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pivot_forecast
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refactor work

This commit is contained in:
Paul Trowbridge 2022-05-06 23:07:42 -04:00
parent a8a14dda2b
commit 9e381f7d78
6 changed files with 357 additions and 1018 deletions
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204
index.js
View File

@ -33,130 +33,14 @@ var Postgres = new pg.Client({
});
Postgres.connect();
//------------create a callable sql exec func that return first rows----------------
Postgres.FirstRow = function(inSQL, args, inResponse) {
Postgres.query(inSQL, args, (err, res) => {
if (err === null) {
//need to test if the response is an object or an array
//inResponse.json(res.rows[0]);
if (Array.isArray(res)) {
inResponse.json(res[1].rows[0]);
}
else {
inResponse.json(res.rows[0]);
}
return;
}
console.log(err.stack);
inResponse.json(err.stack);
});
const SQLTemplate = (inSql, inJSON) => {
for (key in inJSON) {
inSql = inSql.replace(new RegExp(key, 'g'), inJSON[key]);
}
return inSql;
};
//------------route to test if the process is running-------------------------------
server.get('/', (req, res) => res.send('pivotscale api is running'))
//------------build forecast baseline that is a mirror of the target period---------
server.get('/baseline', bodyParser.json(), function(req, res) {
var sql = "";
var path = './routes/baseline/baseline.sql';
var args = [];
var app_req = JSON.stringify(req.body);
var app_baseline_from_date = req.body.app_baseline_from_date;
var app_baseline_to_date = req.body.app_baseline_to_date;
var app_first_forecast_date = req.body.app_first_forecast_date;
var app_openorder_cutoff = req.body.app_openorder_cutoff;
var app_plug_fromdate = req.body.app_plug_fromdate;
var app_plug_todate = req.body.app_plug_todate;
var app_openstatus_code = req.body.app_openstatus_code;
var app_forecast_name = req.body.app_forecast_name;
var callback = function(arg) {
sql = arg;
console.log(new Date().toISOString() + "-------------------------baseline build-----------------------------")
console.log(req.body);
//parse the where clause into the main sql statement
//sql = sql.replace(new RegExp("where_clause", 'g'), w)
sql = sql.replace(new RegExp("app_req", 'g'), app_req);
sql = sql.replace(new RegExp("app_baseline_from_date", 'g'), app_baseline_from_date);
sql = sql.replace(new RegExp("app_baseline_to_date", 'g'), app_baseline_to_date);
sql = sql.replace(new RegExp("app_first_forecast_date", 'g'), app_first_forecast_date);
sql = sql.replace(new RegExp("app_openorder_cutoff", 'g'), app_openorder_cutoff);
sql = sql.replace(new RegExp("app_openstatus_code", 'g'), app_openstatus_code);
sql = sql.replace(new RegExp("app_plug_fromdate", 'g'), app_plug_fromdate);
sql = sql.replace(new RegExp("app_plug_todate", 'g'), app_plug_todate);
sql = sql.replace(new RegExp("app_forecast_name", 'g'), app_forecast_name);
//execute the sql and send the result
args.push(req.body.app_baseline_from_date);
console.log(sql);
//res.send(sql);
Postgres.FirstRow(sql, [], res)
};
fs.readFile(path, 'utf8', function(err, data) {
if (!err) {
callback(data);
} else {
console.log("fatal error pulling sql file")
callback(err);
}
});
})
//------------scale a selected slice by the specified amounts-----------------------
server.get('/scale', bodyParser.json(), function(req, res) {
var sql = "";
var w = ""; //holds the where
var c = 1; //flag if body is empty
var d = 1;
var path = './routes/scale/scale.sql';
var args = [];
var app_pincr = req.body.app_pincr;
var app_req = JSON.stringify(req.body);
var app_vincr = req.body.app_vincr;
var app_forecast_name = req.body.app_forecast_name;
var callback = function(arg) {
sql = arg;
({ c, w, d } = build_where(req, c, w, d, args));
//if there was no body sent, return with nothing
//if (c == 1) {
// res.send("no body was sent");
// return;
//}
console.log(new Date().toISOString() + "-------------------------scale type adjustment----------------------")
console.log(JSON.stringify(req.body));
//parse the where clause into the main sql statement
//sql = sql.replace(new RegExp("where_clause", 'g'), w)
//sql = sql.replace(new RegExp("app_pincr", 'g'), app_pincr);
sql = sql.replace(new RegExp("app_req", 'g'), app_req);
sql = sql.replace(new RegExp("app_forecast_name", 'g'), app_forecast_name);
//sql = sql.replace(new RegExp("app_vincr", 'g'), app_vincr);
sql = sql.replace(new RegExp("app_where", 'g'), w);
//execute the sql and send the result
args.push(req.body.app_baseline_from_date);
console.log(sql);
//send only the sql as the result of the route for debug
//res.send(sql);
Postgres.FirstRow(sql, [], res)
};
fs.readFile(path, 'utf8', function(err, data) {
if (!err) {
callback(data);
} else {
console.log("fatal error pulling sql file")
callback(err);
}
});
})
function build_where(req, c, w, d, args) {
const build_where = (req, c, w, d, args) => {
//loop through each top level item expected to be a simple key/value list reflecting the column and the target value
// "part":"XFRM500", "customer":"Sanford and Son" --> SQL --> part = 'XFRM500'
// AND customer = 'Sanford and Son'
@ -167,7 +51,7 @@ function build_where(req, c, w, d, args) {
if (c > 1) {
w = w +
`
AND `;
AND `;
}
if (Array.isArray(req.body.app_scenario[i])) {
//if the scenario key has a value that is an array of items, push it into an `IN` statement
@ -189,3 +73,75 @@ function build_where(req, c, w, d, args) {
};
return { c, w, d };
}
//------------route to test if the process is running-------------------------------
server.get('/', (req, res) => res.send('pivotscale api is running'))
//------------build forecast baseline that is a mirror of the target period---------
server.get('/baseline', bodyParser.json(), function(req, res) {
var sql = "";
var path = './routes/baseline/baseline.sql';
var args = [];
fs.readFile(path, 'utf8', function(err, fileContents) {
if (err) {
console.log("fatal error pulling sql file");
return;
}
console.log(new Date().toISOString() + "-------------------------baseline build-----------------------------")
sql = SQLTemplate(fileContents, {
...req.body,
app_req: JSON.stringify(req.body)
});
Postgres.query(sql, []).then((result, error) => {
res.json(result[1].rows[0]);
});
});
});
//------------scale a selected slice by the specified amounts-----------------------
server.get('/scale', bodyParser.json(), function(req, res) {
var sql = "";
var w = ""; //holds the where
var c = 1; //flag if body is empty
var d = 1;
var path = './routes/scale/scale.sql';
var args = [];
fs.readFile(path, 'utf8', function(err, data) {
if (err) {
console.log("fatal error pulling sql file")
return
}
let { check, where } = build_where(req, c, w, d, args);
//if there was no body sent, return with nothing
//if (c == 1) {
// res.send("no body was sent");
// return;
//}
console.log(new Date().toISOString() + "-------------------------scale type adjustment----------------------")
let sql = SQLTemplate(data, {
app_req: JSON.stringify(req.body),
app_forecast_name: req.body.app_forecast_name,
app_where: where
});
//execute the sql and send the result
Postgres.query(sql, []).then((result, error) => {
res.json(result.rows[0]);
});
});
});

894
package-lock.json generated
View File

@ -1,897 +1,8 @@
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"engines": {
"node": ">= 0.6"
}
},
"node_modules/toidentifier": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/toidentifier/-/toidentifier-1.0.1.tgz",
"integrity": "sha512-o5sSPKEkg/DIQNmH43V0/uerLrpzVedkUh8tGNvaeXpfpuwjKenlSox/2O/BTlZUtEe+JG7s5YhEz608PlAHRA==",
"engines": {
"node": ">=0.6"
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"node_modules/type-is": {
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"dependencies": {
"media-typer": "0.3.0",
"mime-types": "~2.1.24"
},
"engines": {
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"node_modules/unpipe": {
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"engines": {
"node": ">= 0.8"
}
},
"node_modules/utils-merge": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/utils-merge/-/utils-merge-1.0.1.tgz",
"integrity": "sha1-n5VxD1CiZ5R7LMwSR0HBAoQn5xM=",
"engines": {
"node": ">= 0.4.0"
}
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"node_modules/vary": {
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"integrity": "sha1-IpnwLG3tMNSllhsLn3RSShj2NPw=",
"engines": {
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"node_modules/xtend": {
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"dependencies": {
"accepts": {
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@ -1315,8 +426,7 @@
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"requires": {}
"integrity": "sha512-6iCR0wVrro6OOHFsyavV+i6KYL4lVNyYAB9RD18w66xSzN+d8b66HiwuP30Gp1SH5O9T82fckkzsRjlrhD0ioQ=="
},
"pg-protocol": {
"version": "1.5.0",

119
routes/baseline/baseline.sql Normal file
View File

@ -0,0 +1,119 @@
DELETE FROM fc.dcard WHERE app_version = 'app_forecast_name';
WITH
req AS (SELECT $$app_req$$::jsonb j)
,ilog AS (
INSERT INTO
fc.log (doc)
SELECT
req.j
FROM
req
RETURNING *
)
,baseline AS (
SELECT
null::integer AS id
,null::integer AS logid
,o."Trans. Date"
,o."Post Date"
,o."Description"
,sum(o."Amount") AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,sum(o.app_units) AS app_units
,'app_forecast_name' AS app_version
,'baseline' AS app_iter
,(SELECT id FROM ilog) AS app_logid
FROM
fc.dcard o
WHERE
(
--base period orders booked....
"Trans. Date" BETWEEN 'app_baseline_from_date'::date AND 'app_baseline_to_date'::date
--...or any open orders currently booked before cutoff....
OR ("Description" IN (app_openstatus_code) and "Trans. Date" <= 'app_openorder_cutoff'::date)
--...or anything that shipped in that period
OR ("Post Date" BETWEEN 'app_baseline_from_date'::date AND 'app_baseline_to_date'::date)
)
--be sure to pre-exclude unwanted items, like canceled orders, non-gross sales, and short-ships
GROUP BY
o."Trans. Date"
,o."Post Date"
,o."Description"
,o."Category"
,o."Party"
,o."Reason"
UNION ALL
SELECT
null::integer AS id
,null::integer AS logid
,o."Trans. Date" + interval '1 year' AS "Trans. Date"
,o."Post Date" + interval '1 year' AS "Post Date"
,o."Description"
,sum(o."Amount") AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,sum(o.app_units) AS app_units
,'app_forecast_name' AS app_version
,'baseline' AS app_iter
,(SELECT id FROM ilog) AS app_logid
FROM
fc.dcard o
LEFT OUTER JOIN fc.perd tdate ON
(o."Trans. Date" + interval '1 year' )::date <@ tdate.drange
LEFT OUTER JOIN fc.perd pdate ON
(o."Post Date" + interval '1 year' )::date <@ pdate.drange
WHERE
"Trans. Date" BETWEEN 'app_plug_fromdate'::date AND 'app_plug_todate'::date
--be sure to pre-exclude unwanted items, like canceled orders, non-gross sales, and short-ships
GROUP BY
o."Trans. Date"
,o."Post Date"
,o."Description"
,o."Category"
,o."Party"
,o."Reason")
,incr AS (
SELECT
null::integer AS id
,null::integer AS logid
,o."Trans. Date" + interval '1 year' AS "Trans. Date"
,o."Post Date" + interval '1 year' AS "Post Date"
,o."Description"
,sum(o."Amount") AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,sum(o.app_units) AS app_units
,'app_forecast_name' AS app_version
,'baseline' AS app_iter
,(SELECT id FROM ilog) AS app_logid
FROM
baseline o
LEFT OUTER JOIN fc.perd tdate ON
(o."Trans. Date" + interval '1 year' )::date <@ tdate.drange
LEFT OUTER JOIN fc.perd pdate ON
(o."Post Date" + interval '1 year' )::date <@ pdate.drange
GROUP BY
o."Trans. Date"
,o."Post Date"
,o."Description"
,o."Category"
,o."Party"
,o."Reason"
)
,ins AS (
INSERT INTO
fc.dcard
SELECT
*
FROM
incr i
WHERE
i."Trans. Date" >= 'app_first_forecast_date'::date
OR i."Post Date" >= 'app_first_forecast_date'::date
RETURNING *
)
SELECT COUNT(*) num_rows FROM ins

2
routes/baseline/generate_route_sql.sh
View File

@ -1,4 +1,4 @@
# execure the sql for baseline which builds the sql and inserts into a table
#$PG -f routes/baseline/gen_baseline.sql
# pull the sql out of the table and write it to route directory
$PG -c "SELECT t FROM fc.sql WHERE cmd = 'baseline'" -t -A -o routes/baseline/baseline.sql
psql -h hptrow.me -p 54329 -d ubm -U ptrowbridge -c "SELECT t FROM fc.sql WHERE cmd = 'baseline'" -t -A -o routes/baseline/baseline.sql

2
routes/scale/generate_route_sql.sh
View File

@ -1,4 +1,4 @@
# execure the sql for scale which builds the sql and inserts into a table
#$PG -f ./routes/scale/gen_scale.sql
# pull the sql out of the table and write it to route directory
$PG -c "SELECT t FROM fc.sql WHERE cmd = 'scale'" -t -A -o ./routes/scale/scale.sql
psql -h hptrow.me -p 54329 -d ubm -U ptrowbridge -c "SELECT t FROM fc.sql WHERE cmd = 'scale'" -t -A -o ./routes/scale/scale.sql

154
routes/scale/scale.sql Normal file
View File

@ -0,0 +1,154 @@
WITH
req AS (SELECT $$app_req$$::jsonb j)
,target AS (
SELECT
(req.j->>'app_vincr')::numeric vincr --volume
,(req.j->>'app_pincr')::numeric pincr --price
FROM
req
)
-----this block is supposed to test for new products that might not be in baseline etc-------
,test AS (
SELECT
sum(app_units) FILTER (WHERE app_iter <> 'ACTUALS') total
,sum(app_units) FILTER (WHERE app_iter = 'baseline') base
FROM
fc.dcard o
WHERE
app_where
)
,ilog AS (
INSERT INTO
fc.log (doc)
SELECT
req.j
FROM
req
RETURNING *
)
------need to group basemix and forego any detail iterations
,basemix AS (
SELECT
o.id
,o.logid
,o."Trans. Date"
,o."Post Date"
,o."Description"
,sum(o."Amount") AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,sum(o.app_units) AS app_units
,'app_forecast_name' AS app_version
,'scale' AS app_iter
,0::bigint AS app_logid
FROM
fc.dcard o
WHERE
app_where
GROUP BY
o.id
,o.logid
,o."Trans. Date"
,o."Post Date"
,o."Description"
,o."Category"
,o."Party"
,o."Reason"
),
vscale AS (
SELECT
(SELECT vincr FROM target) AS target_increment
,sum(app_units) AS units
,CASE WHEN sum(app_units) = 0 THEN 0 ELSE (SELECT vincr FROM target)/sum(app_units) END AS factor
FROM
basemix
)
,volume_only AS (
SELECT
o.id
,o.logid
,o."Trans. Date"
,o."Post Date"
,o."Description"
,round(o."Amount" * vscale.factor,2) AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,round(o.app_units * vscale.factor,5) AS app_units
,'app_forecast_name' AS app_version
,'scale volume' AS app_iter
,(SELECT id FROM ilog) AS app_logid
FROM
basemix o
CROSS JOIN vscale
WHERE
vscale.factor <> 0
)
,volume AS (
SELECT * FROM volume_only
UNION ALL
SELECT * FROM basemix WHERE (SELECT factor FROM vscale) = 0
)
,pscale AS (
SELECT
(SELECT pincr FROM target) AS target_increment
,sum("Amount") AS value
,CASE WHEN (SELECT sum("Amount") FROM volume) = 0 THEN
--if the base value is -0- scaling will not work, need to generate price, factor goes to -0-
0
ELSE
CASE WHEN (SELECT factor FROM vscale) = 0
--if the incoming volume dataset has just basemix data, then create an absolute factor and multiply by basemix
THEN (SELECT pincr FROM target)/(SELECT sum("Amount") FROM volume)
--if the incoming volume table already has an adjusment, just need to create a true-up factor
--multiplying by the raw factor without adding 1 will work since this data set will be added to the volume data set
ELSE ((SELECT pincr FROM target)-(SELECT sum("Amount") FROM volume))/(SELECT sum("Amount") FROM volume)
END
END factor
,CASE WHEN (SELECT sum("Amount") FROM volume) = 0 THEN
CASE WHEN ((SELECT pincr::numeric FROM target) - (SELECT sum("Amount") FROM volume)) <> 0 THEN
--if the base value is -0- but the target value hasn't been achieved, derive a price to apply
((SELECT pincr::numeric FROM target) - (SELECT sum("Amount") FROM volume))/(SELECT sum(app_units) FROM volume)
ELSE
0
END
ELSE
0
END mod_price
FROM
volume
)
,pricing AS (
SELECT
o.id
,o.logid
,o."Trans. Date"
,o."Post Date"
,o."Description"
,round((CASE WHEN pscale.factor = 0 THEN o.app_units * pscale.mod_price ELSE o."Amount" * pscale.factor END)::numeric,2) AS "Amount"
,o."Category"
,o."Party"
,o."Reason"
,0::numeric AS app_units
,'app_forecast_name' AS app_version
,'scale price' AS app_iter
,(SELECT id FROM ilog) AS app_logid
FROM
volume o
CROSS JOIN pscale
WHERE
pscale.factor <> 0 or pscale.mod_price <> 0
)
INSERT INTO
fc.dcard
SELECT
*
FROM
volume_only
UNION ALL
SELECT
*
FROM
pricing