hiplab/data-transport
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data-transport
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Merge pull request #13 from lnyemba/v2.0.4 

documentation added (notebooks)
This commit is contained in:
Steve L. Nyemba 2024-06-10 01:29:10 -05:00 committed by GitHub
parent a4481865ea d0472ccee5
commit 76484f0130
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6 changed files with 107 additions and 145 deletions
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45
notebooks/bigquery.ipynb
View File

@ -15,21 +15,21 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stderr", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"100%|██████████| 1/1 [00:00<00:00, 5440.08it/s]\n" "100%|██████████| 1/1 [00:00<00:00, 10106.76it/s]\n"
] ]
}, },
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"['data transport version ', '2.0.0']\n" "['data transport version ', '2.0.4']\n"
] ]
} }
], ],
@ -45,7 +45,7 @@
"PRIVATE_KEY = os.environ['BQ_KEY'] #-- location of the service key\n", "PRIVATE_KEY = os.environ['BQ_KEY'] #-- location of the service key\n",
"DATASET = 'demo'\n", "DATASET = 'demo'\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"bqw = transport.factory.instance(provider=providers.BIGQUERY,dataset=DATASET,table='friends',context='write',private_key=PRIVATE_KEY)\n", "bqw = transport.get.writer(provider=providers.BIGQUERY,dataset=DATASET,table='friends',private_key=PRIVATE_KEY)\n",
"bqw.write(_data,if_exists='replace') #-- default is append\n", "bqw.write(_data,if_exists='replace') #-- default is append\n",
"print (['data transport version ', transport.__version__])\n" "print (['data transport version ', transport.__version__])\n"
] ]
@ -63,7 +63,8 @@
"\n", "\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
@ -93,7 +94,7 @@
"from transport import providers\n", "from transport import providers\n",
"import os\n", "import os\n",
"PRIVATE_KEY=os.environ['BQ_KEY']\n", "PRIVATE_KEY=os.environ['BQ_KEY']\n",
"pgr = transport.instance(provider=providers.BIGQUERY,dataset='demo',table='friends',private_key=PRIVATE_KEY)\n", "pgr = transport.get.reader(provider=providers.BIGQUERY,dataset='demo',table='friends',private_key=PRIVATE_KEY)\n",
"_df = pgr.read()\n", "_df = pgr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from demo.friends'\n", "_query = 'SELECT COUNT(*) _counts, AVG(age) from demo.friends'\n",
"_sdf = pgr.read(sql=_query)\n", "_sdf = pgr.read(sql=_query)\n",
@ -106,35 +107,13 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'dataset': 'demo', 'table': 'friends'}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"{\n",
" \n",
" \"dataset\":\"demo\",\"table\":\"friends\"\n",
"}"
] ]
}, },
{ {

51
notebooks/mongodb.ipynb
View File

@ -11,14 +11,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"2.0.0\n" "2.0.4\n"
] ]
} }
], ],
@ -30,7 +30,7 @@
"from transport import providers\n", "from transport import providers\n",
"import pandas as pd\n", "import pandas as pd\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"mgw = transport.factory.instance(provider=providers.MONGODB,db='demo',collection='friends',context='write')\n", "mgw = transport.get.writer(provider=providers.MONGODB,db='demo',collection='friends')\n",
"mgw.write(_data)\n", "mgw.write(_data)\n",
"print (transport.__version__)" "print (transport.__version__)"
] ]
@ -48,12 +48,13 @@
"\n", "\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -73,7 +74,7 @@
"\n", "\n",
"import transport\n", "import transport\n",
"from transport import providers\n", "from transport import providers\n",
"mgr = transport.instance(provider=providers.MONGODB,db='foo',collection='friends')\n", "mgr = transport.get.reader(provider=providers.MONGODB,db='foo',collection='friends')\n",
"_df = mgr.read()\n", "_df = mgr.read()\n",
"PIPELINE = [{\"$group\":{\"_id\":0,\"_counts\":{\"$sum\":1}, \"_mean\":{\"$avg\":\"$age\"}}}]\n", "PIPELINE = [{\"$group\":{\"_id\":0,\"_counts\":{\"$sum\":1}, \"_mean\":{\"$avg\":\"$age\"}}}]\n",
"_sdf = mgr.read(aggregate='friends',pipeline=PIPELINE)\n", "_sdf = mgr.read(aggregate='friends',pipeline=PIPELINE)\n",
@ -86,41 +87,13 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'host': 'klingon.io',\n",
" 'port': 27017,\n",
" 'username': 'me',\n",
" 'password': 'foobar',\n",
" 'db': 'foo',\n",
" 'collection': 'friends',\n",
" 'authSource': '<authdb>',\n",
" 'mechamism': '<SCRAM-SHA-256|MONGODB-CR|SCRAM-SHA-1>'}"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"{\n",
" \"host\":\"klingon.io\",\"port\":27017,\"username\":\"me\",\"password\":\"foobar\",\"db\":\"foo\",\"collection\":\"friends\",\n",
" \"authSource\":\"<authdb>\",\"mechamism\":\"<SCRAM-SHA-256|MONGODB-CR|SCRAM-SHA-1>\"\n",
"}"
] ]
}, },
{ {

66
notebooks/mssqlserver.ipynb
View File

@ -17,17 +17,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"['data transport version ', '2.0.0']\n"
]
}
],
"source": [ "source": [
"#\n", "#\n",
"# Writing to Google Bigquery database\n", "# Writing to Google Bigquery database\n",
@ -41,7 +33,7 @@
"MSSQL_AUTH_FILE= os.sep.join([AUTH_FOLDER,'mssql.json'])\n", "MSSQL_AUTH_FILE= os.sep.join([AUTH_FOLDER,'mssql.json'])\n",
"\n", "\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"msw = transport.factory.instance(provider=providers.MSSQL,table='friends',context='write',auth_file=MSSQL_AUTH_FILE)\n", "msw = transport.get.writer(provider=providers.MSSQL,table='friends',auth_file=MSSQL_AUTH_FILE)\n",
"msw.write(_data,if_exists='replace') #-- default is append\n", "msw.write(_data,if_exists='replace') #-- default is append\n",
"print (['data transport version ', transport.__version__])\n" "print (['data transport version ', transport.__version__])\n"
] ]
@ -59,30 +51,15 @@
"\n", "\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
" name age\n",
"0 James Bond 55\n",
"1 Steve Rogers 150\n",
"2 Steve Nyemba 44\n",
"\n",
"--------- STATISTICS ------------\n",
"\n",
" _counts \n",
"0 3 83\n"
]
}
],
"source": [ "source": [
"\n", "\n",
"import transport\n", "import transport\n",
@ -91,7 +68,7 @@
"AUTH_FOLDER = os.environ['DT_AUTH_FOLDER'] #-- location of the service key\n", "AUTH_FOLDER = os.environ['DT_AUTH_FOLDER'] #-- location of the service key\n",
"MSSQL_AUTH_FILE= os.sep.join([AUTH_FOLDER,'mssql.json'])\n", "MSSQL_AUTH_FILE= os.sep.join([AUTH_FOLDER,'mssql.json'])\n",
"\n", "\n",
"msr = transport.instance(provider=providers.MSSQL,table='friends',auth_file=MSSQL_AUTH_FILE)\n", "msr = transport.get.reader(provider=providers.MSSQL,table='friends',auth_file=MSSQL_AUTH_FILE)\n",
"_df = msr.read()\n", "_df = msr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n", "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
"_sdf = msr.read(sql=_query)\n", "_sdf = msr.read(sql=_query)\n",
@ -104,25 +81,31 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"{'dataset': 'demo', 'table': 'friends'}" "{'provider': 'sqlserver',\n",
" 'dataset': 'demo',\n",
" 'table': 'friends',\n",
" 'username': '<username>',\n",
" 'password': '<password>'}"
] ]
}, },
"execution_count": 3, "execution_count": 1,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -130,10 +113,17 @@
"source": [ "source": [
"\n", "\n",
"{\n", "{\n",
" \n", " \"provider\":\"sqlserver\",\n",
" \"dataset\":\"demo\",\"table\":\"friends\",\"username\":\"<username>\",\"password\":\"<password>\"\n", " \"dataset\":\"demo\",\"table\":\"friends\",\"username\":\"<username>\",\"password\":\"<password>\"\n",
"}" "}"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {

37
notebooks/mysql.ipynb
View File

@ -14,14 +14,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"2.0.0\n" "2.0.4\n"
] ]
} }
], ],
@ -33,7 +33,7 @@
"from transport import providers\n", "from transport import providers\n",
"import pandas as pd\n", "import pandas as pd\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"myw = transport.factory.instance(provider=providers.MYSQL,database='demo',table='friends',context='write',auth_file=\"/home/steve/auth-mysql.json\")\n", "myw = transport.get.writer(provider=providers.MYSQL,database='demo',table='friends',auth_file=\"/home/steve/auth-mysql.json\")\n",
"myw.write(_data,if_exists='replace') #-- default is append\n", "myw.write(_data,if_exists='replace') #-- default is append\n",
"print (transport.__version__)" "print (transport.__version__)"
] ]
@ -51,12 +51,13 @@
"\n", "\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -68,7 +69,7 @@
"1 Steve Rogers 150\n", "1 Steve Rogers 150\n",
"2 Steve Nyemba 44\n", "2 Steve Nyemba 44\n",
"--------- STATISTICS ------------\n", "--------- STATISTICS ------------\n",
" _counts avg\n", " _counts AVG(age)\n",
"0 3 83.0\n" "0 3 83.0\n"
] ]
} }
@ -77,7 +78,7 @@
"\n", "\n",
"import transport\n", "import transport\n",
"from transport import providers\n", "from transport import providers\n",
"myr = transport.instance(provider=providers.POSTGRESQL,database='demo',table='friends',auth_file='/home/steve/auth-mysql.json')\n", "myr = transport.get.reader(provider=providers.MYSQL,database='demo',table='friends',auth_file='/home/steve/auth-mysql.json')\n",
"_df = myr.read()\n", "_df = myr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n", "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
"_sdf = myr.read(sql=_query)\n", "_sdf = myr.read(sql=_query)\n",
@ -90,16 +91,18 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -109,21 +112,29 @@
" 'port': 3306,\n", " 'port': 3306,\n",
" 'username': 'me',\n", " 'username': 'me',\n",
" 'password': 'foobar',\n", " 'password': 'foobar',\n",
" 'provider': 'mysql',\n",
" 'database': 'demo',\n", " 'database': 'demo',\n",
" 'table': 'friends'}" " 'table': 'friends'}"
] ]
}, },
"execution_count": 1, "execution_count": 5,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"{\n", "{\n",
" \"host\":\"klingon.io\",\"port\":3306,\"username\":\"me\",\"password\":\"foobar\",\n", " \"host\":\"klingon.io\",\"port\":3306,\"username\":\"me\",\"password\":\"foobar\", \"provider\":\"mysql\",\n",
" \"database\":\"demo\",\"table\":\"friends\"\n", " \"database\":\"demo\",\"table\":\"friends\"\n",
"}" "}"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {

29
notebooks/postgresql.ipynb
View File

@ -14,14 +14,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"2.0.0\n" "2.0.4\n"
] ]
} }
], ],
@ -33,7 +33,7 @@
"from transport import providers\n", "from transport import providers\n",
"import pandas as pd\n", "import pandas as pd\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"pgw = transport.factory.instance(provider=providers.POSTGRESQL,database='demo',table='friends',context='write')\n", "pgw = transport.get.writer(provider=providers.POSTGRESQL,database='demo',table='friends')\n",
"pgw.write(_data,if_exists='replace') #-- default is append\n", "pgw.write(_data,if_exists='replace') #-- default is append\n",
"print (transport.__version__)" "print (transport.__version__)"
] ]
@ -49,14 +49,16 @@
"- Basic read of the designated table (friends) created above\n", "- Basic read of the designated table (friends) created above\n",
"- Execute an aggregate SQL against the table\n", "- Execute an aggregate SQL against the table\n",
"\n", "\n",
"\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -77,7 +79,7 @@
"\n", "\n",
"import transport\n", "import transport\n",
"from transport import providers\n", "from transport import providers\n",
"pgr = transport.instance(provider=providers.POSTGRESQL,database='demo',table='friends')\n", "pgr = transport.get.reader(provider=providers.POSTGRESQL,database='demo',table='friends')\n",
"_df = pgr.read()\n", "_df = pgr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n", "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
"_sdf = pgr.read(sql=_query)\n", "_sdf = pgr.read(sql=_query)\n",
@ -90,16 +92,18 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -109,18 +113,19 @@
" 'port': 5432,\n", " 'port': 5432,\n",
" 'username': 'me',\n", " 'username': 'me',\n",
" 'password': 'foobar',\n", " 'password': 'foobar',\n",
" 'provider': 'postgresql',\n",
" 'database': 'demo',\n", " 'database': 'demo',\n",
" 'table': 'friends'}" " 'table': 'friends'}"
] ]
}, },
"execution_count": 1, "execution_count": 4,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"{\n", "{\n",
" \"host\":\"klingon.io\",\"port\":5432,\"username\":\"me\",\"password\":\"foobar\",\n", " \"host\":\"klingon.io\",\"port\":5432,\"username\":\"me\",\"password\":\"foobar\", \"provider\":\"postgresql\",\n",
" \"database\":\"demo\",\"table\":\"friends\"\n", " \"database\":\"demo\",\"table\":\"friends\"\n",
"}" "}"
] ]

22
notebooks/sqlite.ipynb
View File

@ -18,7 +18,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"2.0.0\n" "2.0.4\n"
] ]
} }
], ],
@ -30,7 +30,7 @@
"from transport import providers\n", "from transport import providers\n",
"import pandas as pd\n", "import pandas as pd\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n", "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"sqw = transport.factory.instance(provider=providers.SQLITE,database='/home/steve/demo.db3',table='friends',context='write')\n", "sqw = transport.get.writer(provider=providers.SQLITE,database='/home/steve/demo.db3',table='friends')\n",
"sqw.write(_data,if_exists='replace') #-- default is append\n", "sqw.write(_data,if_exists='replace') #-- default is append\n",
"print (transport.__version__)" "print (transport.__version__)"
] ]
@ -46,9 +46,11 @@
"- Basic read of the designated table (friends) created above\n", "- Basic read of the designated table (friends) created above\n",
"- Execute an aggregate SQL against the table\n", "- Execute an aggregate SQL against the table\n",
"\n", "\n",
"\n",
"**NOTE**\n", "**NOTE**\n",
"\n", "\n",
"It is possible to use **transport.factory.instance** or **transport.instance** they are the same. It allows the maintainers to know that we used a factory design pattern." "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
] ]
}, },
{ {
@ -74,10 +76,10 @@
"\n", "\n",
"import transport\n", "import transport\n",
"from transport import providers\n", "from transport import providers\n",
"pgr = transport.instance(provider=providers.SQLITE,database='/home/steve/demo.db3',table='friends')\n", "sqr = transport.get.reader(provider=providers.SQLITE,database='/home/steve/demo.db3',table='friends')\n",
"_df = pgr.read()\n", "_df = sqr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n", "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
"_sdf = pgr.read(sql=_query)\n", "_sdf = sqr.read(sql=_query)\n",
"print (_df)\n", "print (_df)\n",
"print ('--------- STATISTICS ------------')\n", "print ('--------- STATISTICS ------------')\n",
"print (_sdf)" "print (_sdf)"
@ -87,11 +89,13 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The cell bellow show the content of an auth_file, in this case if the dataset/table in question is not to be shared then you can use auth_file with information associated with the parameters.\n", "An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n", "\n",
"**NOTE**:\n", "1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n", "\n",
"The auth_file is intended to be **JSON** formatted. This is an overkill for SQLite ;-)" "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
] ]
}, },
{ {