Python relative imports in AWS Lambda fail with attempted relative import with no known parent package
In AWS Lambda if I attempt an explicit relative import like this
.
├── lambda_file.py
└── example.py
psql -U postgres | |
postgres=# SHOW config_file; |
# XGBClassifier | |
param_dist = {'objective': 'binary:logistic', 'n_estimators': 2} | |
clf = xgb.XGBClassifier(**params_dist) |
class pyspark.sql.DataFrame | |
people = spark.read.parquet("...") | |
department = spark.read.parquet("...") | |
people.filter(people.age > 30) \ | |
.join(department, people.deptId == department.id) \ | |
.groupBy(department.name, "gender") \ | |
.agg({"salary": "avg", "age": "max"}) |
# saves credentials | |
$ git config credential.helper store | |
$ git push http://example.com/repo.git | |
Username: <type your username> | |
Password: <type your password> |
#!/bin/bash | |
export PYTHON_VERSION=3.6.5 | |
export PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python/$PYTHON_VERSION/Python-$PYTHON_VERSION.tgz | |
sudo apt update | |
sudo apt install --no-install-recommends -y \ | |
software-properties-common build-essential \ | |
libssl-dev libreadline-dev libbz2-dev libsqlite3-dev zlib1g-dev \ | |
python-minimal |
com.sun.management:type=DiagnosticCommand | |
com.sun.management:type=HotSpotDiagnostic | |
java.lang:name=CodeCacheManager,type=MemoryManager | |
java.lang:name=Code Cache,type=MemoryPool | |
java.lang:name=Compressed Class Space,type=MemoryPool | |
java.lang:name=G1 Eden Space,type=MemoryPool | |
java.lang:name=G1 Old Generation,type=GarbageCollector | |
java.lang:name=G1 Old Gen,type=MemoryPool | |
java.lang:name=G1 Survivor Space,type=MemoryPool | |
java.lang:name=G1 Young Generation,type=GarbageCollector |
# BENCHMARK----------------------------------------------------- | |
#1. Rust kafka-benchmark (https://github.com/fede1024/kafka-benchmark) | |
# must create topic with 6 partitions first | |
bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 6--topic [scenario] | |
# replace scenario with one in file kafka-benchmark/config/base_producer.yaml |
#basic python code for working with POSGRESQL through psycopg2 | |
import psycopg2 | |
conn = psycopg2.connect(database="testdb", user="postgres", password="pass123", host="127.0.0.1", port="5432") | |
print("Opened database sucessfully") | |
cur = conn.cursor() |