Added pyproject.toml.

Author: toddbirchard

.gitignore

@@ -108,4 +108,5 @@ venv.bak/
 .idea
 
 # Credentials
-creds
+creds
+creds/*

README.md

@@ -1,9 +1,9 @@
 # Pandas SQLAlchemy Tutorial
 
 ![Python](https://img.shields.io/badge/Python-v^3.8-blue.svg?logo=python&longCache=true&logoColor=white&colorB=5e81ac&style=flat-square&colorA=4c566a)
-![Pandas](https://img.shields.io/badge/Pandas-v^1.0.0-blue.svg?logo=Google&longCache=true&logoColor=white&colorB=5e81ac&style=flat-square&colorA=4c566a)
-![SQLAlchemy](https://img.shields.io/badge/SQLAlchemy-^1.3.6-red.svg?longCache=true&style=flat-square&logo=scala&logoColor=white&colorA=4c566a&colorB=bf616a)
-![PyMySQL](https://img.shields.io/badge/Psycopg2--Binary-v2.7.7-red.svg?longCache=true&style=flat-square&logo=PostgreSQL&logoColor=white&colorA=4c566a&colorB=bf616a)
+![Pandas](https://img.shields.io/badge/Pandas-v^1.0.0-blue.svg?logo=python&longCache=true&logoColor=white&colorB=5e81ac&style=flat-square&colorA=4c566a)
+![SQLAlchemy](https://img.shields.io/badge/SQLAlchemy-^1.3.6-red.svg?longCache=true&style=flat-square&logo=python&logoColor=white&colorA=4c566a&colorB=bf616a)
+![PyMySQL](https://img.shields.io/badge/PyMySQL-v0.9.3-red.svg?longCache=true&style=flat-square&logo=mysql&logoColor=white&colorA=4c566a&colorB=bf616a)
 ![GitHub Last Commit](https://img.shields.io/github/last-commit/google/skia.svg?style=flat-square&colorA=4c566a&colorB=a3be8c)
 [![GitHub Issues](https://img.shields.io/github/issues/hackersandslackers/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorA=4c566a&colorB=ebcb8b)](https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial/issues)
 [![GitHub Stars](https://img.shields.io/github/stars/hackersandslackers/pandas-sqlalchemy-tutorial.svg?style=flat-square&colorB=ebcb8b&colorA=4c566a)](https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial/stargazers)
@@ -13,26 +13,37 @@
 
 Easily drop data into Pandas from a SQL database, or upload your DataFrames to a SQL table. Tutorial found here: https://hackersandslackers.com/connecting-pandas-to-a-sql-database-with-sqlalchemy/
 
-## Getting Started
 
-Installation is recommended with Pipenv:
+## Installation
+
+**Installation via `requirements.txt`**:
 
 ```shell
 $ git clone https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial.git
 $ cd pandas-sqlalchemy-tutorial
-$ pipenv shell
-$ pipenv update
+$ python3 -m venv myenv
+$ source myenv/bin/activate
+$ pip3 install -r requirements.txt
 $ python3 main.py
 ```
 
-Alternatively, try installing via `setup.py`:
+**Installation via [Pipenv](https://pipenv-fork.readthedocs.io/en/latest/)**:
 
 ```shell
 $ git clone https://github.com/hackersandslackers/pandas-sqlalchemy-tutorial.git
 $ cd pandas-sqlalchemy-tutorial
-$ python3 setup.py install
+$ pipenv shell
+$ pipenv update
 $ python3 main.py
 ```
------
 
-**Hackers and Slackers** tutorials are free of charge. If you found this tutorial helpful, a [small donation](https://www.buymeacoffee.com/hackersslackers) would be greatly appreciated to keep us in business. All proceeds go towards coffee, and all coffee goes towards more content.
+## Usage
+
+Replace the values in **.env.example** with your values and rename this file to **.env**:
+
+* `SQLALCHEMY_DATABASE_URI`:Connection URI of a SQL database.
+
+*Remember to never commit secrets saved in .env files to Github.*
+------------------
+
+**Hackers and Slackers** tutorials are free of charge. If you found this tutorial helpful, a [small donation](https://www.buymeacoffee.com/hackersslackers) would be greatly appreciated to keep us in business. All proceeds go towards coffee, and all coffee goes towards more content.

config.py

@@ -7,5 +7,5 @@
 
 
 SQLALCHEMY_DATABASE_URI = environ.get('SQLALCHEMY_DATABASE_URI')
-SQLALCHEMY_ENGINE_OPTIONS = {'ssl': {'ca': './creds/ca-certificate.crt'}}
-CSV_FILE = 'data/nyc-jobs.csv'
+SQLALCHEMY_ENGINE_OPTIONS = {'ssl': {'ca': './creds/ca-certificate.crt'}}  # Optional for SSL connections
+CSV_FILE = 'data/nyc_jobs.csv'

data/nyc-jobs.csv data/nyc_jobs.csvdata/nyc-jobs.csv renamed to data/nyc_jobs.csv

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "Pandas SQLAlchemy Tutorial"
 version = "0.1.0"
-description = "Easily drop data into Pandas from a SQL database or upload DataFrames to a SQL table."
+description = "Load or insert data into a SQL database using Pandas DataFrames."
 authors = ["Todd Birchard <toddbirchard@gmail.com>"]
 maintainers = ["Todd Birchard <toddbirchard@gmail.com>"]
 license = "MIT"

pyproject.toml

@@ -9,7 +9,8 @@
 
 
 def init_script():
+	"""Demonstrate Pandas' SQLAlchemy integration."""
 	jobs_df = load_csv_data(CSV_FILE)
 	db = Database(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_ENGINE_OPTIONS)
-	db.upload_dataframe_to_sql(jobs_df)
+	db.upload_dataframe_to_sql(jobs_df, 'nyc_jobs')
 	db.get_dataframe_from_sql('nyc_jobs')

tutorial/__init__.py

@@ -5,6 +5,7 @@
 
 
 class Database:
+    """Pandas database client."""
 
     def __init__(self, db_uri, db_args):
         self.engine = create_engine(
@@ -13,12 +14,12 @@ def __init__(self, db_uri, db_args):
             echo=True
         )
 
-    def upload_dataframe_to_sql(self, local_df):
+    def upload_dataframe_to_sql(self, csv_df, table_name):
         """Upload data to database with proper dtypes."""
-        local_df.to_sql(
-            "nyc_jobs",
+        csv_df.to_sql(
+            table_name,
             self.engine,
-            if_exists='append',
+            if_exists='replace',
             index=False,
             chunksize=500,
             dtype={
@@ -36,13 +37,15 @@ def upload_dataframe_to_sql(self, local_df):
                 "posting_updated": DateTime
             }
         )
+        print(f'Loaded {len(csv_df)} rows into {table_name} table.')
 
     def get_dataframe_from_sql(self, table_name):
         """Create DataFrame form SQL table."""
-        sql_DF = pd.read_sql_table(
+        table_df = pd.read_sql_table(
             table_name,
-            con=self.engine,
-            parse_dates=['posting_date', 'posting_updated']
+            con=self.engine
         )
-        return sql_DF
+        print(f'Loaded {len(table_df)} rows from {table_name}.')
+        print(table_df.info())
+        return table_df
 

tutorial/database.py

@@ -3,8 +3,6 @@
 
 
 def load_csv_data(csv):
-    """Create DataFrame and clean column names."""
+    """Create DataFrame from local CSV."""
     jobs_df = pd.read_csv(csv)
-    new_columns = [column.replace(' ', '_').lower() for column in jobs_df]
-    jobs_df.columns = new_columns
     return jobs_df