Migrating CSV, JSON and XML Data with Client Python

Goal
A Quick Look at the Schema
An Overview
Get Started
Include the Data Files
Set up the migration mechanism
build_phone_call_graph(inputs)
load_data_into_typedb(input, session)
The Template Functions
DataFormat-specific Implementation
Putting It All Together
Time to Load
Next

Goal

In this tutorial, our aim is to migrate some actual data to the phone_calls knowledge graph that we defined previously using Client Python.

A Quick Look at the Schema

Before we get started with migration, let’s have a quick reminder of how the schema for the phone_calls knowledge graph looks like.

The Visualised Schema

An Overview

Let’s go through a summary of how the migration takes place.

we need a way to talk to our TypeDB database. To do this, we use Client Python.
we go through each data file, extracting each data item and parsing it to a Python dictionary.
we pass each data item (in the form of a Python dictionary) to its corresponding template function, which in turn gives us the constructed TypeQL query for inserting that item into TypeDB.
we execute each of those queries to load the data into our target database — phone_calls.

Before moving on, make sure you have Python3 and Pip3 installed and the TypeDB Server running on your machine.

Get Started

Create a directory named phone_calls on your desktop.
cd to the phone_calls directory via terminal.
Run pip3 install typedb-client to install the TypeDB Client Python.
Open the phone_calls directory in your favourite text editor.
Create a migrate.py file in the root directory. This is where we’re going to write all our code.

Include the Data Files

Pick one of the data formats below and download the files. After you download them, place the four files under the files/phone-calls/data directory. We need these to load their data into our phone_calls knowledge graph.

CSV

JSON

XML

Set up the migration mechanism

All code that follows is to be written in phone_calls/migrate.py.

from typedb.client import TypeDB 

inputs = [
    {
        "data_path": "files/phone-calls/data/companies",
        "template": company_template
    },
    {
        "data_path": "files/phone-calls/data/people",
        "template": person_template
    },
    {
        "data_path": "files/phone-calls/data/contracts",
        "template": contract_template
    },
    {
        "data_path": "files/phone-calls/data/calls",
        "template": call_template
    }
]

build_phone_call_graph(inputs)

First thing first, we import the typedb module. We use it for connecting to our phone_calls database.

Next, we declare the inputs. More on this later. For now, what we need to understand about inputs — it’s a list of dictionaries, each one containing:

The path to the data file
The template function that receives a dictionary and produces the TypeQL insert query. we define these template functions in a bit.

Let’s move on.

build_phone_call_graph(inputs)

from typedb.client import TypeDB, SessionType

def build_phone_call_graph(inputs):
    with TypeDB.core_client("localhost:1729") as client:
        with client.session("phone_calls", SessionType.DATA) as session:
            for input in inputs:
                print("Loading from [" + input["data_path"] + "] into TypeDB ...")
                load_data_into_typedb(input, session)

# ...

This is the main and only function we need to call to start loading data into TypeDB.

What happens in this function, is as follows:

A TypeDB client is created, connected to the server we have running locally.
A session is created, connected to the database phone_calls. Note that by using with, we indicate that the session closes after it’s been used.
For each input dictionary in inputs, we call the load_data_into_typedb(input, session). This takes care of loading the data as specified in the input dictionary into our database.

load_data_into_typedb(input, session)

from typedb.client import TransactionType

def load_data_into_typedb(input, session):
    items = parse_data_to_dictionaries(input)

    for item in items:
        with session.transaction(TransactionType.WRITE) as transaction:
            typeql_insert_query = input["template"](item)
            print("Executing TypeQL Query: " + typeql_insert_query)
            transaction.query().insert(typeql_insert_query)
            transaction.commit()

    print("\nInserted " + str(len(items)) + " items from [ " + input["data_path"] + "] into TypeDB.\n")

# ...

In order to load data from each file into TypeDB, we need to:

retrieve a list containing dictionaries, each of which represents a data item. We do this by calling parse_data_to_dictionaries(input)
for each dictionary in items: a) create a transaction, which closes once used, b) construct the typeql_insert_query using the corresponding template function, c) execute the query and d) commit the transaction.

[Important] To avoid running out of memory, it’s recommended that every single query gets created and committed in a single transaction. However, for faster migration of large datasets, this can happen once for every `n` queries, where `n` is the maximum number of queries guaranteed to run on a single transaction.

Before we move on to parsing the data into dictionaries, let’s start with the template functions.

The Template Functions

Templates are simple functions that accept a dictionary, representing a single data item. The values within this dictionary fill in the blanks of the query template. The result is a TypeQL insert query. We need 4 of them. Let’s go through them one by one.

company_template

def company_template(company):
    return 'insert $company isa company, has name "' + company["name"] + '";'

Example:

Goes in:
```
{ "name": "Telecom" }
```
Comes out:

insert $company isa company, has name "Telecom";

person_template

def person_template(person):
    # insert person
    typeql_insert_query = 'insert $person isa person, has phone-number "' + person["phone_number"] + '"'
    if "first_name" in person:
        # person is a customer
        typeql_insert_query += ", has is-customer true"
        typeql_insert_query += ', has first-name "' + person["first_name"] + '"'
        typeql_insert_query += ', has last-name "' + person["last_name"] + '"'
        typeql_insert_query += ', has city "' + person["city"] + '"'
        typeql_insert_query += ", has age " + str(person["age"])
    else:
        # person is not a customer
        typeql_insert_query += ", has is-customer false"
    typeql_insert_query += ";"
    return typeql_insert_query

Example:

Goes in:
```
{ "phone_number": "+44 091 xxx" }
```
Comes out:

insert $person isa person, has phone-number "+44 091 xxx", has is-customer false;

or:

Goes in:

{ "first_name": "Jackie", "last_name": "Joe", "city": "Jimo", "age": 77, "phone_number": "+00 091 xxx"}

Comes out:

insert $person isa person, has phone-number "+00 091 xxx", has is-customer true, has first-name "Jackie", has last-name "Joe", has city "Jimo", has age 77;

contract_template

def contract_template(contract):
    # match company
    typeql_insert_query = 'match $company isa company, has name "' + contract["company_name"] + '";'
    # match person
    typeql_insert_query += ' $customer isa person, has phone-number "' + contract["person_id"] + '";'
    # insert contract
    typeql_insert_query += " insert (provider: $company, customer: $customer) isa contract;"
    return typeql_insert_query

Example:

Goes in:

{ "company_name": "Telecom", "person_id": "+00 091 xxx" }

Comes out:

match $company isa company, has name "Telecom"; $customer isa person, has phone-number "+00 091 xxx"; insert (provider: $company, customer: $customer) isa contract;

call_template

def call_template(call):
    # match caller
    typeql_insert_query = 'match $caller isa person, has phone-number "' + call["caller_id"] + '";'
    # match callee
    typeql_insert_query += ' $callee isa person, has phone-number "' + call["callee_id"] + '";'
    # insert call
    typeql_insert_query += " insert $call(caller: $caller, callee: $callee) isa call; $call has started-at " + call["started_at"] + "; $call has duration " + str(call["duration"]) + ";"
    return typeql_insert_query

Example:

Goes in:

{ "caller_id": "+44 091 xxx", "callee_id": "+00 091 xxx", "started_at": 2018-08-10T07:57:51, "duration": 148 }

Comes out:

match $caller isa person, has phone-number "+44 091 xxx"; $callee isa person, has phone-number "+00 091 xxx"; insert $call(caller: $caller, callee: $callee) isa call; $call has started-at 2018-08-10T07:57:51; $call has duration 148;

We’ve now created a template for each and all four concepts that were previously defined in the schema.

It’s time for the implementation of parse_data_to_dictionaries(input).

DataFormat-specific Implementation

The implementation for parse_data_to_dictionaries(input) differs based on the format of our data files.

[tab:CSV] We use Python’s built-in [`csv` library](https://docs.python.org/3/library/csv.html#dialects-and-formatting-parameters). Let’s import the module for it. ```python from typedb.client import TypeDB import csv #... ``` Moving on, we write the implementation of `parse_data_to_dictionaries(input)` for parsing `.csv` files. Note that we use [DictReader](https://docs.python.org/3/library/csv.html#csv.DictReader) to map the information in each row to a dictionary. ```python def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".csv") as data: for row in csv.DictReader(data, skipinitialspace = True): item = { key: value for key, value in row.items() } items.append(item) return items ``` Besides this function, we need to make one more change. Given the nature of CSV files, the dictionary produced has all the columns of the `.csv` file as its keys, even when the value is not there, it’ll be taken as a blank string. For this reason, we need to change one line in our `person_template` function. `if "first_name" in person` becomes `if person["first_name"] == ""`. [tab:end] [tab:JSON] We use [ijson](https://pypi.org/project/ijson/), an iterative JSON parser with a standard Python iterator interface. Via the terminal, while in the `phone_calls` directory, run `pip3 install ijson` and import the module for it. ```python from typedb.client import TypeDB import ijson # ... ``` Moving on, we write the implementation of `parse_data_to_dictionaries(input)` for processing `.json` files. ```python def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".json") as data: for item in ijson.items(data, "item"): items.append(item) return items ``` [tab:end] [tab:XML] We use Python’s built-in [`xml.etree.cElementTree` library](https://docs.python.org/2/library/xml.etree.elementtree.html). Let’s import the module for it. ```python from typedb.client import TypeDB import xml.etree.cElementTree as et # ... ``` For parsing XML data, we need to know the target tag name. This needs to be specified for each data file in our `inputs` deceleration. ```python # ... inputs = [ { "data_path": "files/phone-calls/data/companies", "template": company_template, "selector": "company" }, { "data_path": "files/phone-calls/data/people", "template": person_template, "selector": "person" }, { "data_path": "files/phone-calls/data/contracts", "template": contract_template, "selector": "contract" }, { "data_path": "files/phone-calls/data/calls", "template": call_template, "selector": "call" } ] # ... ``` And now for the implementation of `parse_data_to_dictionaries(input)` for parsing `.xml` files. The implementation below, although, not the most generic, performs well with very large `.xml` files. Note that many libraries that do xml to dictionary parsing, pull in the entire `.xml` file into memory first. There is nothing wrong with that approach when you’re dealing with small files, but when it comes to large files, that’s just a no go. ```python def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".xml", "rb") as inputfile: ## we are in the file keep_adding_lines = False for line in inputfile: if "<" + input["selector"] + ">" in str(line): ## now: at the start of a new target tag buffer = line keep_adding_lines = True elif "</" + input["selector"] + ">" in str(line): ## now: the tag is complete buffer += line keep_adding_lines = False ## convert the buffer (string) to a structured tag tnode = et.fromstring(buffer) ## parse the tag to a dictionary item = {} for element in list(tnode): item[element.tag] = element.text ## append the item to the list items.append(item) ## delete the buffer to free the memory del buffer elif keep_adding_lines: ## now: inside the target tag buffer += line return items ``` [tab:end]

Putting It All Together

Here is how our migrate.py looks like for each data format.

[tab:CSV] ```python from typedb.client import TypeDB, SessionType, TransactionType import csv def build_phone_call_graph(inputs): with TypeDB.core_client("localhost:1729") as client: with client.session("phone_calls", SessionType.DATA) as session: for input in inputs: print("Loading from [" + input["data_path"] + "] into TypeDB ...") load_data_into_typedb(input, session) def load_data_into_typedb(input, session): items = parse_data_to_dictionaries(input) with session.transaction(TransactionType.WRITE) as transaction: for item in items: typeql_insert_query = input["template"](item) print("Executing TypeQL Query: " + typeql_insert_query) transaction.query().insert(typeql_insert_query) transaction.commit() print("\nInserted " + str(len(items)) + " items from [ " + input["data_path"] + "] into TypeDB.\n") def company_template(company): return 'insert $company isa company, has name "' + company["name"] + '";' def person_template(person): # insert person typeql_insert_query = 'insert $person isa person, has phone-number "' + person["phone_number"] + '"' if person["first_name"] == "": # person is not a customer typeql_insert_query += ", has is-customer false" else: # person is a customer typeql_insert_query += ", has is-customer true" typeql_insert_query += ', has first-name "' + person["first_name"] + '"' typeql_insert_query += ', has last-name "' + person["last_name"] + '"' typeql_insert_query += ', has city "' + person["city"] + '"' typeql_insert_query += ", has age " + str(person["age"]) typeql_insert_query += ";" return typeql_insert_query def contract_template(contract): # match company typeql_insert_query = 'match $company isa company, has name "' + contract["company_name"] + '";' # match person typeql_insert_query += ' $customer isa person, has phone-number "' + contract["person_id"] + '";' # insert contract typeql_insert_query += " insert (provider: $company, customer: $customer) isa contract;" return typeql_insert_query def call_template(call): # match caller typeql_insert_query = 'match $caller isa person, has phone-number "' + call["caller_id"] + '";' # match callee typeql_insert_query += ' $callee isa person, has phone-number "' + call["callee_id"] + '";' # insert call typeql_insert_query += (" insert $call(caller: $caller, callee: $callee) isa call; " + "$call has started-at " + call["started_at"] + "; " + "$call has duration " + str(call["duration"]) + ";") return typeql_insert_query def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".csv") as data: # 1 for row in csv.DictReader(data, skipinitialspace = True): item = { key: value for key, value in row.items() } items.append(item) # 2 return items inputs = [ { "data_path": "files/phone-calls/data/companies", "template": company_template }, { "data_path": "files/phone-calls/data/people", "template": person_template }, { "data_path": "files/phone-calls/data/contracts", "template": contract_template }, { "data_path": "files/phone-calls/data/calls", "template": call_template } ] build_phone_call_graph(inputs=inputs) ``` [tab:end] [tab:JSON] ```python from typedb.client import TypeDB, SessionType, TransactionType import ijson def build_phone_call_graph(inputs): with TypeDB.core_client("localhost:1729") as client: with client.session("phone_calls", SessionType.DATA) as session: for input in inputs: print("Loading from [" + input["data_path"] + "] into TypeDB ...") load_data_into_typedb(input, session) def load_data_into_typedb(input, session): items = parse_data_to_dictionaries(input) with session.transaction(TransactionType.WRITE) as transaction: for item in items: typeql_insert_query = input["template"](item) print("Executing TypeQL Query: " + typeql_insert_query) transaction.query().insert(typeql_insert_query) transaction.commit() print("\nInserted " + str(len(items)) + " items from [ " + input["data_path"] + "] into TypeDB.\n") def company_template(company): return 'insert $company isa company, has name "' + company["name"] + '";' def person_template(person): # insert person typeql_insert_query = 'insert $person isa person, has phone-number "' + person["phone_number"] + '"' if "first_name" in person: # person is a customer typeql_insert_query += ", has is-customer true" typeql_insert_query += ', has first-name "' + person["first_name"] + '"' typeql_insert_query += ', has last-name "' + person["last_name"] + '"' typeql_insert_query += ', has city "' + person["city"] + '"' typeql_insert_query += ", has age " + str(person["age"]) else: # person is not a customer typeql_insert_query += ", has is-customer false" typeql_insert_query += ";" return typeql_insert_query def contract_template(contract): # match company typeql_insert_query = 'match $company isa company, has name "' + contract["company_name"] + '";' # match person typeql_insert_query += ' $customer isa person, has phone-number "' + contract["person_id"] + '";' # insert contract typeql_insert_query += " insert (provider: $company, customer: $customer) isa contract;" return typeql_insert_query def call_template(call): # match caller typeql_insert_query = 'match $caller isa person, has phone-number "' + call["caller_id"] + '";' # match callee typeql_insert_query += ' $callee isa person, has phone-number "' + call["callee_id"] + '";' # insert call typeql_insert_query += (" insert $call(caller: $caller, callee: $callee) isa call; " + "$call has started-at " + call["started_at"] + "; " + "$call has duration " + str(call["duration"]) + ";") return typeql_insert_query def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".json") as data: for item in ijson.items(data, "item"): items.append(item) return items inputs = [ { "data_path": "files/phone-calls/data/companies", "template": company_template }, { "data_path": "files/phone-calls/data/people", "template": person_template }, { "data_path": "files/phone-calls/data/contracts", "template": contract_template }, { "data_path": "files/phone-calls/data/calls", "template": call_template } ] build_phone_call_graph(inputs) ``` [tab:end] [tab:XML] ```python from typedb.client import TypeDB, SessionType, TransactionType import xml.etree.cElementTree as et def build_phone_call_graph(inputs): with TypeDB.core_client("localhost:1729") as client: with client.session("phone_calls", SessionType.DATA) as session: for input in inputs: print("Loading from [" + input["data_path"] + "] into TypeDB ...") load_data_into_typedb(input, session) def load_data_into_typedb(input, session): items = parse_data_to_dictionaries(input) with session.transaction(TransactionType.WRITE) as transaction: for item in items: typeql_insert_query = input["template"](item) print("Executing TypeQL Query: " + typeql_insert_query) transaction.query().insert(typeql_insert_query) transaction.commit() print("\nInserted " + str(len(items)) + " items from [ " + input["data_path"] + "] into TypeDB.\n") def company_template(company): return 'insert $company isa company, has name "' + company["name"] + '";' def person_template(person): # insert person typeql_insert_query = 'insert $person isa person, has phone-number "' + person["phone_number"] + '"' if "first_name" in person: # person is a customer typeql_insert_query += ", has is-customer true" typeql_insert_query += ', has first-name "' + person["first_name"] + '"' typeql_insert_query += ', has last-name "' + person["last_name"] + '"' typeql_insert_query += ', has city "' + person["city"] + '"' typeql_insert_query += ", has age " + str(person["age"]) else: # person is not a customer typeql_insert_query += ", has is-customer false" typeql_insert_query += ";" return typeql_insert_query def contract_template(contract): # match company typeql_insert_query = 'match $company isa company, has name "' + contract["company_name"] + '";' # match person typeql_insert_query += ' $customer isa person, has phone-number "' + contract["person_id"] + '";' # insert contract typeql_insert_query += " insert (provider: $company, customer: $customer) isa contract;" return typeql_insert_query def call_template(call): # match caller typeql_insert_query = 'match $caller isa person, has phone-number "' + call["caller_id"] + '";' # match callee typeql_insert_query += ' $callee isa person, has phone-number "' + call["callee_id"] + '";' # insert call typeql_insert_query += (" insert $call(caller: $caller, callee: $callee) isa call; " + "$call has started-at " + call["started_at"] + "; " + "$call has duration " + str(call["duration"]) + ";") return typeql_insert_query def parse_data_to_dictionaries(input): items = [] with open(input["data_path"] + ".xml", "rb") as inputfile: append = False for line in inputfile: if "<" + input["selector"] + ">" in str(line): ## start of a new xml tag buffer = line append = True elif "</" + input["selector"] + ">" in str(line): ## we got a complete xml tag buffer += line append = False tnode = et.fromstring(buffer) ## parse the tag to a dictionary and append to items item = {} for element in list(tnode): item[element.tag] = element.text items.append(item) ## delete the buffer to free the memory del buffer elif append: ## inside the current xml tag buffer += line return items inputs = [ { "data_path": "files/phone-calls/data/companies", "template": company_template, "selector": "company" }, { "data_path": "files/phone-calls/data/people", "template": person_template, "selector": "person" }, { "data_path": "files/phone-calls/data/contracts", "template": contract_template, "selector": "contract" }, { "data_path": "files/phone-calls/data/calls", "template": call_template, "selector": "call" } ] build_phone_call_graph(inputs) ``` [tab:end]

Time to Load

Run python3 migrate.py

Sit back, relax and watch the logs while the data starts pouring into TypeDB.

… So Far With the Migration

We started off by setting up our project and positioning the data files.

Next, we went on to set up the migration mechanism, one that was independent of the data format.

Then, we went ahead and wrote the template functions whose only job was to construct a TypeQL insert query based on the data passed to them.

After that, we learned how files with different data formats can be parsed into Python dictionaries.

Lastly, we ran python3 migrate.py which fired the build_phone_call_graph function with the given inputs. This loaded the data into our TypeDB knowledge graph.

Now that we have some actual data in our knowledge graph, we can go ahead and query for insights.