### Install elasticsearch-dbapi via pip

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Provides commands to install the `elasticsearch-dbapi` library using pip. It includes the base installation and an optional installation for AWS Elasticsearch Service / Open Distro support.

```bash
$ pip install elasticsearch-dbapi
```

```bash
$ pip install elasticsearch-dbapi[opendistro]
```

--------------------------------

### Run Unit Tests for elasticsearch-dbapi

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Provides the necessary commands to set up and execute the unit tests for the `elasticsearch-dbapi` project. It involves starting Elasticsearch and Kibana using Docker Compose and then running tests with `nosetests`.

```bash
$ docker-compose up -d
```

```bash
$ nosetests -v
```

--------------------------------

### Perform Aggregation Queries with SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Demonstrates using SQLAlchemy's declarative capabilities to interact with Elasticsearch. It shows how to define a table, use SQLAlchemy's `func.count` for aggregation, and execute the query to get a scalar result.

```python
from sqlalchemy import func, select
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import MetaData, Table


engine = create_engine("elasticsearch+http://localhost:9200/")
logs = Table("flights", MetaData(bind=engine), autoload=True)
count = select([func.count("*")], from_obj=logs).scalar()
print(f"COUNT: {count}")
```

--------------------------------

### Connect and Query Elasticsearch using DBAPI

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Demonstrates how to establish a connection to Elasticsearch using the DBAPI interface provided by `elasticsearch-dbapi`. It shows how to create a cursor, execute a SQL query, and iterate over the fetched results.

```python
from es.elastic.api import connect

conn = connect(host='localhost')
curs = conn.cursor()
curs.execute(
    "select * from flights LIMIT 10"
)
print([row for row in curs])
```

--------------------------------

### Configure Basic Authentication for Opendistro with SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Illustrates setting up basic username/password authentication for an Opendistro Elasticsearch connection using SQLAlchemy's `create_engine` by embedding credentials directly in the URI.

```Python
from sqlalchemy.engine import create_engine

engine = create_engine(
    "odelasticsearch+https://my_user:my_password@search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/"
)
```

--------------------------------

### Build and Upload Python Package to PyPI

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/RELEASING.md

These commands are used to build the Python package distributions (source distribution and wheel) and then upload the generated files to the Python Package Index (PyPI) using the `twine` utility. This is a standard step in the release process for Python libraries.

```bash
python setup.py sdist bdist_wheel
twine upload dist/*
```

--------------------------------

### Enable Opendistro SQL v2 Engine

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Shows how to enable the new Opendistro SQL v2 engine by appending `v2=true` as a query parameter to the connection URI, which brings improvements and fixes.

```URI
odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_profile=us-west-2&v2=true
```

--------------------------------

### Query Elasticsearch using SQLAlchemy Engine Execute

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Illustrates how to connect to Elasticsearch using SQLAlchemy's `create_engine` with the `elasticsearch+http` dialect. It shows how to obtain a connection from the engine and execute a raw SQL query directly.

```python
from sqlalchemy.engine import create_engine

engine = create_engine("elasticsearch+http://localhost:9200/")
rows = engine.connect().execute(
    "select * from flights LIMIT 10"
)
print([row for row in rows])
```

--------------------------------

### Connect to Docker Compose Opendistro Instance

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Provides the connection URI for connecting to an Opendistro Elasticsearch instance running via `docker-compose`, including basic authentication and disabling certificate verification.

```URI
odelasticsearch+https://admin:admin@localhost:9400/?verify_certs=False
```

--------------------------------

### Connect to AWS ES Opendistro via DBAPI

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Shows how to connect to an AWS Elasticsearch Opendistro endpoint using the `es.opendistro.api.connect` DBAPI and execute a SQL query to fetch a limited number of rows.

```Python
from es.opendistro.api import connect

conn = connect(host='localhost',port=9200,path="", scheme="http")

curs = conn.cursor().execute(
    "select * from flights LIMIT 10"
)

print([row for row in curs])
```

--------------------------------

### Configure Elasticsearch Connection Parameters via URL

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Explains how to pass additional connection parameters, such as `http_compress` and `timeout`, to the underlying `elasticsearch-py` library by appending them as query parameters to the SQLAlchemy connection string URL.

```bash
elasticsearch+http://localhost:9200/?http_compress=True&timeout=100
```

--------------------------------

### Connect to AWS ES Opendistro via SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Demonstrates connecting to an AWS Elasticsearch Opendistro endpoint using SQLAlchemy's `odelasticsearch` driver and executing a SQL query to retrieve data.

```Python
from sqlalchemy.engine import create_engine

engine = create_engine(
    "odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/"
)
rows = engine.connect().execute(
    "select count(*), Carrier from flights GROUP BY Carrier"
)
print([row for row in rows])
```

--------------------------------

### Reflect Elasticsearch Schema using SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Shows how to use SQLAlchemy's reflection features to inspect the schema of an Elasticsearch instance. It demonstrates listing available table names and reflecting metadata to access column details for a specific table.

```python
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import Table, MetaData

engine = create_engine("elasticsearch+http://localhost:9200/")
logs = Table("flights", MetaData(bind=engine), autoload=True)
print(engine.table_names())

metadata = MetaData()
metadata.reflect(bind=engine)
print([table for table in metadata.sorted_tables])
print(logs.columns)
```

--------------------------------

### Configure IAM AWS Profile Authentication for Opendistro with SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Demonstrates configuring IAM authentication using an AWS profile for Opendistro Elasticsearch connections in SQLAlchemy, by passing the `aws_profile` parameter in the connection URI.

```Python
from sqlalchemy.engine import create_engine

engine = create_engine(
    "odelasticsearch+https://search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_profile=us-west-2"
)
```

--------------------------------

### Configure IAM AWS Key Authentication for Opendistro with SQLAlchemy

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Explains how to use AWS access and secret keys for IAM authentication with Opendistro Elasticsearch via SQLAlchemy, specifying `aws_keys` and `aws_region` as query parameters in the connection URI.

```Python
from sqlalchemy.engine import create_engine

engine = create_engine(
    "odelasticsearch+https://<AWS_ACCESS_KEY>:<AWS_SECRET_KEY>@search-SOME-CLUSTER.us-west-2.es.amazonaws.com:443/?aws_keys=1&&aws_region=<AWS_REGION>"
)
```

--------------------------------

### Python Project Dependency List

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/requirements-dev.txt

This snippet lists all required Python packages and their pinned versions for the project. These dependencies are crucial for ensuring a consistent development, testing, and production environment, covering aspects like code formatting, linting, testing, and cloud integration.

```Python
black==22.3.0
coverage==6.3.2
flake8==4.0.1
flake8-commas==2.1.0
flake8-import-order==0.18.1
nose==1.3.7
pip-tools==3.6.0
pre-commit==1.17.0
twine==2.0.0
readme_renderer==24.0
mypy==0.790
requests-aws4auth==1.0.1
boto3==1.16.63
pytest==7.2.1
```

--------------------------------

### Set Fetch Size for Elasticsearch Queries

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Demonstrates how to configure the `fetch_size` parameter when establishing a connection using the DBAPI. This parameter controls the maximum number of rows retrieved by a single query, with a default limit of 10000.

```python
from es.elastic.api import connect

conn = connect(host="localhost", fetch_size=1000)
curs = conn.cursor()
```

--------------------------------

### Set Time Zone for Elasticsearch Queries

Source: https://github.com/preset-io/elasticsearch-dbapi/blob/master/README.md

Illustrates how to specify the `time_zone` parameter when connecting to Elasticsearch via the DBAPI. This allows overriding the default UTC time zone for queries, ensuring results are aligned with a specific geographic time zone.

```python
from es.elastic.api import connect

conn = connect(host="localhost", time_zone="Asia/Shanghai")
curs = conn.cursor()
```

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