Metadata-Version: 2.1
Name: PygQuery
Version: 0.0.5
Summary: 🐷 Multitread your data with Google BigQuery
Home-page: https://github.com/mlabarrere/PygQuery
Author: M_Lbr
Author-email: m.micky.lbr@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: English
Description-Content-Type: text/markdown
Requires-Dist: google-cloud-bigquery-storage
Requires-Dist: pandas
Requires-Dist: google-cloud-bigquery
Requires-Dist: google-api-python-client
Requires-Dist: google-auth-httplib2
Requires-Dist: google-auth-oauthlib
Requires-Dist: fastavro
Requires-Dist: pyarrow

# 🐷 PygQuery

Multi-treaded wrapper to read and write Pandas dataframes with Google BigQuery without the hassle of the heavy BigQuery API.

PygQuery is multi-treaded by design, meaning that any SQL request is a thread of its own. The advantage of it is that you can send multiple requests in parallel, and have awaiting inbound data ready for later.

### Install
On CLI, just type: 
```shell
pip install pygquery
```

### Read Data

Let's import the module first
```python
from pygquery.bigquery import BigQueryReader
```

The module takes 3 arguments as an input:
1. `request` : A string of your query. E.g. `"""SELECT * FROM myproject.dataset.table"""`
2. `project` : The string of the project you are currently gathering data from
3. `api_key_path` : a path of the G Service Account key, you can create one in the IAM tab of your GCP interface

Let's instantiate our data reader:
```python
reader_dict = {
  'request' : """SELECT * FROM myproject.dataset.table""",
  'project' : 'myproject',
  'api_key_path' : 'folder/key.json'
}

# If there any error in your query at the instantiation stage, BigQuery will let you know
my_request = BigQueryReader(**reader_dict) 
```
Now you have an object ready to be launched. If the line of code above executes, you know that:
1. There is no error in the SQL
2. There is no credentials failure


Let's fire up this object:

```python

my_request.start() # Launch the thread for downloading data

"# ... Do other things while data is downloading, like launching another request ... #"

my_request.join() # Tell to Python to wait for your download to complete

my_data = myRequest.data # Get your data
```

Et voilà! You have your data in Pandas `DataFrame` format ready to be crunched.
```python
my_data.info()
my_data.head()

```


