; | |
import com.google.api.client.http.HttpTransport; | |
import com.google.api.client.http.javanet.NetHttpTransport; | |
import com.google.api.client.json.JsonFactory; | |
import com.google.api.client.json.jackson.JacksonFactory; | |
import com.google.api.services.bigquery.Bigquery; | |
import com.google.api.services.bigquery.BigqueryScopes; | |
import com.google.api.services.bigquery.model.*; |
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package com.fearlesstg; | |
import com.google.api.services.bigquery.model.TableFieldSchema; | |
import com.google.api.services.bigquery.model.TableRow; | |
import com.google.api.services.bigquery.model.TableSchema; | |
import com.google.api.services.bigquery.model.TimePartitioning; | |
import org.apache.beam.sdk.Pipeline; | |
import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO; | |
import org.apache.beam.sdk.io.gcp.bigquery.TableDestination; | |
import org.apache.beam.sdk.options.PipelineOptions; |
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import com.google.api.services.bigquery.model.TableRow; | |
import com.google.api.services.bigquery.model.TimePartitioning; | |
import org.apache.beam.sdk.io.gcp.bigquery.TableDestination; | |
import org.apache.beam.sdk.transforms.SerializableFunction; | |
import org.apache.beam.sdk.values.ValueInSingleWindow; | |
import org.slf4j.Logger; | |
import org.slf4j.LoggerFactory; | |
//From: https://shinesolutions.com/2017/12/05/fun-with-serializable-functions-and-dynamic-destinations-in-cloud-dataflow/ | |
public class GetTableShardPartition implements SerializableFunction<ValueInSingleWindow<TableRow>, TableDestination> { |
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from google.cloud import storage | |
import sys | |
from avro.datafile import DataFileReader | |
from avro.io import DatumReader | |
import json | |
client = storage.Client() | |
bucket_name = sys.argv[1] | |
blob_name = sys.argv[2] |
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from google.cloud import storage | |
from airflow.hooks.base_hook import BaseHook | |
from airflow.utils.log.logging_mixin import LoggingMixin | |
import random | |
import string | |
class GCSCustomHook(BaseHook, LoggingMixin): | |
def __init__(self, storage_conn_id='google_cloud_storage_default'): |
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terraform plan | |
2020/01/03 14:33:49 [WARN] Log levels other than TRACE are currently unreliable, and are supported only for backward compatibility. | |
Use TF_LOG=TRACE to see Terraform's internal logs. | |
---- | |
2020/01/03 14:33:49 [INFO] Terraform version: 0.12.18 | |
2020/01/03 14:33:49 [INFO] Go runtime version: go1.12.13 | |
2020/01/03 14:33:49 [INFO] CLI args: []string{"/usr/local/bin/terraform", "plan"} | |
2020/01/03 14:33:49 [DEBUG] Attempting to open CLI config file: /Users/peter/.terraformrc | |
2020/01/03 14:33:49 [DEBUG] File doesn't exist, but doesn't need to. Ignoring. | |
2020/01/03 14:33:49 [INFO] CLI command args: []string{"plan"} |
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import pandas as pd | |
import pandas_ta as ta | |
from dateutil import parser | |
df = pd.read_csv('AUD_CAD.csv', sep=',', names=[ | |
'datetime', 'bid_open', 'bid_high', 'bid_low', 'bid_close', 'ask_open', 'ask_high', 'ask_low', 'ask_close', 'mid_open', 'mid_high', 'mid_low', 'mid_close', 'volume'], error_bad_lines=False, parse_dates=['datetime']) | |
df.ta.atr(append=True, high='bid_high', low='bid_low', close='bid_close') | |
print(df) |
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