Using MongoDB

Update Data

You can use the update_one() and the update_many() methods to update documents of a collection. The update_one() method updates a single document. Use update_many() to update all documents that match the criteria. The methods accept the following parameters:

• a filter document to match the documents to update,
• an update document to specify the modification to perform, and
• an optional upsert parameter.

To change a field value, MongoDB provides update operators to modify values. Some update operators, such as $set, will create the field if the field does not exist.

The following operation updates the first document in the Cu-F chemical system (chemsys), using the $set operator to update the tags field and the $currentDate operator to update the lastModified field with the current date.

result = db.materials.update_one(
    {"chemsys": "Cu-F"},
    {
        "$set": {
            "tags": ["halide"]
        },
        "$currentDate": {"lastModified": True}
    }
)

The object returned reports the count of documents matched and modified:

result.matched_count

1

result.modified_count

1

db.materials.find_one({"chemsys": "Cu-F"},
                      {"tags": 1, "lastModified": 1, "material_id": 1})

{'_id': ObjectId('56ced2fb7943f6405b32a0b6'),
 'lastModified': datetime.datetime(2016, 2, 25, 10, 10, 7, 525000),
 'material_id': 'mp-1229',
 'tags': ['halide']}

To update an embedded field, use the dot notation:

result = db.materials.update_one(
    {"material_id": "mp-1229"},
    {"$set": {"elasticity.calculations.source": "Private communication"}}
)

print(result.matched_count, result.modified_count)

1 1

The update_one() method updates a single document. To update multiple documents, use the update_many() method. Let’s tag all of the halides, where a halide is a binary compounds for which one part is a halogen atom and the other part is an element that is less electronegative than the halogen. Specifically, we will use the $addToSet update operator to add “halide” idempotently to a compound’s tags array, creating the array if it does not exist.

First, let’s generate a list of halide chemical systems. The pymatgen Python package includes a JSON file, a copy of which you downloaded earlier, with basic information on chemical elements, including Pauling electronegativity (“X”) if known. Let’s load it as a new MongoDB collection:

import json

db.elements.drop() # If it exists, clear it
with open('data/periodic_table.json') as f:
    for symbol, rest in json.load(f).items():
        doc = {"Symbol": symbol}
        doc.update(rest)
        db.elements.insert_one(doc)

Now, let’s use our new collection to write a generator for halide systems. The chemsys values in our materials collection are sorted alphabetically, i.e. we say “Cu-F” rather than “F-Cu”, so we have to account for that. You are not expected to know the Python syntax for doing this – the point here is to demonstrate how a JSON data source can quickly be ingested by MongoDB and how what you’ve learned so far about query operators can be used effectively to find what we need from the data.

halogens = ["F", "Cl", "Br", "I", "At"]
def halide_systems():
    for halogen in halogens:
        X = db.elements.find_one({"Symbol": halogen})["X"]
        for doc in db.elements.find({"X": {"$lt": X}}):
            yield "-".join(sorted([doc["Symbol"], halogen]))

To demonstrate use of the generator let’s see which systems contain copper:

[s for s in list(halide_systems()) if 'Cu' in s]

['Cu-F', 'Cl-Cu', 'Br-Cu', 'Cu-I', 'At-Cu']

Now, we’re ready for the show. We use the $in query operator to test for membership of a compound’s chemsys in our list of halide systems:

result = db.restaurants.update_many(
    {"chemsys": {"$in": list(halide_systems())}},
    {"$addToSet": {"tags": "halide"}}
)

What’s the damage?

result.matched_count, result.modified_count

(1127, 1127)

It looks like we have 1127 halides in our materials collection. Equivalently,

db.materials.find({"tags": "halide"}).count()

1127

result = db.materials.update_one(
   {"material_id": "mp-NaN"},
   {"$set": {"elasticity.calculations.source": "Private communication"}}
)

db.materials.find_one({"material_id": "mp-NaN"})

result = db.materials.update_one(
   {"material_id": "mp-NaN"},
   {"$set": {"elasticity.calculations.source": "Private communication"}},
   upsert=True
)